Saeed Varamesh; Sohrab Mohtaram Anbaran; Zahra Rouhnavaz
Abstract
Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed ...
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Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed the pattern of demand for resources and lands, changing the nature and quality of agricultural land, Historical and natural landscapes and surrounding urban areas through the transformation of these lands into residential areas. In recent decades, the suburban lands of cities have changed their use due to the urbanization process and the need of citizens for new residential areas and the surrounding lands, which are often high quality agricultural lands and gardens. This, along with things like industrialization and changing rainfall patterns, has destroyed the cover and natural environment of cities, and thus has posed many social and environmental challenges and endangered sustainable urban development, and as a result of this process, a lot of ecological pressure has been imposed on the natural ecosystem of the region. These changes are considered as one of the important and effective factors of social and environmental challenges. Today, remote sensing technology and GIS due to capabilities such as high monitoring power and resolution, frequent images, cost reduction, etc., To effectively identify and quantify land use changes and their effects on the environment and monitoring And rapid management of the growth and development of cities are used. In the present study, the aim is to evaluate the urban development of Ardabil in the last 30 years using remote sensing technology and satellite images.
Materials & Methods
Landsat satellite imagery was used to prepare land use maps for 1987, 2000 and 2017. In order to ensure the quality of data and bands, the images used in this research were first corrected for radiometric errors in ENVI 5.3 software environment. Then RVI, SAVI, NDVI, BI and IPVI indices were extracted. In the next step, maps related to filter texture, vegetation delineation and tasseled cap were prepared. At the end of this step, all the extracted layers were merged with the corrected image bands. Then satellite imagery using support vector machine algorithms, maximum similarity and artificial neural network with acceptable accuracy in six user classes (residential areas, covered agricultural lands, fallow, barren lands, urban forest and water) floor were classified. Then, to evaluate the classification accuracy, the overall accuracy and kappa coefficient were calculated for each of the maps.
Results & Discussion
According to the values of overall accuracy and kappa coefficient, which in 1987 for the support vector machine algorithm were 90% and 0.86, respectively, the maximum likelihood was 84.5% and 0.78, and the neural net was 90.5% and 0.87, respectively, in 2000. Overall accuracy and kappa coefficient for support vector machine algorithm 92% and 0.90, maximum likelihood 92.5% and 0.90 and neural net 92.6% and 0.90, and in 2017 overall accuracy and kappa coefficient for backup vector machine algorithm 90.6% and 0.88, maximum likelihood of 82.8% and 0.78 and for neural net were 88% and 0.85, it was found that the support vector machine algorithm has the highest accuracy compared to the other two algorithms. According to the results obtained from the study of satellite images classified by the support vector machine algorithm, the area of land built in Ardabil has increased from 20.023 square kilometers in 1987 to 41.554 square kilometers in 2017.
Conclusion
In general, it can be concluded that to evaluate the trend of urban sprawl and awareness of land use change patterns for optimal management and planning of cities, the use of satellite images, especially Landsat images is a suitable and low cost option. The results also showed that the rate of land use change to land uses is increasing and since land is the main element in urban development, so control how to use it and also calculate the real need of the city for land, to In order to provide different uses is effective. As a result, according to the findings of this study, in the absence of proper planning for this city due to favorable lands for urban development around the city, in the not too distant future, witness the destruction of agricultural lands around the city of Ardabil and conversion they will be residential areas.
Hamid Reza Ghafarian Malamiri; Hadi Zare Khormizi
Abstract
Introduction Investigation of vegetation changes can provide valuable information on global warming, the carbon cycle,water cycle and energy exchange. Satellite imagery timeseriesandremote sensing techniques offers a great deal of information on variations and dynamics of vegetation. Harmonic ANalysis ...
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Introduction Investigation of vegetation changes can provide valuable information on global warming, the carbon cycle,water cycle and energy exchange. Satellite imagery timeseriesandremote sensing techniques offers a great deal of information on variations and dynamics of vegetation. Harmonic ANalysis of Time Series (HANTS) has been effectively used to eliminate missing and outliers in time series of vegetation indices and land surface temperature (LST). However, the algorithm has been less frequently used to detect changes in vegetation and phenology. HANTSalgorithm decomposes periodic phenomena into their components(different sines and cosineswith different amplitudes and phases). The value of phases and amplitudes contains valuable information that can be used to investigate variations and identify different characteristics of vegetation such as growth and phenology. The present study aims to determine changes in each componentof vegetation time series in Iranin the past (1982, 1983, 1984 and 1985) and in recent years (2015, 2016, 2017 and 2018). Materials & Methods A daily NDVI product of AVHRR sensor, with a resolution of 0.05 at 0.05 ° (i.e. AVH13C1) was used in the present study. To obtain reliable harmonic components (amplitude and phase images), a reliable curve has to be fitted on the primary time series data. To do so, first,parameters of HANTS algorithm were determined and then Root Mean Square Error (RMSE) of the curves fitted on data related to four one-year time series in the past year’s category (1982, 1983, 1984 and 1985) and four one-year time series in recent year’s category (2015, 2016, 2017 and 2018) was estimated. This classification (i.e. four one-year time series in the past and recent years) was used for two reasons. First, extraction and comparison of harmonic components in a single time series in the past and recentyears’ categories cannot reflect real changes, as these changes may occur under the influence ofimpermanent dynamics of vegetation, such as dryor wet periods. Second, with four one-year time series in the past category (1982, 1983, 1984 and 1985), and four one-year time series (2015, 2016, 2017 and 2018) in recent years, statistical comparison of the harmonic components through one-way analysis of variance becomes possible. Following the production of reliable harmonic components, variations of the harmonic components in recent years were compared with their variations in the past using difference method, and mean difference of the harmonic components’value in four one-year time seriesin the past and present categories wasdetermined using one-way analysis of variance. Finally, some maps were produced to exhibitthe significance of differenceinmeans. Results & Discussion According to the findings of the present study, mean RMSE of the fitted curves in the four one-year periods ofpresent and past time series were always less than 0.1 unit of NDVI. Moreover, mean RMSEof total area of Iranin the past and present time series were 0.037 and 0.039, respectively. This demonstrates high efficiency of the HANTS algorithm in elimination of missing and outlier data in the daily-NDVI time series ofNOAA-AVHRR. Results indicate thatrange of zero amplitude (the mean value of NDVI or the average vegetation coverage) decreasesin the central, eastern and northeastern regions of Iran atthe 95% probability level (F-value <0.05), whileit increases significantly (F-value <0.05)in the north, northwestern and western regions (especially, the Alborz and Zagros mountains). The meandifferenceof phases value in the four-time series of the past and recent years’categories wassignificant at the 95% probability level (F-value <0.05). Compared to the past time series, first harmonic phase average of total area of Iran in the new time series has decreased by almost 14 degrees. This decrease in the value of the annual and 6-month phases indicates a quicker growth phase and phenological processes of plants compared to past times. Conclusion Results indicated that HANTS algorithm can effectively eliminateand reconstruct outliers in the NDVI time series. Zero harmonic (mean value) represents the overall level of vegetation cover and the firstharmonic phase in a one-year time series determines the starting time of growth in seasonal plants or thosewith agrowth period of6-month or less. Annual Phase indicates the angular starting position of the annual cycles and the 6-month phase inherently indicates the fluctuation and angular position of a half-year or 6-month curve. However, interpreting 6-month amplitude and phases are difficult. As most changes are controlled by the first harmonic phase, the first harmonic phase in a one-year time series contains important information about the beginning of growth and the phenological processes of plants. Therefore, harmonic components of a periodic time series canbeusedto identify and determine changes in vegetation coverage and phenological processes.
Hamid Panahi; Davood Amini; Ali Osanlu
Abstract
Extended Abstract
Introduction
To achieve sustainable security in Countries where security regards as a main concern, must implement land use planning programs in order of priority from the border to the interior. In land use studies, geography as a context plays a main role in the realization ...
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Extended Abstract
Introduction
To achieve sustainable security in Countries where security regards as a main concern, must implement land use planning programs in order of priority from the border to the interior. In land use studies, geography as a context plays a main role in the realization of codified plans and programs. All three vertices of the golden triangle of land management mean; Man, activity and space are influenced by the natural and human geographical features of the study area. Border zone planning is a type of planning that integrates border development with security and defense, based on the geographical characteristics of border areas, by establishing a link between development indicators and security plans, introduces strategies for sustainable development of border areas, that are bound to each other.
Security considerations are among those categories that have received less attention in macro-planning. In addition, awareness of the current situation is essential for any kind of careful planning for the development and progress of regions, especially in less developed provinces (Alipour et al., 2016: 159). The most important issues and problems in the formulation and implementation of planning in the country, include; Lack of attention to geographical-security considerations in locating the bases of law enforcement, border and military units, vital and sensitive centers and facilities, commercial, economic and communication uses. These issues have made political borders vulnerable to threats, military and terrorist attacks, border vulnerability to armed and opposition groups, border insecurity, dissatisfaction and conflict among border residents, poverty and underdevelopment, etc. in the country’s border areas.
Materials & Methods
The method of this research is descriptive-analytical and data analysis has been done with a quantitative and qualitative (mixed) analysis approach. To analyze the data, the method of contextual and basic theory (foundation data) has been used. In terms of method, this research is descriptive and survey based on field work, using open questionnaire, closed questionnaire and using SPSS and MAXQDA analytical software and Arc GIS. In MAXQDA software, it was proved that border management indicators are effective in security management, implementation and execution of security plans along the country’s political borders. After classifying the extracted indices, to examine the factor status of each of the indices under the relevant components through factor analysis in SPSS software, factors were classified into three categories. In order to analyze the status of application of selected indicators in the northwestern borders of the country, a questionnaire was designed and referred to the expert community was statistically analyzed.
Results & Discussion
Based on factor analysis; Thirteen border operational plans based on indicators Border planning was evaluated in the form of three factors that after reviewing the indicators: first factor; designing of ambush and anti-ambush operations in the border area is based on the shape of the land, the location of natural features in relation to the passages, the location of the escape routes and the connection points, the second factor; In the border monitoring and control planning, determining the location of telecommunication and communication systems in the region based on the situation of the repression points with enough view of the surrounding areas, the third factor; Determining the optimal routes for border patrols is based on the geographical realities prevailing in the border strip like land slope, distance to zero border, snowfall, flooding, etc., these three main plans were selected among the border operational plans influenced by border planning indicators in the northwestern borders of the country.
Conclusion
By analyzing the status of application of border management indicators in the implementation of plans in the border areas of the studied provinces, which was based on the Likert questionnaire and referring to the expert community, the status of the provinces was determined based on calculations and statistical analysis. Then, by summarizing the mean of the indicators based on which three provinces were examined, the status of the provinces was compared and ranked. Based on the results of statistical analysis, the first place is Ardabil province with an average of 3.92, the second place is East Azerbaijan province with an overall average of 3.64 and the third place is West Azerbaijan province with an overall average of 3.61.
Asyeh Namazi; Sayed Ahmad Hosseini; Sohrab Amirian
Abstract
Extended AbstractIntroductionAs a land use specially designed for physical activity, recreation and leisure, sports facilities are considered to be a public space vital for the society, improving health and well-being of the community. Therefore, special attention should be paid to the pattern of distribution, ...
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Extended AbstractIntroductionAs a land use specially designed for physical activity, recreation and leisure, sports facilities are considered to be a public space vital for the society, improving health and well-being of the community. Therefore, special attention should be paid to the pattern of distribution, easy access to these land uses, and spatial organization of these facilities in accordance with the pattern of road networks. Accordingly, the pattern in which sport facilities are distributed across urban areas can have a direct impact on the desired operational efficiency of the city. Therefore, optimal site selection and easy access to sports facilities are of great importance for a healthy city and a healthy community. A huge difference between per capita sports areas and the standard per capita or imbalanced distribution of sports facilities in the region may result in reduced interest in physical activities and threaten the health of individual and society. Accordingly, the present study has evaluated per capita sports spaces in Kashan, and the spatial distribution of these facilities. The average time required for accessing these spaces has also been measured in accordance with the local road network and the total area each facility serves. Finally, an optimal model has been proposed for sports related land use in Kashan. Materials & MethodsThe present descriptive-analytical study is applied in nature and uses ArcGIS and SuperDecisions software to analyze its descriptive and spatial data. To provide an optimal model, 11 indicators including area each land use serves, its quality, urban land use, population density, health centers, educational centers, distance from faults, distance from urban waterways, fuel centers, distance from industries, parks and green spaces were identified based on expert opinions. The importance of each indicator was also determined based on expert opinions using the ANP model, and weighted linear combination was used to combine the previously mentioned indicators in GIS. A brief summary of the models used are presented in the following section. Results and discussionThe nearest neighbor algorithm is used to evaluate the spatial distribution regardless of the total area of each sports facility. Results indicate the presence of a completely clustered distribution (P = 0.000 and Z = -3.368) at the level of 99%. Finally, the relative weight of each criteria is combined with the relative weight of each option obtained from ANP model using the weighted combination in GIS to reach an optimal model for site selection. The resulting value actually indicates the necessity of new sports facilities. In other words, higher values show higher priority and as it is shown, about 40% of the total area of Kashan is potentially appropriate for new sports facilities while about 60% of the city area is not suitable for such facilities. ConclusionOptimal site selection maximizes the efficiency of sports facilities and improves the quality of services for those using the areas. Therefore, the present study aims to evaluate the area each sports center is serving and provide an optimal model for site selection in Kashan. In 2016, Kashan had a population of about 304 thousand people and about 202 thousand meters of sports related land use. Thus, there was a 0.67 square meters per capita sports related land use in Kashan. Finally, 11 indicators were combined using the weighted combination to reach an optimal model. Results showed that about 40% of the total area of Kashan is potentially appropriate (relatively appropriate and completely appropriate) for new sports centers while about 60% of this urban area is not suitable for construction of such facilities. Moreover, results proves the efficiency of spatial statistics used to evaluate spatial distribution of land uses. As it is shown in the present study, GIS can provide an optimal model for site selection using practical indicators and appropriate data analysis methods. In general, results indicate that sports facilities in Kashan are not generally in a good condition in terms of per capita and distribution pattern which confirms the fact that these issues were not considered important in the process of site selection.
