هادی عبدالعظیمی

Wetlands are considered valuable resources of the environment. Despite the importance of wetlands, they are currently threatened by intensive water harvesting for irrigation, industrial development, deforestation, construction of dam reservoirs, and changing rainfall patterns. Monitoring can determine the changes in the location, extent, and quality of the wetland and therefore plays an important role in the maintenance and protection of the wetland. Ecosystem monitoring with remote sensing methods offers the advantage of difference, frequent and uniform coverage of large areas. The study of effective parameters or up-to-date maps that show spatial and temporal changes in the sub-basin of Horul Azim Wetland is not available. Therefore, considering that currently, this wetland is struggling with various problems to continue its survival, the purpose of this research is to use Google Earth Engine and satellite data to study the process of wetland changes.

This study was done on the platform of Google Earth Engine open source system. In this study, the data of water area, vegetation cover, precipitation, evaporation, and surface temperature were coded in the Google Earth Engine system in a standard way and their time series was obtained. Also, the NASA GRACE data analysis tool (DAT) was used for time series of groundwater levels. In this research, the Mann-Kendall test and Spearman's correlation were used in order to evaluate the changes in different parameters. In this research, the period from 2000 to 2022 was considered to investigate the trend of the data according to the available time range of the data. Finally, to check the fact that the changes in the zones were affected by floods, the data of the Global Surface Water of Water Occurrence (GSWE) probe was used.

 The results of the analysis graph of the water area data trend showed that from 2007 to 2019 the water area trend is increasing, with 2007 being the minimum year and 2019 being the maximum year, and the reason for this was the 90% water withdrawal of the Hor al-Azim wetland in the Iranian part. Also, the reason for the increase in the water area in 2017 is heavy rains that lead to floods and overflowing of the Karkheh dam in the sub-basin of the Hor al-Azim wetland. In 2017 and 2020, 2021, the water area shows a significant increase, which is due to the change in climatic behavior and the occurrence of floods in these years. Finally, the trend of the blue zone will be downward until July 2022. The results of a careful analysis of the data trend by the Mann-Kendall test showed that the trend of the available time period was observed. Kendall's tau value also confirms the increasing trend. It seems that the increasing trend of the water area in the years 2019 to 2021 in this study using the Google Earth Engine system is the result of the floods of the last few years, that Considering only this parameter and these data leads to errors in the study and investigation of the condition of Hor-al Azim wetland. No significant trend was observed in the time series of vegetation cover, but according to the positive Mann-Kendall vegetation cover statistic, one of the causes of the non-significant decrease in the groundwater level could be the increase of pastures and agricultural lands. Kendall's tau value for the surface temperature also showed a negative value (-0.24). According to this result and the sensitivity of the evaporation parameter to temperature, we can point to the role of this parameter in reducing evaporation in the sub-basin of the Hor al-Azim wetland. The northwest and southeast regions have the highest temperature up to a part of the central region of the sub-basin. The western part, which includes the border of the Hor al-Azim wetland, has the lowest temperature, and most of the central part has the lowest temperature, one of the causes of which can be the presence of vegetation and the development of agricultural lands. The time series graph of precipitation showed that the parameter of precipitation in the years 2017 to 2020 had an upward trend, which led to recent floods in the studied area. The results of the Mann-Kendall test for the general trend of evaporation and transpiration parameters, ground surface temperature, and precipitation in the sub-basin of the Hor al-Azim wetland did not show a significant trend. Using the Global Surface Water Explorer (GSWE) data, the occurrence of water, the intensity of water changes, and the seasonal change of water on the wetland were studied for the period of 1984-2021. The study of this dataset confirmed the human interference (creating the Karkheh Dam and draining its lake) and the occurrence and effects of the flood on the sub-basin of the Hor-al Azim wetland. The results of Spearman's correlation test also showed that climate changes such as changes in precipitation patterns and human activities can become factors that affect the surface of the water body of Hor al-Azim Wetland. The results of this research can be used in the management of Hor al-Azim wetland and wetlands with similar conditions.