SHadman Darvishi; Karim Solaimani; Morteza Shabani
Abstract
Extended Abstract Introduction Urbanization is a continuous process and the spatial patternsof urban growth havealways played an important role in the transformation of human life throughout history. Urban growth has two dimensions: demographic and spatial, meaning that with increased urban population, ...
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Extended Abstract Introduction Urbanization is a continuous process and the spatial patternsof urban growth havealways played an important role in the transformation of human life throughout history. Urban growth has two dimensions: demographic and spatial, meaning that with increased urban population, the need for shelter increases and cities are faced with spatial growth. Expansion of cities in the spatial dimensions have several consequences,including changes in land use and land covers of areas surrounding cities.Land use change is currentlyone of the major concerns ofthe environmental approach, since land use changes in areas surrounding cities have led to changes in the economic structure of cities and the destruction of vegetation and agricultural lands as one of the main foundations of production in these areas. They have also seriously damaged other water resources, wildlife habitats, and resulted in the reduction of soil organic matter, changes in soil humidity and saltiness, increased energy consumption, increased urban heat islands, climate changes, as well as negative effects on the mental and physical health of urban residents. Nowadays, rapid growth in remote sensing technology and geographic information system, as well as the advancements in computer science and its application in environmental sciences and urban planning have created spatial modeling techniques such as Markov chain, Cellular Automata, intelligent neural networks and statistical models. Due to its dynamic nature, the capability of showing spatial distribution of land use changes, as well as its unique characteristics in modeling of natural and physical geographic featureson the ground and simpler adaptation with remote sensing data and GIS, a combination of Markov chain model and Cellular Automata are used as an important supporting toolfor decision making in urban planning and environmental sciences in many studies performedrecently. Over the past few decades, the population of Iranhas increased from 27 million in 1955 to 79 million in 2016. And according to the 2016census, 74 percent of the population lives in urban areas. In recent years, the population of Kurdistan province has experienced a 1.42% (2011 to 2016)average annual growth rate (especially in Baneh, Marivan and Saghez), which isaround 0.18% more than the average annual growth rate of the country (1.24%). Investigating census data shows that Baneh, Marivan and Saqezhave experienced a higher urban growth rate as compared to other cities in the province, and thus monitoring this growth and predicting its negative effects on the surrounding land use seems crucial.Destruction of vegetation and agricultural lands not only results in climate change, but also directly affect the lives of residents in the region. Therefore, understanding the growth rate is necessary for properplanning and managementofthese areas. Materials and Methodology Images received from Landsat in 1987, 2002 and 2017 were downloaded from the US Geological Surveywebsite and used in the present study. Google Earth images, land useand topography maps, and ground control points (GCP) were also used to perform imagepreprocessing, classification operations, and accuracy assessment. The study area includesBaneh, Marivan and Saqqez cities, which have recently experienced a high level of population growth. Considering the impact of population growth on increased rate of construction and physical development of urban areas, it is therefore necessary to study urban growth. In order to reduce the city’s impact on land use in future, it is necessary to modelurban growth. Using these models, planners can guide the urban development back to the optimal and appropriate routes and minimize the destruction of the land use.Image pre-processing in the present research was performed in ENVI5.3 environment. Then, using Maximum Likelihood algorithm, the images were categorized into five classes of water, residential areas, vegetation, agriculture and open spaces. Then, the overall accuracy of the classification maps was assessed using ground control points. To predict the urban growth, CA-Markov model was used in the IDRISI TerrSet software. Results and Discussion Findings indicate that the classified images have an accuracy of above 80%, and thus, land use maps of the study areas are valid.Investigations shows that the growth inMarivan and Baneh has most severely affected vegetation and agricultural land use. In the time period of 1987 to 2017, 897. 39 and 801 hectares of vegetation in Marivan and Banehhave been transformed into urban areas, respectively.During the same time period, 790.38 hectares of agricultural land in Marivan and 772.29 hectaresinBanehhave changed into urban areas. It is also important to note that unlike Saqez, the degradation of vegetation and agricultural lands in Marivan and Banehwas more severe than bare lands. In other words, bare landsinSaqez were more severely affected (as compared to vegetation and agricultural land), and about 1249,29 hectares of bare lands have turned into urban areas, while only 121.50 hectares of vegetation, and 509.04 hectaresof agriculture lands haveexperienced such a change.Also, results of the CA-Markov model showed that the growth of Baneh and Marivan cities in the 2017-2032 period will be in the Northeast and East directions, respectively. Results also indicate that this urban growth will affect agricultural and bare landsmore significantly. It is predicted that about 511.29 hectares of agricultural lands and 722.70 hectares of bare lands (in Baneh city) and 1080 hectares of agricultural lands and 2402.101 hectares of bare lands (in Marivan city) will turn into urban areas in this time period. Conclusion Based on the findings, it can be concluded that planning urban growth inthe study areas should be performed in a way that vegetation and especially the surrounding agricultural lands are preserved, and the negative effects of land use changesare minimized. Also,plannerscan apply the results of the present study in their future plansto guide the development of Baneh, Marivan and Saqeztoward optimal ways and reduce land use degradation.
Samira Afshari; Ali Lotfi; Saeid Pourmanafi
Abstract
Extended Abstract
Introduction
Industrial and economic developmentalong with population growth and increased exploitation of natural resources may upset the environmental balance. Inappropriate land use, along withpollution and destruction of natural resources are considered to be serious problems ...
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Extended Abstract
Introduction
Industrial and economic developmentalong with population growth and increased exploitation of natural resources may upset the environmental balance. Inappropriate land use, along withpollution and destruction of natural resources are considered to be serious problems caused by environmental imbalance in many parts of the world. These problems indicate the limited capacity of environment to resist human exploitation of land.
Industrial site selectionis considered to be one of the key factors in sustainable regional planning due to the different environmental impacts of industries. Because of the developmentin industrial areas and the existence of numerous mines in GolpayeganCounty, it is necessary to optimize industrialsite selection in accordance with environmental standards and regulations. Therefore, the present studyintegrates hierarchical analysis with multi-criteria evaluation methods to investigate 24 different criteria with the aim ofoptimizing industrial site selection in accordance withenvironmental standards and regulations in GolpayeganCounty.
Materials and methods
In accordance with the rules and regulations of setting up industrial and manufacturing units and similar studies,the conceptual model of Golpayegan county site selection was prepared based on three criteria: physical, biological and socio-economical. Followingthe preparation ofinformation layer for each criterion, spatial analysis ofEuclidean Distance was performed for each of them.
Then, information layers produced in the previous steps were standardized using Boolean and fuzzy logic. The integration and overlapping in Boolean method was performed using AND logic.
At this stage, all the information layers were entered into TerrSet software and standardized using fuzzy model and membership functions of the software’sfuzzy sets. The real scale (from 0 to 1) was used in this study to determine the membership function.Higher membership value in this range indicates higher utility while lower membership value indicates lower utility. In the present study, AND operator was used to integrate maps.
Hierarchical analysis was used to determine the weight of each factor. Afterwards, the maps were integrated using fuzzy overlay method, weighted sum model and weighted linear combination (WLC) method. In this way, a map was produced for the industrial park site selection. Then according to the histogram curve and its breakpoints and also according to the environmental conditions of the region, it was classified into 5 classes.
Results and Discussion
An inconsistency rate of 0.04 was calculated in the present study to evaluate the accuracy of judgments made about the weight of the criteria and sub-criteria.Distance from Mouteh Wildlife Refuge, distance from faults, distance from wells and distance from roadswere identified as the most important criteria for assessing the industrial capacity of the region.
Maps produced using the Boolean method include two classes of 0 and 1,the valuesin the fuzzy overlay, weighted sum and weighted linear combination methods rangebetween 0 and 1, while they range between 0 and 0.7 in the weighted sum method and between 0 and 0.8 in the weighted Linear combinations method.
2783.5 hectares of the study area have the potential of serving as industrial sites based on the Boolean method, indicating that 1.7% of the study area is suitable for industrial construction. Combining moderate, good and highlysuitable classes using fuzzy overlay method showed that 1769.13 hectares or 1.1% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes usingweighted sum method showed that 1758.77 hectares or 1.09% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes using weighted linear combination method showed that 1902.78 hectares or 1.18% of Golpayeganregionaresuitable for industrial site construction. No matter which method is used, suitable areas for industrial site constructionare located in the southeastern region of the County and in vicinity of the main road.
Conclusion
Comparing the results of the present study with similar studies indicates that the Boolean logic finds the least number of suitable areas for industrial park construction and its selected areas must have an appropriate score in all evaluation criteria.
Findings indicated that due to the specific characteristicsof the Analytical Hierarchy Process, this method can be useful in the investigation of regional planning issues.
It can be concluded that Weighted Sumand WLC are more effective than Boolean and fuzzy overlay methods.
Results indicate that all four models located landssuitable for industrial development in the southeastern areas of the County and in vicinity ofits main road, thus these areas should be prioritizedin future planning, policy making and investment for industrial development. Furthermore, given the concentration of agricultural activities in GolpayeganCounty and its numerous tourism capacities, the development of agricultural conversion industries and ecotourism related industries within the predicted authorized areas can be considered as priorities of regional development.
Nowadays, sustainable economic development in most countries depends on industrial development. Sustainable development of industries creates more opportunities for social and economic growth. Sinceappropriate site selection for industrial parksharmonize the goals of economic development with the goals of urban development, economic enterprises and environmental objectives, it is considered to be a step toward sustainable development. Achieving such a goal requires a revision of the site selection criteria in accordance with the sustainable development indicators. This increases national and local employment rate and accelerates industrial growth without damaging the environment.
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Afrouz Bagheri; Bahram Malekmohammadi; Banafsheh Zahraei; Amirhesam Hasani; Farzam Babaei
Abstract
1. Introduction Nowadays, changes in environmentaldynamics including changes in land cover, land use, water supplies and climate are considered to be challenging issues of human communities. Thus, it is especially important to investigate different aspects of land use change and their effects on the ...
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1. Introduction Nowadays, changes in environmentaldynamics including changes in land cover, land use, water supplies and climate are considered to be challenging issues of human communities. Thus, it is especially important to investigate different aspects of land use change and their effects on the past and future trends ofdifferent plains. Identification of previous changes and prediction of future trends help planners and managers to compensate for losses and avoid similar mistakes in future.Therefore, the present study is divided into two parts. In the first part, land usechanges of Lenjanat Plain in the 1990-2015 period are analyzed. In the second part, future land use changes (2015-2035) of the area are investigated.Adjustment coefficient is calculated to show the effect of land use changes on runoff coefficient. Materials and methods 2.1 Study area and its characteristics Lenjanat Plain is a sub-basin of Gavkhuni Wetland located in the central part of the Iranian plateau with the longitude of 51˚ 8' to 51˚45' E and latitude of 32˚2' to 32˚24' N. 2.2 Land use change In the first step, preprocessing of satellite data and preparation of the information were carried out through geometric and atmospheric correction of the digital imageswith the purpose of correcting errors, removing defects in the images and omitting system errors. Landsat-4 and 5, TM sensor, Landsat-7, ETM+ sensor and Landsat-8 OLI sensor were used to evaluate and predict land use changes in the study area. Image selection was performed based on the availability criteria, and Landsat satellite images were thus obtainedfor 1990, 2005, and 2015. In the next step, unsupervised classification was used to create a general understanding of land use classes in the study area as a useful tool for determining training samples. ENVI software was used to identify suitable training samples for classification. To realize the second goal of the study, Marco integration model and a cellular automaton model were used and future land use changes in Lenjanstudy area were predicted for 2035 based on the base map and the assumption that the current trend in land use changes will continue. For this purpose, the Marco and CA-MARKOV modules were utilizedin IDRISI SELVA. CA-Markov model was used to predict land use changes with spatial contiguity and spatial transitions over time. 3. Results and discussion 3.1 Measuringland usechanges Finall and use maps represent the percentage and spatial distribution of each landuse type in the study area in the past, and at present. These maps area also used to evaluate the effects of management on the intensity of land use changes in the study area. Man-made surfaces have almost doubled in the region and reached from 3922 to 7202 hectares. In the past, 3922, 22516, 81613 and 367 hectaresof man-made areas (such as residential and industrial), agricultural lands, barren lands, and riverbeds were located in the study area which have reached 7202, 17943, 82793 and 229 hectares, respectively. 3.2 Prediction of future land usechanges Land use types in 2035 were predicted using CA-Markov chain model. Results indicate that manmade surfaces will exhibit a rising trend and increase from 7,202 to 9,122 hectaresduring 2015-2035 period.To determine the compatibility or incompatibility of actual maps and modelingresults, model validation was performed. In this regard, land usesof the study area was predicted for 2015 through the aforementionedmodel and the predicted map was compared with the actual land use map in 2015. In this method, the Kappa index of 0-1 was used to interpret the results. 3.3 Adjustment Factor Before anything else, the present study have determinedland usechangespercentage. Then, runoff coefficient of the forecast period was divided by runoff coefficient of land use changes in the pastto calculate the adjustment factor.Based on the findings of this study and the land use changesforecasted forLenjanat plain in 2035, the adjustment coefficient for the region equals 1.051. 4. Conclusions The present study aimed to evaluate various criteria affecting the quantity of water resources. Moreover, it has evaluated and determinedadjustment factor. For this purpose, Lenjan plain was used as a representative of the plainsin the country. Five land use types, including man-made areas (such as residential and industrial), agricultural lands, Barren lands, riverbeds and rock beds were identified for 1990, 2005 and 2015. CA-Markov was applied to predict land use changes for 2035. Adjustment coefficient is also calculated to show the effect of land use changes on runoff coefficient
Hossein Asakereh; Skineh Khani Temeliyeh
Abstract
Extended Abstract
Introduction
As an influential element of climate, precipitation affects human activities and societies. It is thus considered to be the essence of any study conducted as a part of environmental and economic planning. Precipitation in Iran, especially in its west and southwest is ...
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Extended Abstract
Introduction
As an influential element of climate, precipitation affects human activities and societies. It is thus considered to be the essence of any study conducted as a part of environmental and economic planning. Precipitation in Iran, especially in its west and southwest is affected by thermal, dynamic, and thermodynamic low-pressure centers such as the Red Sea trough. The trough is an extension of Sudanese low-pressure with a central pressure of about 1006 hPa. The Red Sea is stretched in a southeast to northwest direction and thus connects tropical and subtropical regions. Considering the importance of the Red Sea low-pressure system for precipitation events in west and southwest Iran, any change in this system will affect precipitation patterns in the region. Analyzing the activity of this system and resulting precipitation in west and southwest Iran will thus provide more accurate understanding of the climate of this region.
Materials and methods
Environmental and precipitation data retrieved from Asfezari national database and atmospheric data (geopotential height) extracted from the European Center for Medium-Range Weather Forecasts (ECMWF) were utilized in the present study. A numerical algorithm was also used to identify the cyclones. The algorithm identified 459 cyclones in the statistical period.
Results and discussion
Time distribution of days in which the Red Sea trough is active showed increased activity in summer (198 days) especially August (99 days) and spring (178 days) especially April. However, the Red Sea trough showed decreased activity in autumn and winter. Activities of the Red Sea trough have shown a slightly decreasing but significant annual trend during the statistical period. A sharply and significantly decreasing slope can be observed in summer which results in a decreasing annual trend. Average daily precipitation of the study area in the statistical period ranged from 0 to 2.5 mm. The minimum average precipitation (less than 1 mm) was observed in 29.58% of the study area while maximum average precipitation (more than 2 mm) was observed in 3.64% of the study area. The largest part of the study area (66.87%) experienced an average daily precipitation of 1 to 2 mm. Moreover, 24.28% of the region with minimum precipitation (less than 1 mm) was located in the south and southwest of the study area. This indicates a relatively less severe impact of the Red Sea trough in this area. Around 70.88% of the study area has experienced a precipitation between 1 and 2 mm. Subtracting average daily precipitation recorded throughout the statistical period from the average daily precipitation occurring simultaneously with the activities of the Red Sea trough showed a positive anomaly (more than 0.4 mm) in the north and northeast of the study area. Therefore, it can be inferred that most of the precipitation in this area is originated over the Red Sea. It seems that the presence of the Zagros Mountains has also had a significant effect on precipitation in the study area. Areas with a negative anomaly (less than -0.4 mm) in which precipitation is not affected by the Red Sea trough include spatially scattered regions in Khuzestan, and Kohkiluyeh and Boyer-Ahmad provinces (0.74% of the study area). In other words, precipitation associated with the activity of the Red Sea trough was less than the total precipitation, and thus, most of the precipitation in these regions has other sources.
Conclusion
Results indicated that during the statistical period, minimum average daily precipitation has occurred in south, southwest, and northeast of the study area. Moreover, south and southwest of the study area experienced precipitation simultaneously with the activity of the Red Sea trough. The maximum precipitation in either cases (during the statistical period and also during the activity of the Red Sea trough) has been concentrated in parts of the northwest, west, and east of the study area (along the Zagros mountain range). Significant latitude difference between the north and south of the study area, and existence of the Zagros Mountains and consequently the heterogeneous topography have created two different zones in the study area experiencing minimum and maximum precipitation. In the presence of the Red Sea trough, a higher percentage of the study area experienced maximum precipitation. The frequency of days with more than one millimeter precipitation and their spatial distribution showed that under general conditions, the maximum precipitation has occurred in the north, northwest, west, and east covering 61.11% of the study area. Kurdistan province has recorded a maximum precipitation in more than 3500 days under the influence of different air masses. More than 73% of the factors associated with precipitation in Iran, especially in its northwest, west, and southwest are various synoptic systems (cyclones and short waves) entering the country from the Mediterranean with westerly winds. The minimum number of rainy days during the whole statistical period and also during the low-pressure activity of the Red Sea were also recorded in the southern and southwestern parts of the study area.
Geographic Data
Shahin Jafari; Saeid Hamzeh; Hadi Abdolazimi; Sara Attarchi
Abstract
Extended AbstractIntroductionHuman activities as well as environmental and climate changes affect the trends of wetlands. Detecting and monitoring aquifers are considered to be very important for evaluation of past, present, and future influential factors, and the findings of such studies are essential ...
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Extended AbstractIntroductionHuman activities as well as environmental and climate changes affect the trends of wetlands. Detecting and monitoring aquifers are considered to be very important for evaluation of past, present, and future influential factors, and the findings of such studies are essential for taking measures and making decisions based on the goals of sustainable water and soil resources management. Over the past decade, many researchers around the world have been attracted to remote sensing and especially satellite remote sensing and used this technology to detect such changes over time. The present study has used Landsat (monitoring the area of water body), TRMM (monitoring rainfall), MODIS (monitoring vegetation and evapotranspiration), Grace (monitoring groundwater) satellite images available in Google Earth Engine to study last two decades changes (from 2000 to 2019) in Maharloo wetland, Goshnegan catchment and their surroundings. Materials & MethodsMaharloo wetland is located in Fars province and Goshnegan catchment (426 square kilometers). The present study has used Landsat 7 and 8 images to extract the area of water body, TRMM images to obtain precipitation values, MODIS products to calculate NDVI and evapotranspiration, and data received from Grace to extract changes in groundwater level. These satellite images were available in Google Earth Engine. Mann-Kendall test was also used to assess the overall trend of the aforementioned factors. Results & DiscussionThe automated water extraction index was used in the present study to identify and estimate the area covered by water bodies in the study area. The largest area belonged to 2006 (216.76 square kilometers) and the smallest belonged to 2018 (66 square kilometers). In 2000 (the beginning of the reference period), an area of 216.52 square kilometers was covered by this wetland which is close to what was observed in 2006. In 2018, this has reduced to 66 square kilometers. Thus, there is about 150.72 square kilometers (69.54 percent) difference between these two years. In 2009, the total area has reduced to 66.67 square kilometers. A numerical comparison between 2000 and 2019 also indicates a reduction of 91.17 square kilometers (42% decrease) in the total area covered by this wetland. Also, a 53.72 square kilometers (29.60%) difference was observed between the average area covered by the water body in the first and second ten years. Since calculated p-value value (< 0.00001) is less than the alpha level (0.05), so a significant trend was observed in the average annual data of the area covered by this wetland. Kendall's tau also indicated declining trend of the collected data. Groundwater level was calculated using data received from Grace Satellite to investigate the role of groundwater level in reducing the area covered by the water body. Results indicated that since 2008, groundwater level have always showed a negative value (a decreasing trend). For an instance, a groundwater level of -10.86 cm in 2019 indicates a decrease in the water level in the study area. As the calculated p-value (< 0.0001) is less than the alpha level (0.05), so a significant decreasing trend was observed in the groundwater level. Results of Mann-Kendall test (-0.6) also indicated that changes in water bodies, vegetation, rainfall and groundwater level had a decreasing, increasing, increasing and decreasing trend, respectively. No significant trend was observed in evapotranspiration. It seems that the expansion of agricultural lands and subsequent water extraction from aquifers have intensified the decreasing trend of water bodies in this wetland. ConclusionWetlands provide many ecological services including water treatment, natural hazard prevention, soil and water protection, and coastline management (Amani et al., 2019). Therefore, understanding the importance of wetlands and their management need to be seriously considered by relevant organizations in different countries of the world, and Iran is no exception. Satellite data and remote sensing methods and techniques are considered to be one of the most important and cost-effective methods of monitoring wetlands. The present study used satellite data collected by Landsat, MODIS, Grace, and TRMM to monitor water bodies, vegetation, groundwater level, and rainfall in Goshnegan catchment in which Maharloo wetland is located. The results of Mann-Kendall test showed a decreasing annual trend for changes in the average area of this wetland. This decreasing trend is considered to be a serious threat to human settlements around the wetland which can intensify over time. It will also affect the thermal islands of Shiraz and Sarvestan in near future. Obviously, management of agricultural and forest land uses with the aim of stopping their increasing trend can improve water balance in catchment areas. A 132.2 ha (approximately 36.16%) difference was observed between the average vegetation cover in this catchment area over the first and second ten years (233.4 vs. 365.6 ha). It seems that the expansion of agricultural lands and subsequent water extraction from aquifers have intensified the decreasing trend of water bodies in this wetland. Due to the proximity of this wetland to the city of Shiraz and its importance as an ecological and tourist attraction, it is suggested that related authorities (Department of Environment and Water Organization) demarcate lake bed and riparian zone with the help of remote sensing researchers to improve the management of this wetland and prevent it from drying up. Also, it is suggested that the Organization of Agriculture Jihad review and improve water consumption methods and cultivation patterns in the areas surrounding this wetland.
Abbas Tajaddini; Zahra Sabzi; Ladan Zarif
Abstract
Extended Abstract Introduction Determining the landfill site for municipal waste is an important issue in the urban planning process due to its great impact on the economy, ecology and environment of each region. In the process of site locating, it is tried to consider areas with the least risks to the ...