Nitrogen dioxide is considered one of the important indicators for evaluating the air quality of cities, therefore, identifying the areas contaminated with this pollutant is very important. One of the sciences and technologies that can help urban environmental experts to identify these areas in the shortest time and at a lower cost is satellite remote sensing. Currently, satellite remote sensing is a useful technology for measuring atmospheric pollutants at the global, regional, and urban levels. Therefore, the present research has identified and investigated the temporal-spatial distribution of nitrogen dioxide gas during the spread of Covid-19 using Sentinel-5P satellite data in the Shiraz metropolis for 24 months (2019 and 2020). Based on the results of this research, the highest monthly average values of nitrogen dioxide gas in 2019 and 2020 are related to the autumn season. In addition, district 2 of Shiraz was identified as the most polluted area in the two years studied. In addition, after analyzing the parameters of wind, precipitation, and temperature, it was found that the wind factor with a correlation coefficient of -0.638 at a significance level of 1% compared to other climate factors had the greatest impact on the change in nitrogen dioxide gas values. The Covid-19 crisis also played a role in changing the amount of nitrogen dioxide gas in 2020 compared to 2019 every month with its impact on the reduction of traffic and urban traffic. The pattern of changes in the average nitrogen dioxide gas related to satellite data in the studied years had a decreasing trend, which was consistent with the pattern of changes in the values obtained from the pollution monitoring station. The results of this research can be useful in urban livability and crisis management.

The world is experiencing an unprecedented flow of urbanization. Population growth and urbanization have changed land use in urban areas. One of the consequences of these changes is the increase in the temperature of the earth's surface in urban areas and the formation of a heat island. The main purpose of this research is to monitor the surface temperature of the earth and its relationship with land cover. For this purpose, Landsat 8 and 7 satellite images were taken first. Then, using the supervised classification method - maximum likelihood algorithm, the land cover map was classified into three classes of man-made land, barren land and vegetation and finally, in order to monitor the surface temperature of the earth, the surface temperature map of Kashan city was extracted using single channel algorithm. The analysis of land cover showed that man-made lands increased by 21.05 percent during the years 1385 to 1400, and barren lands and lands with vegetation (with 11.17 percent and 9.88 percent, respectively) has had a decreasing trend. The minimum temperature of the earth's surface has reached from 34.87 degrees Celsius to 42.33 degrees Celsius in 1385 and 1400, respectively. Also, during the 15-year period, the maximum temperature has increased from 59.63 degrees Celsius to 60.70 degrees Celsius. Vegetation has the lowest surface temperature in the studied years. Due to its climatic and spatial nature, the city of Kashan, like other arid and semi-arid regions of Iran, has a lower surface temperature than its surrounding environment, this phenomenon is known as urban cool islands. Moran's spatial autocorrelation analysis at the 99% confidence level showed that the surface temperature data of Kashan city are distributed in clusters. According to the Gi* index, in all the studied years, the maximum temperature belongs to barren lands.

Understanding the levels of urban resilience and planning to reduce the effects of various risks has a key role in managing urban crises. The purpose of this research is to identify areas with different resilience in the eleven districts of the Shiraz metropolis in order to deal with the flood crisis. The current research is based on the Fuzzy-AHP method and uses the criteria of the level of relief (sub-criteria of the density of firefighting centers, emergency, medical centers, hospitals, law enforcement, and Red Crescent), the state of residence (sub-criteria of the density of temporary accommodation places, population density and spaces Occupied), access status (sub-criteria of the density of arterial type and width of passages), worn texture and equipment placement status, identifies areas with different levels of resilience (weak, medium, good and very good). Examination of the level of relief showed that there is a weakness of relief in areas far from the city center. Therefore, it is suggested to increase the emergency services in the neighborhoods and areas far from the center of Shiraz in these places. In terms of criteria and sub-criteria examined in this research, weaker resilience was generally seen in the east and northwest of the city. The results of this research can be considered by executive managers in the phase of crisis management prevention and preparation.