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Extended Abstract Introduction Determining the landfill site for municipal waste is an important issue in the urban planning process due to its great impact on the economy, ecology and environment of each region. In the process of site locating, it is tried to consider areas with the least risks to the environment and human health and conservation. During the recent three decades, the production of municipal solid wastes has increased considerably, beside that their specifications has been changed meaningfully due to the change in people’s life style, progress of industrialization and world economies. Still, one of the best methods of waste disposal is waste dumping or burying. Optimized selection of landfill sites may minimize any negative environmental or financial effect. Searching various places to locate landfills requires choosing an appropriate method. Therefore, applying mathematical methods and determining the influence of different criteria the selection of a suitable place can be very useful. This subject was examined here for the city of Karaj, which is one of the Iran’s megacities with a fast and uncontrolled population growth and increase in waste production. Materials & MethodsIn this research, the indicators and effective criteria in locating the landfill of Karaj city were identified, evaluated and prioritized with a sustainable development approach using GIS and Fuzzy Analytical Hierarchy Process (AHP). The research data were collected through literature review, internet searching, and technical survey. Using fuzzy logic and decision making techniques based on expert opinions, it was tried to limit the gap in the research field. The current research is descriptive-survey, and functional. To carry out the research, at first, the major influencing criteria were identified. The criteria were categorized into five major groups of geotechnical, environmental, municipal developing, socio economic, and hydrological items. Afterwards, an initial survey was utilized to control the items, and then, a pairwise comparison questionnaire was designed to collect the expert opinions. The research population was 30 experts, adopted from academia, industry, and environmental engineering sector, that 27 of them were selected randomly to answer the questions. It was adequate according to the Cochran’s formula. To ensure the data collected were acceptable, the validity and reliability of the questions were examined sufficiently. Due to its simplicity and accuracy, the triangular fuzzy number was adopted to assess the descriptive variables. In continue, and based on the GIS analysis method, extra specifications of the potential landfill sites proposed were further examined. It was accomplished through categorizing the information layers, then by weighting the potential landfill sites according to the total scores obtained. The information layers included: geotechnical effect, ground slope, land use, permeability, being subjected to flood, water quality, water level, distance from the city, and distance from power transmission lines. Based on the influence level of these layers upon the landfill sites, they were categorized into four classes of highly suitable, suitable, relatively suitable, and unsuitable. For overall ranking, the score of each landfill site in each information layer was calculated by multiplying each layer score by its weight. After completion of this computation phase, all available information layers obtained their own scores, demonstrating their suitability level to be a landfill site. Using the ArcView software, the simple additive weighting method was utilised for site locating. Results & DiscussionThe results showed that the urban development criteria with a weight of 0.270 was the most important criterion in locating municipal waste landfill, followed by the environmental criterion with a weight of 0.226. Accordingly, the socio-economic criterion with a weight of 0.152 was placed in the last rank. Moreover, in the geological group, the fault index weighted 0.261 and the climatic conditions index weighted 0.236. In the environmental group, the surface water distance index weighted 0.201, and the landfill odor index weighted 0.172. In addition, in the urban development group, the land use index with a weight of 0.283 and the access to equipment and facilities with a weight of 0.258 were the most influencing items. The Inconsistency Ratio of pairwise comparison matrix (I.R) for all matrices was less than 0.1, which confirmed the compatibility of the components. Conclusion In the complementary analysis, using the Fuzzy TOPSIS technique and the Geographic Information System (GIS) and utilizing the simple incremental weighting method (SAW), it was determined that Nazarabad site and Halqe Dare new-site are the most suitable options for constructing a new landfill site.
Seyed Mehdi Yavari; Zahra Azizi
Abstract
Extended AbstractIntroductionLack of uniform light radiation on the objects, reduces the amount of contrast in the images and makes it difficult to extract image features. This problem destroys information about the behavior, shape, size, pattern, texture, and tone of the effects, and compresses the ...
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Extended AbstractIntroductionLack of uniform light radiation on the objects, reduces the amount of contrast in the images and makes it difficult to extract image features. This problem destroys information about the behavior, shape, size, pattern, texture, and tone of the effects, and compresses the image histogram in one or more specific areas. UAV images have been widely used in recent years due to their extensive coverage, high operating speed, use in hard-to-reach areas and up-to-date equipment. If drone images are correctly taken and pre-processed, they provide good accuracy for a variety of applications. The preprocessing is important since the image acquisition conditions cannot be changed in most cases so that the acquired images are contaminated with some distortions or errors which must be removed or their effect reduced to a minimum before any process. Improving the exposure in the image, which increases the amplitude of the histogram, can highlight features with similar gray-scale values, and this is useful in identification. Materials & MethodsIn this study, two aerial images have been used with a variety of vegetation, soil and man-made features using Storm 2 hexacopter drone in Simorgh city (Kiakla) in Mazandaran province with longitude and latitude 52⸰ 54' 1'' and 36⸰ 35' 49''. At first the SMQT algorithm is applied to the input images. So the bits number of the input image is calculated to determine the number of transmission levels. Then with rgb2gray command creates a gray image of the original image. The overall average of the image is calculated and the DN of each pixel is compared to the average. If the DN is greater than the pixel value, the number 1 is assigned to the pixel, otherwise the number zero in another image is assigned to the pixel. The average calculation and segmentation of pixels based on the number of bits continues, each segmentation is called a transfer. Then, by converting the data from these divisions into values in the spectral range of the image, a new image is created. This image has higher radiometric resolution than the original input image but lower spectral resolution. For this reason, the image is fused. Global gamma correction is applied to the fused image. Finding gamma in the image, especially local gamma is time consuming and complex for programming and computing. Therefore, to increase the computing speed, a local gamma of 0.7 was applied to the whole image and then the first step processes are applied again and finally, the SSIM index is checked for image enhancement.Results & DiscussionThe SSIM value for input image 1 and 2 is 0.8372 and 0.8401 while this value before processing was 0.4352 and 0.4161. Examining the histogram of the images before and after processing, in all three bands R, G and B, shows the stretch of the image histogram in the range of 0 to 255. There is a decrease in the number of peaks and valleys in the histogram of the processed images. The density function for input and processed images shows that the more homogeneous the number of effects in the image, the greater the slope of the function graph. The value of the density function has increased after processing, which is due to the stretching of the image histogram. SSIM is used to validate the results in this study. The images have been visually improved significantly, but this is not enough for verification. The goal of quantitative quality recognition is to design computational methods that can accurately and automatically express image quality, which affects all the image pixels in the same way. The SSIM range is between (+1 and 0). The closer the measured value for an image to one, the better image quality will be. SMQT also has less computational complexity and less configuration. If the image of a light object is formed in a completely dark background (such as night shooting), this algorithm does not work in the background pixels. Examining the image samples taken from a complication at night, it was found that the black pixels changed color to purple after fusion. In order to optimize the algorithm, it is suggested to increase the efficiency of the algorithm by examining the spectral behavior of different features in different color spaces and integrating their effective components in image or feature highlighting or the use of plant or soil indicators. The fuzzy method can also be used for semi-shady areas. These improvements should also prevent complexity of computing by increasing efficiency.
Asghar Hosseini; Zahra Azizi; Saeed Sadeghian
Abstract
Introduction LiDAR (Light Detection and Ranging) employs pulse models which penetrates vegetation cover easilyand provides the possibility of retrieving data related to Digital Terrain Model (DTM).Pulses sent by the Lidar sensorhitdifferent geographical features on the surfaceground and scatter inall ...
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Introduction LiDAR (Light Detection and Ranging) employs pulse models which penetrates vegetation cover easilyand provides the possibility of retrieving data related to Digital Terrain Model (DTM).Pulses sent by the Lidar sensorhitdifferent geographical features on the surfaceground and scatter inall directions. Distance to the object is determined by recording the time between transmitted and backscattered pulses and by using the speed of light to calculate the distance traveled by the small portion of pulses backscattered. Most LiDAR receivers at least record the first and last backscattered pulses. The first backscattered pulses are used to produce Digital Surface Models (DSMs) and the last ones are used to produce DTMs. Despite the fact that these data can provide a valuable source for DTM generation, the volume of vegetation (vegetation density) in forest areas reducesthe accuracyof DTMs. Onthe other hand, ground surveying of forest areas is rather expensive and time consuming, especially in largerforests. Aerial images are also used as a source for DTM generation, but this approach requires a 60–80% overlap between images which along with canopy height reduce the potential of this method for DTM generation. Also, low spatial resolution of satellite images collected from forest areas increases errors in DTM generation to a large degree. The present study investigates the accuracy and precision of DTMsproduced from LiDAR data in a forest area. Furthermore, the effect of different methods of filtering and DTM interpolation was explored. Different methods of DTM generation were also closely analyzed and evaluated. Materials & Methods The case study area is located in Doroodforests, a part of Zagros forests, in the southeastern regions of Lorestan province in Iran (48°51’19’’E to 48°54’31’’E and 33°19’21’’N to 33°21’15’’N). Minimum and maximum altitude above sea level were 1143 and 2413m, respectively. The study area covers 100 hectares of mountains with an average slope of 38%. Approximately 50% of the area is covered by forests in which Brant’s oak (Quercusbrantii Lindley) is the most frequent species. LiDAR data were collected by the National Cartographic Center of Iran (NCC) in 2012 using a Laser scanner system (Litermapper 5600) fixed on an aircraft flying at an average altitude of 1000m. LiDAR data consisted of the first and last returns (backscattered pulses), distance and their intensity value. Collected data had an irregular structure and included an average of more than four points per square meter. A DTM was produced using a two-step filtering. First, a morphological filter removed most of non-ground points, and then a slope-based filter detected remaining points. Inforest areas with rough-surface, DTM was producedthrough processing ofLiDAR data with statistical methods likekriging and inverse distance weighting (IDW). These methods apply third and fourth power to detect and remove non-ground points. To assess the accuracy of DTMs produced by different approached, 5 percent of the LiDAR point cloudswererandomly separated as the test data. Amongst these data sets, 62 points with a suitable dispersion were selected and measured using a GPS-RTK. An error matrix, along with accuracy indices (including correlation and Root Mean Square Error (RMSE)) were calculated based on these data. Results & Discussion Results indicated that 44-degree slope is the best threshold for isolation of non-ground points and inverse distance weighting (IDW) is the best third power interpolation method with the highest correlation (0.9986) and the lowest RMSE (0.204 meter). Amongst the filtering methods, slope-based filter used for separation of ground and non-ground points had the best performance. Since this filter combines two parameters of slope and radius, it can remove cloud points related to the vegetation cover and results in high efficiency for steep forest areas. Slope-based filter is suitable for processing of near-surface vegetation, whilst statistical filter is well-suited for vegetation cover consisting of tall trees. Conclusion The present study proposed and investigated different scenarios for the production offorest areas’ DTM using LiDAR data and two interpolation methods. These algorithms were practicallyassessed using LiDAR data collected from Dorood forest areas. The best scenario was slope-based filter with inverse distance weighting (IDW) interpolation. Based on accurate assessment, this approach can produce reliable DTM in forest areas.
Farzaneh Sasanpour; Fateme Mohebbi; َAmir hosein Kazem
Abstract
Extended Abstract
Introduction
Floods are natural hazards that cause a lot of financial and human losses every year. Flood zoning plans contain basic and important information in the study of development projects in the world, sobefore any investment or implementation of development plans, they should ...
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Extended Abstract
Introduction
Floods are natural hazards that cause a lot of financial and human losses every year. Flood zoning plans contain basic and important information in the study of development projects in the world, sobefore any investment or implementation of development plans, they should be reviewed by the relevant organizations. The Taleghan River has faced numerous floods over the years,however, no comprehensive studies have been conducted regarding the damage caused by the flood of Taleghan River and its zoning. Taleghan town, which is the main population settlement in the region, the river passes through and the construction of residential and commercial buildings along the river, is expanding. By Using the ARC GIS software,Taleghan most affected areas by flood risk have been determined in the form of a zoning map. Flood risk zoning map has been preparedby using FuzzyVIKOR method, determining the weight through the critic for 7 effective criteria in evaluating flood zones including: altitude, slope, slope directions, land use, geology, distance from waterway and average rainfall. The results of this study, which has been prepared in five categories, show that 83% of the total area of the basin includes safe or low-risk areas. However, 17% of its lands have moderate and high flood risk, which includes areas around the main waterway and sub-waterways with residential and agricultural uses in the basin. Therefore, in order to reduce floods,in low and medium slope lowlands of Taleghan River, in development of rural urban uses in the region, it should be implemented.
Materials and Methods
The present research is descriptive-analytical in terms of method and applied research in terms of purpose. Many factors must be considered in flood zoning, with different degree of importance. In this study, based on previous experiences, the factors that had the greatest impact on flood occurrence in the Taleghan watershed were selected in the VIKOR Fuuzy model. The data used in this study include sea level elevation, slope, slope directions, average rainfall, distance from waterway lines, land use and formation, which were used to determine areas vulnerable to floods.Some part of the required data including Digital Elevation Model (DEM), land use map of the region and map of geological formations have been collected in raw form with a shape file format in the scale of 1: 250,000 from the rangeland and watershed management department of the Faculty of Agriculture and Natural Resources, University of Tehran. Elevation, slope and geographical aspect, maps were extracted from DEM 10 m. The layer of waterways, including permanent canals and rivers, was provided by the National Forests, Rangelands and Watershed Management Organization. The map contains same rain line that is received from the Meteorological Organization. The raster map of the average precipitation of the basin that was prepared based on the information of the precipitation rain lines and the statistics of rainfall data related to 5 stations of Dizan, Ciancranchal, Gotehdeh, Jostan, Glird, Armut and Zidasht, using the Interpolation technique. The criteria were normalized after preparing the maps (GIS READY) and applying the required edits such as defining the unit coordinate system for the maps, eliminating the errors that occurred during digitization and reducing the descriptive data by adding a new column to the related descriptive information table.
In all of the maps thatwere converted from Vector format to Raster, after the normalization step, the layers were weighed through the Critic method. Using the VIKOR model and the weights obtained by the Critic method, which were calculated in Excel software, the value of the VIKOR index (Q) was obtained for every option (pixel). Finally, the ultimate map of flood risk zoning in Taleghan watershed resulted from assigning the values of VIKOR index (Q) obtained from the previous step for every relevant point (option), by ARC GIS software.
Results and discussion
The results of flood zoning map show that 83% of the total area of the basin includes safe or low risk areas. However, 17% of this area has a moderate and high flood risk, which mostly includes urban, rural settlements, orchards and agricultural lands, which shows the importance of paying attention to proper management in these areas. According to the results, it can be said thatthe distance from the waterway in Taleghan watershed has had a significant effect on the amount of flooding, so by moving away from the main waterway and sub-waterways of the basin, the risk of floods and flooding can be reduced. The results of the terming flood risk zoning, show that 27 villages and settlements out of 68 villages in the region are in high-risk areas, including the villages of Eskan, Gotehdeh, Narian, Prachan, Mehran, Joostan, Nisa Olga, Hasanjoon, Jazan, and Mochan are at the highest risk.
Conclusion
It has been proved that Multi-criteria decision analysis methods in GIS is a robust approach to generating risk maps with acceptable accuracy. The judgment about the acceptabilityof the model can be made byusing external information from real ground data. In this study, relatively high compliance with the final zoning map was obtained by checking the history of floods in the study area.
Ali Akbar Anabestani; Hedayatollah Noori Zamanabadi; Masoumeh Mollanorozi
Abstract
Extended Abstract
Introduction
Evaluating the ecological capability is so important that if the selected land lacks the appropriate ecological potential for the implementation of a specific land use, implementing the plan (even if there is a socio-economic need for that specific land use) not only ...
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Extended Abstract
Introduction
Evaluating the ecological capability is so important that if the selected land lacks the appropriate ecological potential for the implementation of a specific land use, implementing the plan (even if there is a socio-economic need for that specific land use) not only does not improve the environmental status of the region, but also causes more environmental damages. As an economic activity that somehowsells the natural and cultural heritage of different regions, and depends on the natural environment and its exploitation, tourism is one of the most important environmental potentials. Therefore, tourism is considered to be a path to sustainable development, which through its multidimensional nature not only meets the needs of tourists, but also creates major changes in the systemof the host society. Consequently, in order to achieve sustainability, tourismshould be planned in a way that it does not negatively affect the environment, economy and culture of the host societyand meets the needs of the current generation without overusing what also belongs to the next generations.
Materials & Methods
The present studywas applied in nature and took advantage of a descriptive-analytical method to study the parameters in two main sub-sections.The first part included a library research performed with the aim of investigating related theoretical literature and the research background.The second part included some interviews and a field research performed for data collection. To evaluate the regional environmental capability and overlayingmaps in ArcGIS environment, Weighted Linear Combination (WLC) methodand Fuzzy operatorswere used. First, the final map of ecological capability for the development of sustainable rural tourism was analyzed and evaluated using WLC method based on highly appropriate, appropriate, limited appropriateness, inappropriate, and highly inappropriate classes. Then, fuzzy maps were produced with a gamma value of 0.7, 0.8 and 0.9 to obtain the tourism capacity of the region. And finally, the Kappa coefficient was used to compare the accuracy of classifications obtained from the WLC and fuzzy methods.
Results & Discussion
Findings indicate that with a weight of 0.33,tourism resources are the most important factor or capability in the development of sustainable rural tourism in Neyshabur County. The topography, with a weight of 0.192 is considered to be the second most important factor according to the experts and specialists. The third most important factor is the land cover with a weight of 0.138 and then, climate criteria with a weight of 0.117, hazards with a weight of 0.088, socioeconomic factors with a weight of 0.084 and water resources with a weight of 0.051 had the highest scores. Finally, the scores were applied to the GIS environmentusing the WLC method, and the final map of land capability for sustainable rural tourism in Neyshabur County was obtained.
Also, the statistical information obtained from the final map of land capability shows that 27.27% of the area is located in the very appropriate class, and31.76%is located in the appropriate class, while 22.23% and 4.28% of the region belongs to the highly inappropriate and inappropriate classes respectively.In the next step, tourism capacity maps of the region were prepared using a Fuzzy model with 0.7, 0.8 and 0.9 operators. The study area was divided into five categories: very high, high, medium, low and very low in terms of tourism capability.
The last and the most important step was to find the most accuratemap from those produced using AHP and fuzzy methods with different gamma values of 0.7, 0.8 and 0.9. To reach this aim, field observations and interviews with experts and specialists ofthe field were performed. Therefore, results obtained from the maps were compared with the experts’ opinions. Findings indicates that the operator with a gamma value of0.7 and a kappa coefficient of 0.84 is considered to bemore reliable than the operators with a gamma value of0.8, and 0.9 and AHP model. Thus, the 0.7 gamma operator is considered to bethe most suitable model for environmental capabilityassessmentin the region regarding tourism.
Conclusion
Using natural capabilities and potentials is the most cost-effective and lucrative way to achieve sustainable development. Findings of the present studyindicated that the operator with a gamma value of 0.7 and a Kappa coefficient of 0.84 is considered to be the most suitable model for the assessmentof the region’senvironmental capability for the development of sustainable rural tourism and it is more reliable and appropriate than the AHP model and operators with a gamma value of 0.9 and 0.8.Finally, considering the capabilities and potentials of the Neyshabur County for the development of sustainable rural tourism, it is recommended to consider development of tourism in this county as the priority of rural development plans and to use the natural resources of the area especially in the appropriate and highly appropriate classesas a way to achieve sustainable tourism development of the county in the most cost-effective way. It is also suggested that with appropriate management, planning and using the ideas of academic researchers to improve the capabilities of theaverage class, we can make the most out of the potentials of this area to develop sustainable regional tourism.
Amer Nikpour; Hamid Amoniya; Sahele Shokri
Abstract
Extended Abstract
Introduction
Sprawl is the process of rapid population growth and spreading of urban developments on undeveloped land near a city with a direct impact on the spatial development which in recent years has become one of the major challenges of cities around the world. Growing population ...
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Extended Abstract
Introduction
Sprawl is the process of rapid population growth and spreading of urban developments on undeveloped land near a city with a direct impact on the spatial development which in recent years has become one of the major challenges of cities around the world. Growing population trend and substantial changes in land use have made scientific and accurate planning a vital requirement for the management of this phenomenon. Accurate planning can help managers and spatial planners achieve sustainable urban and rural development. The present study seeks to enhance understanding about spatio-temporal processes of urban growth and development in Babolsar, identify general factors affecting the formation and spatio-temporal changes of the city and also inform managers and decision makers of the trends and growth patterns to help them in accurate planning, designing and managing. In order to achieve these goals, detailed information about the physical structure of the region in different time periods are collected, changes and spatial dispersion of the study area are observed, and information about the physical growth of the city is also obtained.
Material and Methods
The present study applies descriptive-analytical method to examine population growth and physical expansion of the city. After selecting the geographical area, satellite images captured in 1990, 2000, 2010 and 2020 were obtained from the US Geological Survey (USGS) web site. To calculate Shannon's entropy, the study area was divided into 25 regions based on the distance from central core of the city. Then, total area of each region and each zone (marked in each region for each period) were calculated. Thus, the necessary information was prepared to determine the trend of physical expansion and development of Babolsar city from 1990 to 2020. Shannon's entropy model not only has no limitation regarding the number of areas, but also has a high level of flexibility regarding the types of divisions used for the study area.
Results and discussion
These maps show that Babolsar has always grown both spatially and demographically from 1990 to 2020. The relative entropy of Shannon was calculated for each period and each region, and resulting coefficients show that not only is the rate of sprawl high in Babolsar, but it has always exhibited a sharply increasing trend during the last three decades especially from 2010 to 2020. Since examining expansion and dispersion require a careful consideration of population changes and trends, population of the study area was calculated for each year and its relationship with sprawl was examined. Findings indicate that sprawl has increased along with population increase. According to Holdern model and results obtained in the present study, population is the most important factor affecting physical growth of Babolsar city. It has played an especially powerful role from 1990 to 2000. Three main patterns of spatial development and sprawl can be identified in Babolsar: 1) strip or linear growth pattern spreading the city along the main transportation artery further away from the urban core. 2) Leapfrog development pattern which occurs when developers skip over land to obtain cheaper land further away from cities and thus create separately, singularly, discontinuously developed settlements. 3) Continuous low-density pattern developed due to excessive use of land for urban purposes along the outskirts surrounding the city. Gradual development in this pattern support infrastructure such as water, and energy and road network.
Conclusion
Studies indicate that sprawl in Babolsar city has had destructive effects on the environment and high quality agricultural lands around urban and rural settlements. Especial attention of Iranian society to its northern culture and the concept of "pleasure utopia" which has been assigned to the Southern Coast of the Caspian Sea are considered to be the most important reasons for urban sprawl in this city and other similar cities. Rapid increase in the number of villas built by indigenous and non-indigenous people has resulted in the destruction of high quality agricultural land and irreparable socio-economic damages. Currently, real estate trading, even in the villages of northern region, has not only intensified the sprawl, but also has changed and dissolved the traditional land use systems turning previous land owners into janitors. Other influential factors affecting sprawl in Babolsar and similar cities in the northern region of Iran include inefficient government policies in land and housing section, failure to meet the goals of urban and rural projects, population growth, real estate trade, development and construction codes incompatible with the realities of society, ambiguity in the laws and regulations governing construction within the legal limits of cities, lack of protection for government-owned land and properties, lack of proper supervision in construction projects.
Farshad Pazhooh; Farzaneh Jafari
Abstract
Extended Abstract
Introduction
Due to its specific geographical situation,Iranhas an especial precipitation pattern. In other words,despitehaving a precipitation equal to one-third of global average,Iran experiences a strong fluctuation in its rainfall regime. According to global classifications, floods ...
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Extended Abstract
Introduction
Due to its specific geographical situation,Iranhas an especial precipitation pattern. In other words,despitehaving a precipitation equal to one-third of global average,Iran experiences a strong fluctuation in its rainfall regime. According to global classifications, floods are considered to be among the most important natural disasters. In recent decades, humaninterferencesin the environment and improper management of land usehave resulted in increasing severity and higher frequency of these natural disasters (Abbas ZadehTehrani et al., 2010: 78). Extreme floodingcaused by climate changeshave resulted in severe damages in different parts of the world during recent decades and the effects of these changes are more significant in dry environments (Negaresh et. al., 2013: 15). Increasing urbanization and constructions has naturally reduced permeable areasin different basins. The resulting impenetrable surfacesare incapable of absorbing the rainfall, and consequently, the total volume of runoff in the city has increased (TaheriBehbahani and Big Zadeh, 1996).
Materials and methods
Two typesofground level data and data collected from higher levels of the atmosphere were used in the present study:
A) Precipitation data collected during the first ten daysof April 2019 by stations in Western and South Western Iran obtained from the Iranian meteorological organization.
B) Data collected from higher levels of the atmosphere including revised geopotential heights, sea level pressure, meridian and orbital winds, omega and especial humidityobtainedfrom the National centre for environmental surveys at Colorado, USA.
For synoptic analysis, environment to circulation approach was used to detect heavy rainfall peak periods and then their synoptic dimensions were reanalysed in the spatial range of 10 to 70 degrees north latitude and 10 to 80 degrees east longitude. Based on the analysis ofprecipitation data, April5th and11th,2019 were selected as having the highest rainfall resulting in the highest level of flooding and damage in the western and southwest regions of Iran.
Results and Discussion
On April 5th,2019 most regions of Iran have receiveda rainfall of more than 20 mm. The maximum levels of rainfall wererecorded in Koohrangstation(187 mm), Izehstationin Khuzestan (155 mm) and Yasoujstation(151 mm). OnlySistan and Baluchestan, Kerman and South Khorasan Province have experienced a stable situation without any precipitation on this day. However, on April 11th,2019, the highest level of rainfall has occurred inwestern stations of the country. The maximumlevels of rainfallon this day were recorded inNahavand and Tuyserkan stations (Hamedan Province) and Noorabad(LorestanProvince) with 126 and 122 mm, respectively. Central and northwesternregions of the country have experienced the next highest level of rainfallfollowing western regions. Figures 1 to 3 show a part of precipitation values in the western and southwestern regions of Iran during rainfall peak periods. Precipitations in more than 16 provinces in the western, southwestern, and central regions of the country have damagedagricultural, economic and social sectors. More than 45 people were killed in thesedays.The highest number of deaths and injurieshas occurred in Shiraz. In the western parts of the country, Poldokhtar and Mamoualn were most severely damaged. Moreover, heavy rainfall and floodinghave damaged 700 thousand hectares of agricultural land and resulted in 4600 billion USDlosses. In the construction sector, the country has suffered from 1,600 billion USD losses (Hamshahri Newspaper, 1398).