Due to the earthquake damage caused by the earthquake, one of the most important issues which is considered by the authorities after the earthquake is the water supply of citizens of a city. Unfortunately, in many cities of Iran, the management of the crisis, especially concerning drinking water, is not noticed in the aftermath of the various events that the metropolitan is considering. due to the great importance of this issue, in this study, suitable spaces to locate water emergency reservoirs in shiraz, based on criteria urban public open spaces (park and green space, open space Stadium, city Squares), Population density (near Population block whit high Population density), roads network (access to roads high way, main road, minor road), high-risk centers against Earthquake (wearing texture areas in the slopes areas Close to the fault, Historical points of the earthquake) Based on the hierarchical analysis Process (AHP) and decision support system, GIS, (using of transformation functions of a polygon to point, vector to raster, Euclidean distance, reclassify and the functions of a scalar subset to be evaluated. The results of this study suggest the locations with the scores of 7,8,9, that located mainly in destroyed texture areas, regions with high population density and urban main roads of Shiraz as the alternatives for locating of the city's emergency water Resviors.

Human 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. 

Maharloo 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. 

The 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. 

Wetlands 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.

Population growth, industrial expansion, urbanization, and urban construction have led to drastic changes in the morphology of catchments. Land grading and encroachment on rivers and canals have changed the pattern of natural drainage and flow in cities. One of the consequences of this phenomenon is the increase in the risk of flooding and flooded passages and the increase in maintenance costs of cities and has caused a lot of possible human and financial losses in some cities. In our country (Iran), the occurrence of floods is related to the disturbance of the natural balance and the morphological and physiographic conditions of the watersheds than to the heavy rains. One of the reasons for the flood event is the difference in topographic altitude between different regions of the country, according to which runoff is drained from the highlands to the lowlands in the shortest time. Therefore, the importance of research in the field of flood mapping has doubled. Unfortunately, the recent flood that occurred in April 2017 at the Quran Gate in Shiraz was one of the cases in which human intervention and lack of accurate knowledge about the watershed conditions led to irreparable human and financial losses. The floods killed 19 people and injured 200 others. Due to the occurrence of conditions and prevention of similar events, in the present study, to manage the crisis, especially in the prevention phase, floods zones of Shiraz metropolis using TOPSIS method and Geographic Information System (GIS), be identified and evaluated.

As the capital of Fars province, Shiraz is located on a long plain 120 km long and 15 km wide. The city is geographically located between the coordinates '53 '29 29⁰ to ''47 '41 29⁰ north latitude and ''36 '26 52⁰ to ''02 '37 52⁰ east longitude. The sea level is 1488 meters at the eastern end of the city and about 1700 meters to the west. In this study, a  flood mapping was prepared using the TOPSIS method in ArcMap10.3 to identify flood risk areas. In this regard, thirteen criteria, including slope, aspect, elevation classes, precipitation, distance from the canal, drainage density, distance from worn-out urban structures, building density, geological formation, land use, groundwater depth, history of floods, and runoff, were used as information layers. In this study, the TOPSIS decision-making method (similarity to the ideal solution) was used. In this method, two concepts of the ideal solution and anti-ideal solution have been used. The concept of the ideal solution is the best in every way, which is generally not the case in practice, and it tries to get closer to it. In order to select an option to resemble an ideal and counter-ideal solution, the distance between that option and the ideal and counter-ideal solution is measured. The options are then evaluated and ranked based on the ratio of the distance from the counter-ideal solution to the total distance from the ideal and counter-ideal solution.