Conclusion
The present study have focused on synoptic and thermodynamic analysis of systems causing pervasive, heavy and hazardous precipitation onApril 5th and 11th in the western and south western regions of the country. The synoptic and thermodynamic analysis of maps indicated that the contrast between the influence of southern and western low pressure fronts such as Saudi Arabia, Sudan and the Mediterranean on the southwestern areas of the country and the cold high pressure frontover the Caspian Sea have caused a strong pressure gradientand formed a strong front condition over the country and the region under study at the sea level. In the middle and upper atmosphere, deep multiple amplitudetroughsformed over the North Pole passed through Russia as bipolar and low pressureblocks, cyclonic centressettled over the eastern Mediterranean regions and the eastern half of the trough formed as a result of blocking settledover the western and southwesternregions of the country. These have resulted in severe, and widespread negative omega and divergence of warm and humid southern weather over the country and the region.
Manijeh Ghahroudi Tali; Khadijeh Alinoori; Homa Rivandi
Abstract
1. Introduction Sabzevar plain is one of the areas facing subsidence phenomenon in Iran due to a sharp decline of groundwater table, development of residential areas over aqueducts or tectonics processes. The present study investigates the impact of these cases. Sabzevar County is located in a northwestern ...
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1. Introduction Sabzevar plain is one of the areas facing subsidence phenomenon in Iran due to a sharp decline of groundwater table, development of residential areas over aqueducts or tectonics processes. The present study investigates the impact of these cases. Sabzevar County is located in a northwestern plain in Khorasan on the hillside of Jogatai Mountains. Rapid agricultural development and increased water demand in recent decades have resulted in annual groundwater harvesting of about 400 million cubic meters and an annual deficit of about 30 million cubic meters in water reservoirs. The groundwater table in this plain annually experience an average decline of one meter. Despite increased precipitation in the last two years, only a 10 mm increased precipitation was recorded in Sabzevar station and the area still faces drought according to comparative analysis of rainfall. 2. Methodology Data used in the present study include 6 C-band single-look complex (SLC) images received from the ASAR sensor of Envisat. These images were captured during June, May, October, and December 2004 – 2008. Moreover, data including the groundwater table and the depth of water in local wells of Sabzevar County were collected from Khorasan Razavi Water Management Organization for the statistical period of 2003 – 2008 and 1974 – 2014. Data collected from local water wells and aqueducts were used to investigate subsidence. Following the geometric recording of the images, related interferograms were prepared. In order to calculate ground displacement, other effects were removed from the interferograms, and the effect of topography was corrected using the STRM digital elevation model (DEM) with a spatial resolution of 90 m to further improve the results. An adaptive filter was applied on the images to reduce the level of noise. In the phase correction stage, DEM produced through interferometry was used to correct the images and separate the deformation signal resulting in a differential interferogram. In order to estimate the groundwater decrease and study the resulting subsidence, the depth and groundwater level of 88 piezometers in Sabzevar were interpolated using the IDW method. Overlap methods were also used to investigate the relationship between the spatial distribution of subsidence occurrence and the location of wells, aqueducts, and faults. 3. Results Results indicates that the deformation of the area is the consequence of the high rate of subsidence in this short period of time. The maximum level of subsidence has occurred in the northeastern parts of the study area with a southwest-northeast direction starting from the hillside of Mish Mountain and moving with an increasing trend towards the hillside of Joghatay Mountain. Sabzevar and other cities of the county face an average subsidence rate of 10 cm per year. Images of displacement in the study area were obtained through interferometry and based on their overlap with subsidence. These images were then used for spatial analysis of aqueducts, wells, faults to study their impacts on subsidence. Results indicates that the subsidence rate has changed from 1 cm/year in 2007 to 14.6 cm/year in 2008. Active faults were also located in the western part of the study area across formations such as conglomerate, sandstone, red marl, and gypsum-bearing marls. Faults were generally developed perpendicular to the direction of subsidence indicating their role in downward displacement. Interpolation was performed for the 1974 – 2014 period to study long term consequences of this finding. Findings indicates that the decline in groundwater level has deteriorated moving from Sabzevar plain toward the surrounding areas. 4. Discussion and conclusion The study area was located on the hillside of Joghatay Mountain. Agricultural activities have developed in the area resulting in increased annual demand for water. Despite recent precipitations, the area still suffers from drought, decline in groundwater level, and subsidence. Results of a three-year interferometry selected from the period for which appropriate images were available have proved the occurrence of subsidence in the study area. A comparison between this image and the piezometric level in similar statistical years indicated the significant impact of groundwater level decline on subsidence. A comparison between the distribution pattern of faults, wells, and aqueducts and the subsidence area showed that a large number of wells were associated with subsidence, and the dominant faults were perpendicular to the surface of subsidence areas (Figure 1). Therefore, groundwater decline was the most important factor contributing to subsidence in this region, and long term piezometric level also have confirmed this effect. Faults perpendicular to the surface of subsidence areas might also intensify this phenomenon. In other words, further decline of groundwater table in the region will result in a higher rate of subsidence.
Mostafa Mohamadi dehcheshme; Fereshteh Shanbehpour
Abstract
Extended Abstract Introduction 21st century is the era of cities’vulnerability, since as urban life becomes more complex, ...
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Extended Abstract Introduction 21st century is the era of cities’vulnerability, since as urban life becomes more complex, cities face natural hazards and technological crises on the one hand and social-security crises on the other.Urban safety and security have long been a focus of urban planning, and planners have always been concerned about this important issue in the process of building and designing urban areas.Improving the security of critical infrastructures can play a key role in provision of better services and reduction of vulnerabilities, especially in times of crisis,Moreover, reducing the vulnerability of urban land uses by new crisis management approaches such as passive defense, which is one of the most important goals of urban managers can play a role in creation of a safe environment in cities and mitigationof damages. Materials & Methods The present research is theoretical-practical and descriptive-analytic in nature. For data analysis, the final weights of indices were determined using FAHP-GIS and then the neighborhood of each layer was identifiedusing the Distance tool. Afterwards, maps of the interval zoneswere overlapped usingFuzzy Overlay(gamma-0.9)of the Spatial Analyst Tools. Results & Discussion The findings of the present study on spatial analysis of critical infrastructure have indicated that: (A)The 2nd district of Yasujfaces the highest risk level, while the 3rd district faces the lowest level of risks. High concentration of critical infrastructures in the 2nd district and improper distribution of these infrastructures and organizations providing emergency servicesare the most important causes of risks in the city of Yasuj. B) None of the studied critical infrastructures and organizations providing emergency services in Yasuj are located in the very low risk zone. C) Only about 31% of the studied critical land uses are located in the low Risk zone. D) Spatial analysis of critical infrastructures in Yasuj has shown the lack of a logical balance in spatial distribution of these infrastructures. Therefore, ifa possible emergency situation damages a part of the city (the 2nd district as considered in the present study), the activities of many sectors will be challengeddue to the synergy and interoperability of the infrastructure. Conclusion The results show that 11 land uses or 45.83% of infrastructures with percent value of 0.19-0.1 are located in the high risk zone; 6 land uses or 25% of infrastructures with percent value of 0.20-0.39 are located in the relatively dangerous zone; 5 land uses or 20.83% of infrastructures with percent value of 0.40-0.59 are located in the medium risk zone, and finally, 2 land uses or 8.33% of the infrastructures with percent value of 0.60-0.79 are located in the low risk zone. None of the land uses in Yasuj are located inthe very low risk zone.
Behrooz Naroei; Shahindokht Barghjelveh; Hassan Esmaeilzadeh; Lobat Zebardast
Abstract
Extended Abstract
Introduction
The rapid expansion of urbanization along with irregular changes in land use and Landscape System of Tehran has disrupted the composition and distribution pattern of urban green infrastructure. The present study seeks to analyse the spatial-temporal changes of urban green ...
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Extended Abstract
Introduction
The rapid expansion of urbanization along with irregular changes in land use and Landscape System of Tehran has disrupted the composition and distribution pattern of urban green infrastructure. The present study seeks to analyse the spatial-temporal changes of urban green infrastructure in Tehran Landscape System affected by the spatial processes of land use changes in the statistical period (4 decades of 1990 to 2030). To reach this aim, the present study has identified (1) the effect of spatial processes on the changing landscape pattern and (2) the relationship between the spatial pattern and ecological processes of landscape and its influence on the capacities and constraints of green urban infrastructure.
Materials & Methods
The present study has focused on the landscape system of Tehran and its 22 districts as the study area. The descriptive-analytical study consists of following stages: 1) Classifying urban land uses in1990-2000, 2000-2010 and 2010-2020 statistical periods using Landsat satellite images: (in Envi 5.3, Google Earth and Arc GIS 10.2 software), 2) Modelling and forecasting land use changes in 2030 using integrated model of Markov chain, automated cells (CA-MARKOV) and TerrSetsoftware), 3) Determining spatial processes of landscape changes via decision tree algorithm. 4) Quantifying landscape metrics of composition and configuration of landscape pattern (green, open & built patches) at both class and landscape levels in the mentioned periods (in Fragstate 4.2 software).
Results & Discussion
Many environmental decisions presume that some types or composition of land use are preferred to others. It is assumed that the spatial arrangement of elements in a land-space mosaic controls its ecological processes. This proposition is known as the pattern/ process paradigm, and forms the central hypothesis of landscape ecology (a branch of science developed to study ecological processes in their spatial context). Ten spatial landscape processes are considered to reflect changes in various patterns of landscapes (aggregation, attrition, creation, deformation, dissection, enlargement, fragmentation, perforation, shift, and shrinkage). These processes actually change the spatial structure of urban landscape and affect the quality of ecological processes in Tehran Landscape System. To identify the spatial processes responsible for landscape pattern changes during a defined period of time, a decision tree algorithm was developed. Decision tree required the following input: area or size (a), the perimeter or edge length (p), and number of patches (n) in each land-cover class. The decision tree algorithm applied on Tehran Landscape System has indicated that spatial processes of 'attrition' and 'fragmentation' have led to a decrease in the integration of green and open patches in this landscape system. Measuring LSI and IJI metrics in 1990-2030 statistical period at the class level has also proved the previously mentioned finding. Increased ENN-MN and decreased PLAND of open and green patches during two periods of 1990-2000 and 2010-2020 due to the spatial process of 'attrition' have also showed this decreased integrity over time. These conditions have reduced the resilience of Tehran atmosphere and its capability to absorb air pollution and also have resulted in the recent development of thermal islands in different urban areas. Moreover, the COHESION metric has reduced in green and open patches due to the spatial processes of 'attrition' and 'fragmentation' at the class level. At the landscape level, the value of SIDI metric has also decreased from 1990 to 2020 and the same trend will continue according to 2030 forecast. Spatial process of 'aggregation' in constructed patches has resulted in a decrease of NP and PD at landscape level during 1990-2000 and 2010-2020. Findings indicate the effect of spatial process of aggregation on constructed lands (high-rise buildings) in the northern (such as District 1) and western parts of the city (such as District 22) which has interrupted wind movement and air purification in Tehran. The values of LSI and ED has also decreased at the landscape level due to the 'attrition' of open and green patches leading to a reduction in the heterogeneity order of urban landscape system. On the other hand, increased IJI value in 2020 and 2030 indicates increased turbulence in distribution and also increased fineness index of open and green patches in the landscape system of Tehran.
Conclusion
Findings indicate that spatial processes of 'attrition' and 'fragmentation' have resulted in a reduction in the number and area of green and open patches in the composition pattern and also decreased coherence at class level from 1990 to 2020. This has resulted in an unbalanced distribution of the patches in the configuration pattern of green urban infrastructure in Tehran. The spatial process of 'aggregation' has been repeated during the statistical period in the constructed patches. Data forecasted for 2030 shows the impact of 'attrition' on changes occurring in both green and open land use. The landscape is also getting more simplified due to the dominance of constructed land uses. Findings can be applied to determine a roadmap and plan the spatial pattern of urban green infrastructure.
Sayyad Asghari Saraskanroud; Imanali Belvasi
Abstract
Introduction
The sun is known as the source of energy, the origin of life, and the origin of all other energies. The global solar radiation is one of the fundamental structures of any climatic range. Hence, recognition of the features and the prediction of these basic structures have a great impact ...
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Introduction
The sun is known as the source of energy, the origin of life, and the origin of all other energies. The global solar radiation is one of the fundamental structures of any climatic range. Hence, recognition of the features and the prediction of these basic structures have a great impact on energy-related planning. One way to gainaccess to the solar energy information is the direct measurements of solar energy by measuring devices such as Pyranometer and Pyrheliometer Unfortunately, the measurement of the solar radiation is not always carried out in many parts due to the high cost, maintenance and the need for the equipment calibration. Remote sensing techniques can be an appropriate alternative to the experimental and old methods in this field due to the high accuracy and speed in predicting the net radiation values. In general, remote sensing models have a better performance in estimating solar radiation, and can be used as one of the suitable and low cost tools for estimating solar radiation. Considering the importance of solar radiation as a clean, availableand free of any environmental destructive pollutants, identifying the radiation areas to be introduced to the relevant authorities is essential and the aim of the research. In this research, it was attempted to study the feasibility of utilizing solar energy in the region of Alashtar County using the SEBALalgorithm and remote sensing technology.
Materials and Methods
To investigate and study the feasibility of using solar radiation energy, the Landsat-8 satellite images over a 12-month period of the year 2017, 1: 50,000 digital topographic maps of the Armed Forces Geographic Organization and the climatic data of the study area including temperature, precipitation, wind speed and the number of sunny days were used. The ENVI software was used to perform the calculations related to SEBALmodel and the ArcGIS software was used to implement the model. In this study, the feasibility of using solar energy in Salsala city was studied using SEBALalgorithm and remote sensing technology. In this method, the instantaneous values of pure radiation are obtained by measuring the sun’s incident radiation from the cloudless images and using surface albedo, surface emission and surface temperature. In this method, instantaneous values of pure radiation are obtained by measuring the sun’s incident radiation from cloudless images using surface albedo, surface emission and surface temperature. After calculating the parameters of the SEBAL algorithm, the net surface radiation flux was calculated.
Discussion and Results
The results showed that the average maximum short-wave radiation was 996 watts per square meter in June and the minimum was 460 watts per square meter in January, while the highest amount of net radiation in September was calculated to be 602 watts per square meter and the lowest amount in January was calculated to be 261 watts per square meter. Also, the highest percentages of net radiation distribution in the ranges of 0-200, 200-400, 400-600, 600-800 and 800-1000 watts per square meter were in August, November, April, September and June. The highest percentage of net radiation distribution was in the range of 600-800 watts per square meter with 69.86% of total net radiation in September and the lowest percentage was in the range of 800-800 watts per square meter in January.
Conclusion
In order to carry out the research, the Landsat 8 ETM satellite images for the 12 month period of the year 2017 were provided. But, since the images of February, March and December were completely cloudy, they were not used. Then the preprocessing operation in ENVI software was used on all bands of images. The amount of pure radiation in the study area was calculated in watts per square meter in January to November in ENVI software environment and by the utilization of SEBAL algorithm, using the prepared images (Table 2). The results of Table (2) show that the average maximum input shortwave radiation is 996 watts per square meter in June, the lowest amount input is 460 watts per square meter in January, the highest output long wave radiation is 539 watts per square meter in July and the lowest output is 391 watts per square meter in January. Finally, the highest amount of net radiation reaching the surface of the Earth was 602 watts per square meter in September and the lowest amount was 261 watts per square meter in January. The highest percentage of net radiation in the range of 600-800 watts per square meter was 69.86% in September 2017 and the highest percentage of net radiation in the range of 600-400 watts per square meter was 60.12% in January 2017.
The difference in the amount of net radiation reaching the ground in the study area is due to the difference in the angle of the sunlight and the number of sunny hours in different months of the year.
The results obtained from of the information in Tables 2 to 11 prove this fact. Also, given the sensitivity of the photovoltaic cells that are sensitive to the solar radiation from the radiation threshold of up to 1000 watts per square meter and receive them, it can be concluded that solar radiation in the city of Alshtar has the potential to implement the solar photovoltaic plans in 9 months of January to November.
Geographic Data
Ali Akbar Sabziparvar; Alireza Seifzadeh
Abstract
Extended Abstract
Introduction
Ultraviolet radiation (UVA) is a dangerous part of solar radiation that makes a small percentage of total solar radiation energy (5 to 7 percent). Despite the beneficial role of solar energy in the production of vitamin D3, it can cause irreparable damage to human cells. ...
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Extended Abstract
Introduction
Ultraviolet radiation (UVA) is a dangerous part of solar radiation that makes a small percentage of total solar radiation energy (5 to 7 percent). Despite the beneficial role of solar energy in the production of vitamin D3, it can cause irreparable damage to human cells. The majority of previous studies on ultraviolet radiation in Iran have focused on in-vitro impacts of UV radiation on human health and plant physiology in a limited study area. The present study estimates daily cumulative UVA radiation in central regions of Iran and compare it with total column ozone (TCO), cloud optical depth (COD) and aerosol optical depth (AOD) in different seasons.
Materials and methods
The present study estimates daily cumulative UVA radiation (320-400 nm) over a 13-year reference period (2005-2017) in a large area in Central Plateau of Iran with arid and semi-arid climate using TUV5 multilayer radiative transfer model (Madronich, 1993). 22 synoptic stations in 9 provinces were investigated in this study. Daily cumulative UVA radiation under three different sky conditions (clear-sky, overcast and real-sky) was also compared with geographical distribution of total column ozone (TCO), cloud optical depth (COD), aerosol optical depth (AOD) and surface albedo (SALB). Required data were extracted from satellite images (downloaded from http://disc.gsfc.nasa.gov) and Iran Meteorological Organization data center.
Results and Discussion
In general, maximum daily UVA radiation was recorded in the southern half of the study area. During warm seasons of the year, the eastern part of the study area (Kerman and Khorasan-e-Jonubi Provinces) and during the cold seasons of the year, central and southwestern part of the study area (Yazd and Fars Provinces) experience maximum daily UVA radiation. Maximum cloudiness in spring has occurred in northeastern and western parts of the study area and a lower level of cloudiness has always been recorded in its southern parts. Thus, the highest level of UVA radiation has been recorded in southeastern parts of the study area and especially in Birjand station (1071.12 kj/m2 per day). As expected, maximum UVA radiations in all sky conditions and all stations were recorded in summer. The lowest level of cloudiness was also recorded in this season. During autumn and in overcast condition, the highest concentration of UVA was recorded in southeastern parts of the study area and Birjand station (725.85 kj/m2 per day). This is consistent with cloud optical depth and total column ozone, and so, the lowest amount of ozone in this season was recorded in Birjand station (276.57 Dobson). The highest values of atmospheric aerosol with an average of 0.59 optical depth were recorded in winter in the eastern parts of the study area. Thus unlike other seasons, maximum UVA radiation in overcast condition moves toward central stations in winter. Comparison of daily cumulative radiation maps in overcast condition shows that there is a good agreement between daily cumulative radiation and cloud optical depth (COD) and aerosol optical depth (AOD). This indicates that in overcast condition, total column ozone (TCO) have a weaker impact on UVA radiation as compared to other sky conditions. However, UVA radiation is consistent with total column ozone in clear-sky conditions.
Conclusions
Geographical distribution of UVA radiation indicates that maximum daily radiation in warm seasons has often occurred in the eastern parts of the study area. However, maximum concentration of UVA radiation moves towards southwestern parts of the region in cold seasons. Therefore, residents of the eastern and southwestern regions face a higher risk due to daily cumulative UVA radiation. Findings indicate high biological risk of solar UVA wavelengths in clear-sky condition within the study area. Overcast conditions can reduce daily UVA radiation up to 52% in winter and 21% in summer as compared to clear sky conditions. In real-sky conditions, daily UVA radiation decreases up to 19% in summers and up to 32% in winters as compared to clear-sky conditions. As a result of lower solar zenith angle, the impact of cloudiness on surface UVA radiation in summer is relatively less than cold seasons.
Elham Forootan
Abstract
Extended AbstractIntroduction. Floods are natural disasters which occurrence causes annual great damage to people and environment around the world. So, specifying flood susceptible land is a necessity to reduce and control destructive impacts. Watershed management implementations could affect runoff ...
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Extended AbstractIntroduction. Floods are natural disasters which occurrence causes annual great damage to people and environment around the world. So, specifying flood susceptible land is a necessity to reduce and control destructive impacts. Watershed management implementations could affect runoff volume and flood occurrence. The goal of this study is to apply the combination of Curve Number method and AHP in Arc-GIS to prepare flood susceptibility map and to investigate the role of biological measures in flood susceptibility of the region through this method and statistical tests.Materials & Methods .For this purpose, Pardisan watershed located in the southern part of Qom city was selected. Ten factors layers viz. drainage density, slope, annual rainfall, distance from river, elevation, flow accumulation, SCS Curve Number, geo infiltration, geomorphology and previous floods were prepared and classified based on flood susceptibility in different scales. Then future Curve Number was determine with assuming the implementation of biological watershed management in different land uses such as rangeland, agriculture, garden and badland. In this study, AHP method in Arc-GIS was used to calculate pairwise comparison and determine the weight of each factor. Overlaying current and future Curve Number layers with nine layers using the weights obtained from the hierarchical analysis method led to the preparation of flood susceptibility maps for pre and post watershed management implementation. Results & DiscussionGeo infiltration map showed the proportion area of “low”, “and “very low” infiltration classes were 4.46% and 16.87%, respectively while moderate and high infiltration classes were 39.75% and 38.92%. Slope map indicates that 0-2%, 2-5%, 5-15%, 15-35% and 35-60% classes comprise 29.87%, 35%, 30.11%, 4.88% and 0.14% of the studied area, respectively. In this region, South parts were steep whereas; north parts were mild. Distance to river is another factor classified in to four groups of 0-500, 500-1000, 1000-3000 and 3000-6500 meter with 38.86%, 24.32%, 29.63% and 7.19% of the region, respectively. Elevation classified map revealed 45.1% of the region were in 900-1200 meter range whereas; 36.4%, 14.8%, 3.6% and 0.1% were in 1200-1500,1500-1800,1800-2100 and 2100-2400 meter classes, respectively. As can be seen in rainfall map, 25.57% of the region was categorized in 140-160 mm rainfall class while 35.41%, 20.59% and 18.43% of the whole area were classified in 160-180,180-200 and 200-250mm groups. In the region, South parts have more rainfall volume than north. Also, flow accumulation map indicated that 96.5%, 1.97%, 1.07%, 0.24% and 0.22% were classified as 0-1500, 1500-5000, 5000-15000, 15000-25000, 25000-100000 values which high flow accumulation pixel range show high flood susceptibility. Drainage density map represents 10.38%, 14.36%, 56.88% and 18.38% of the studied area were grouped in 0-0.05, 0.05-0.07, 0.07-0.09 and 0.09-0.12 classes. Also, Curve Number (SCS) map for garden, cultivated lands, rangelands and badlands shows that 25.54% of the study area was classified as 15-35 CN value while 36.14%, 0.9% and 37.42% were categorized in 35-50, 50-65 and 65-80 classes before performing biological measures. After biological measures in different uses, 15-35 Curve Number values are observed in 36.6% of the area and 35-50, 50-65, 65-80 classes comprise 32.05%, 29% and 2.35% of the study area, respectively. The geomorphological map shows that the class with the highest score is visible in 68.96% of the area, while the classes with the lower scores are observed in 3.07, 18.34, 9.37, and 0.26% of the region, respectively. The past flood zoning map of the region also shows that 22.41% of the region exist in low susceptibility class, 36.15% of the region locates in the medium susceptibility class and 41.44% is in the high sensitivity class. For AHP approach, the calculated consistency ratio of this study was less than 0.1. Therefore; the compatibility between ten selected factors was acceptable. AHP results showed that the Curve Number factor has the highest weight percentage (27.44) whereas; the geo-infiltration has the lowest weight percentage (3.20). Comparison of flooding classes for pre and post water management implementation shows that high and medium flooding classes will decrease by 7.3 and 39.7% and low and very low susceptibility classes will increase by 22.18 and 24.82 %, respectively due to the implementation of biological watershed management measures. Also, Sign and Wilcoxon statistical tests indicated the existence of significance difference in flood classes’ for pre and after implementing biological watershed management. ConclusionFlood susceptibility map provision is a necessity in arid and semi-arid regions due to insufficient vegetation cover. The results of this study indicate positive effects of biological watershed management in decreasing flood vulnerability. These findings can be considered for future planning of the region and help watershed managers for optimal utilization of water and soil resources and reduction of flood damage.
Mohammad Ghasem Torkashvand; Mostafa Mousapour
Abstract
Extended Abstract
Introduction
The snow cover is one of the quickest changing phenomena on the earth that considerably affects the climate, amount of radiation, the balance of energy between atmosphere and earth, hydrology cycle and biogeochemical as well as human activities. Precise estimate ...
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Extended Abstract
Introduction
The snow cover is one of the quickest changing phenomena on the earth that considerably affects the climate, amount of radiation, the balance of energy between atmosphere and earth, hydrology cycle and biogeochemical as well as human activities. Precise estimate of snow cover is regarded as one of the fundamental operations in precipitation. Thus, monitoring the snow-covered surfaces hasspecial importancefor the perspective of climatic, ecologic and hydrologic studies. The researchers believe that remote sensing data can lead to better assess from the snow-covered areas than traditional topography methods. Therefore, nowadays, in efficient management of water resources, remote sensing data aims to achieve exact information on snow-covered areasis applying operationally. Satellites are suitable tools to measure the mentioned areas since high snow reflection creates a good contrast with other natural surfaces except clouds. This research is conducted to compare the performance of Cornell functions of support vector and object-oriented Fuzzy operators in estimating the desired areas in Almabolaq Mountain, Asadabad.
Material & Methods
The data used in this research are the bands with 10 m spatial segregation of 2B Sentinel satellite including bands 2, 3, 4 and 8 on 6th March 2020. To classify Cornell functions of support vector machine and compute their accuracy, ENVI software was implemented. The eCognation software was used to partition and categorize those with the same object-oriented Fuzzy operators. Separating similar spectral sets and classifying those with the same spectral behaviour are regarded as satellite information classification. In other words, categorizing the photo pixels, and allocating one pixel to one class or phenomenon are the mentioned classification. Support vector machinethat is one of the most common classifiers in learning machine, which divides data using an optimum separation super plate. One of the important advantages of support vector machine is the ability to deal with high dimensional data using almost less training samples for remote sensing applications. Objective analysis is an advanced technique of image processing which is used to assess the digital images and typical conflicts of basic pixel classification based on different methods. Traditionally, pixel-based analysis can be done by available data of each pixel whereas object-based analysis considers a set of similar pixels called objects or image objects. It regards adjacent pixels with the same information value as one distinct unit called piece or segment. In fact, pieces are the areas produced by one or few homogeneous criteria in one or few dimensions of a specific space, so that the pieces have extra spectral information in each band, mean, maximum and minimum amounts, variance, etc. as compared to single pixels. Combining the object-oriented and Fuzzy methods provides the classification of image pieces with a specific membership degree. In this process, image pieces with different membership degrees are classified in more than one class, so according to the membership degree, image piece classification is done leading to the increased final precision.
Results & Discussion
In this research, after preparing satellite images in SNAP software using Sen2Cor, radiometric correction was conducted on the images. To prepare the classification map of Cornell functions of support vector machine, TIFF satellite images were called by ENVI software. Using the shape file of the case study, the area cutting operation was done. Afterwards, two classes of snow and non-snow regions were created to pick up the training points, so based on imagery processing, training points were specified for each class. To classify support vector machine algorithm, linear, polynomial, radialand sigmoid Cornell functions were applied,soclassification maps were separately produced. To draw the classification map of object-oriented Fuzzy operators, satellite images pre-processed in previous stages were called by eCognation software, then they were defined as a project. Afterwards, two mentioned classes were defined to do the classification process, for each class, the desired Fuzzy operator was determined. For suitable classification, it was done in various scales and weight coefficients of shape and compactness. Scale 75, shape 6.0 and compactness 8.0 presented suitable classification. The training samples, parameters of lighting, mean and standard deviations were chosen as distinct features of classes for object-oriented classification. Using the nearest adjacent neighbor algorithm, object-oriented classification was done for each of the Fuzzy operators. After drawing the snow-covered areas through Cornell functions of support vector machine and object-oriented fuzzy operators, the accuracy of classification was computed.
Conclusion
The results indicate that AND algorithm showing the logic share and minimum return value out of Fuzzy values is the highest accuracy (98%) and to classify digital images,the object-oriented processing methods of satellite imagery enable more precision due to the data related to texture, shape, position, content and geometrical features as compared to Cornell functions of support vector machine.
Hasan Sinaei; Mohammad Saliqe; Mehri Akbari
Abstract
Extended AbstractIntroductionPrecipitation is considered to be one of the most important elements of climate. It affects the distribution of other climate elements and thus, has played a prominent and significant role in recent studies especially those focusing on global climate change. Due to ...
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Extended AbstractIntroductionPrecipitation is considered to be one of the most important elements of climate. It affects the distribution of other climate elements and thus, has played a prominent and significant role in recent studies especially those focusing on global climate change. Due to its geographical location, Iran climate is affected by various climate elements. As one of the most important components of general atmospheric circulation, jet streams affect the quality of precipitation (amount, intensity, temporal and spatial distribution, etc.). Jet streams are relatively narrow bands of strong wind traveling across very long distances at high altitudes of the troposphere (tropopause) forming a hypothetical wind tunnel. Materials & MethodsThe study area surrounds southwestern Iran including provinces of Khuzestan, Ilam, Chaharmahal and Bakhtiari, Kohkiluyeh and Boyer Ahmad, Bushehr and Fars. The present study applies statistical methods and synoptic climatology. Based on the library research, representative days were selected in accordance with the following conditions: 1. Precipitation must have occurred in cold season, since cold season events generally show various patterns due to multiple weather systems affecting precipitation in Iran. 2. A significant percentage of the total annual precipitation must have occurred on the specified day (for example, a precipitation in the 90th percentile in each station). 3. Precipitation must be pervasive (i.e. recorded in more than 70% of the stations in the study area). Three representative days, December 17th 2006, November 25th 2014, and January 17th 1996 were thus selected with the highest precipitation volume over a 30-year statistical period (1989-2018). Two climate databases (precipitation data collected from meteorological stations in the capital city of the previously mentioned provinces and NCEP/NCAR climate data separated based on a 2.5 degree pattern) were used for synoptic analysis of these precipitation events. First, daily precipitation recorded by synoptic stations of southwestern Iran on each of these days was obtained. Then, climatic parameters such as geopotential altitudes of 500 and 850 hPa, jet streams occurring at an altitude of 300 hPa, specific humidity at the 1000 hPa level and values of omega component (measuring upward and downward movement of air flow) at the 500 and 850 hPa levels have been used to explore the relationship between these precipitations and jet streams in troposphere. Finally, GrADS was used to map the previously mentioned parameters. The relationship between precipitation occurrences across different stations of southwestern Iran and troposphere jet streams was exhibited based on an analysis of jet stream maps, moisture flows and other climatic parameters at various atmospheric levels. Results & DiscussionThe relationship found between previously mentioned precipitation events and tropospheric jet streams shows that in each of these events, the jet stream is a westerly wind meandering toward southwest or northeast in the study area and extending throughout North Africa and the Middle East. Central core of the jet stream was traveling above the study area with a speed of 35 to 60 meters per second. The present study indicates that in these three days of heavy precipitation, the jet stream axis has affected the study area in a southwest-northeast direction. Moreover, a cyclone is located at the 850 and 500 hPa levels approximately over eastern Mediterranean whose eastern side extends across southwestern Iran. Southwest-northeast direction of jet stream axis and eastern side of the Mediterranean Sea cyclone being extended toward the study area intensified instability in the lower atmospheric levels of the study area. Negative omega values at the 850 and 500 hPa levels (from -0.15 to -0.8 Pascal-second) indicates severe atmospheric instability in the study area. ConclusionEvery year, southwestern regions of Iran face intensive, and pervasive rainfalls resulting in severe floods and damaging agricultural products, gardens, roads, facilities, industries, etc. The present study indicates that Mediterranean cyclones, westerly winds across the lower atmospheric levels, and the subtropical jet stream meandering in the southwest-northeast (in the meridian direction) direction across the upper atmospheric levels affects the study area. Precipitation in this region is mainly supplied by the moisture coming from warm southern seas (Red Sea, Arabian Sea, Sea of Oman, Persian Gulf, etc).
Seyed Ali Ebadinejad; Mohammad Reza Pourgholami-Sarvandani; Ali Asghar Mohammadpour; Ali Osanlu
Abstract
Extended Abstract Introduction Along with other environmental factors, climatic conditions are among the most important factors affecting social, moral and cultural problems. People behave differently in different climates. Quetelet and Gurreydeveloped crime statistics in Franceandinvestigatedits relationship ...
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Extended Abstract Introduction Along with other environmental factors, climatic conditions are among the most important factors affecting social, moral and cultural problems. People behave differently in different climates. Quetelet and Gurreydeveloped crime statistics in Franceandinvestigatedits relationship with physical environment.Thus, they studied the effects of geography and climatic conditions on human behavior, including criminal behavior. In Climate and Crime, Ellen J. Cohen argues that situational approaches, selected rationaltheories and routine activity theory all suggest that climate has a major impact on the rate of crimes and criminal behaviors. Based on their observations, Quetelet and Gurreyformulatedthethermic law of delinquencyin criminology. Based on statistical studies, they concluded that violent crimes are more frequent in hot seasons and hot regions, while in cold regions and cold seasons, more deceptive crimes such as crimes against property requiring thinking and imaginationoccurmore often. It should be noted that crime is a social phenomenon affected by various factors. Environmental conditions can also intensify the threat of human behaviors. The present study seeks to investigate the relationship between the climatic element of temperature and the occurrence of crime in Shiraz, Abadeh and Larestancounties of Fars province? Materials & Methods The present study is applied in nature and purpose, while taking advantage of an analytical-descriptive method. 3 meteorological stations of Shiraz, Abadeh and Larestan were studied here. Investigated data included the seasonal average temperature and seasonal rate of crimes for the2008-2013 period. Seasonal rate of crimes including social corruption, theft, forgery, strife, mischief, intimidation and coercion, smuggling, drug-related crimes, murder, and suspicious death were investigated in Shiraz, Abadeh and Larestan, which have a meteorological station. Crime statistics were collected from the Prevention Police Department of Fars province Law Enforcement Force and statistics related to the climatic elements of temperature were obtained from Fars Meteorological Department. Different descriptive and inferential statistical methods were used to analyze the data and Pearson correlation coefficient test was used in inferential statistics. Data analysis in the present study included two stages. First, the seasonal and annual percentage of various crimes were studied in each of the mentioned cities. In the second stage, the correlation coefficient between the average temperature and the total (seasonal) number of crime occurrence were investigated. Discussion Investigation of various crime occurrence in Shiraz, Abadeh and Larestancounties of Fars province revealed that in spring, strife and affray (47.11), theft (23.16) and social corruption (19.16) were the most frequently committed crimes in Shiraz. However, intimidation and coercion (0.32), smuggling (0.24), forgery (0.20) and murder (0.05) had the lowest frequency in Shiraz during spring. In summer, strife and affray (47.71), theft (24.64) and social corruption (20.95)are considered to be the most frequent crimes, while intimidation and reluctance (0.33), smuggling (0.23), forgery (0.20) and murder (0.03) arethe least frequent crimes, respectively. In autumn, strife and affray (44.36), theft (27.71) and social corruption (18.24) were more common, whileintimidation and coercion (0.33), smuggling (0.27), forgery (0.26) and murder (0.04) had the lowest frequency. In winter, strife and affray (43.92), theft (29.99) and social corruption (16.84) were the most frequently reported crimes,whileintimidation and coercion (0.35), smuggling (1.4), forgery (0.24) and murder (0.02) were the least frequently reported crimes. Findings indicate that during the 2008-2013 period, strife and affray (45.86), theft (28/28) and social corruption (18.84) were the most common crimesin Shiraz city, while smuggling (0.43), intimidation and coercion (0.33), forgery (0.22) and murder (0.03) were the least common crimes. Generally in the three counties, crimes against the person such as strife and affray, murder, mischief, intimidation and coercion were more frequently reported in warm seasons (spring and summer). However, crimes against property, such as theft, were more frequent in cold seasons (autumn and winter). Strife and affray(0.95) in Shiraz have the highest correlation with the seasonal average temperature. There is a negative correlation between the crime of strife and affray and the seasonal average precipitation in Shiraz. The same relationship existsbetweenstrife and affray and the seasonal average relative humidity in Shiraz. In Larestan, drug-related crimes (-0.97) have the highest negative correlation with the seasonal average temperature. In Abadeh city, social corruptions (0.99) have the highest correlation with the seasonal average temperature. Conclusion: In total, crimes against the person, such as strife, murder, mischief, intimidation and coercion were more commonly reported in the warm seasons of the year (spring and summer) in the three counties on the whole and separately. However, crimes against property such as theft had a higher rate of occurrencein the cold seasons (autumn and winter). Therefore, as crimes against the personare more common in warm seasons and crimes against property are more frequent in cold seasons, it can be concluded that QueteletandGurrey’s thermic law of delinquencyis in force in all the three specified counties. However, this law is not generalizable and it cannot be concluded that crimes against property occur more in cold regions and crimes against the person occurs more in warm regions of Fars province. In this respect, this law only applies to Larestan which is located in the warm region of the province.