The most important factor in the study of flood risk areas in the city is identifying and prioritizing effective criteria in creating floods and the study of watersheds in the city, each of which is of varying degrees of importance. The results of the influential factors in flood occurrence can be expressed in the following order; the height criterion is one of the cases with an inverse relationship with the emergence and formation of the flood. The height of Shiraz varies from 1449 meters to 2284 meters. A very steep slope is observed in the northeastern part of Shiraz (Abivardi region towards Chogiah to the Quran Gate), and most of the city is developed in the plains and lower elevations. Most slope directions in Shiraz city are related to the eastern heights of the city (Saadi region 3, Daneshgahian dormitory, Haft Tanan for north and northwest slopes, Shiraz Marvdasht highway, beautiful Quran city gate for west and northwest slopes) (Region 1, Jomhory, Kuhsar Mehdi Abivardi West and Northwest and Chogiah North) (District 6 Mahmoudieh Mansourabad North and West of Drak Heights to the north and northwest slope) (Region 11 Qanat Pisheh North) The western helpers of the North Talaieh Highway (District 10 of Arian Town, Anjireh Town, is the northern and northwestern slopes of Drak). The highest drainage density is related to areas 1 and 6 of Shiraz city. The main geological formations of Shiraz plain with high and low-level sediments are dolomite, limestone with layers of sandstone or marl, limestone, and marl. The lower the permeability of these formations, the higher the score on the map. The final map of the flood-prone areas of Shiraz was classified into five very low, low, medium, high, and very high-risk classes. The results show that areas 2, 3, 11, 7, and 9 are most vulnerable to floods. Also, 2754 hectares of Shiraz city are in the very high-risk category, 6076 hectares are in the high-risk zone, 17390 hectares are in the medium-risk .zone, 13418 hectares are in the low-risk zone, and 6658 hectares are in the very low-risk zone.

Thirteen effective parameters in flood occurrence were used to identify the flood hotspots in Shiraz. Then, using the TOPSIS-GIS approach combination, ten regions were examined. The TOPSIS integrated model is based on the ideal extraction of positive and negative points and determining the distance of each criterion in order to determine the best spatial option in terms of flood hazards. Using geographic information system (GIS) and ArcMap 10.3 software, the layers were prepared, and the best spatial options in terms of flood hazards were determined from the TOPSIS model. Several phenomena are commonly involved in urban flooding, including the limited transmission capacity of urban canals and rivers, drainage and sewage, and decades of urban development without updating the drainage infrastructure of flood-prone areas of Shiraz. Quran, Shiraz Marvdasht Road, Ayatollah Rabbani Boulevard, Haftannan, Chehelmogham Boulevard, Haftannan Boulevard, Saadi Town, Students' Alley, Saadi Gharb, Fazilat Tunnel, Delgsha Boulevard (underpasses), Fig neighborhood, along dry and coastal river crossings Slope, direction of slope, increase of constructions in the river area, increase of impermeable surfaces and building density), District 11 of Shiraz city: Fazilat tunnel, Parvaz town, Rasoul Azam boulevard, Persepolis boulevard, Sibouyeh town, police force town, Shahid Beheshti town, Talab town, buildings located in the foothills (main factors of slope flood, low groundwater depth, constructions in the river area, and inadequacy of urban sewage disposal systems), District 7: Sharifabad, Sahlabad, 20 meters from the sewer, town Imam Hossein, Mehregan town, Kushkak neighborhood, Nasrabad neighborhood and Abu Nasr (main causes of flood: low groundwater depth and inadequacy of urban sewage disposal systems), District 8 of Shiraz city: Isfahan Gate, Takhti St., Keshavarz St., Teymouri St., Imam Ali Bridge, Ali Bin Hamzeh Bridge (main factors Flood due to slope and inadequacy of urban sewage disposal systems), Region 9: Hojjatabad, Bargh, Darati, Modares, Mehdi, Sultanabad, Rezvan and Fajrnegar towns (main causes of increased floods in the area of ​​Chenar Rahdar road), Region 1: Abivardi neighborhood, Mehdi mountain, next to the passages of the martyrs Emdadgar, Fajr, Bahman, reporter (main causes of slope flood and river flood), region 5: Golha town and Nawab Safavid martyr (main factors of flood low groundwater depth, and Inadequacy of municipal sewage disposal systems) Region 2: Glasswork, pottery (Abuzar), tannery, Zahra alley, Fazlabad, Bahar town (Pai Kata), Vali Asr and Sibouyeh boulevard (main causes of floods: low groundwater depth, and lack of Suitability of municipal wastewater disposal systems).

Changing the use of urban green cover over time can create various environmental hazards for the citizens of a city. Due to the importance of the subject, the present study intends to investigate the temporal and spatial changes of green cover in areas 1 and 6 of Shiraz metropolis using Landsat satellite images during five decades (1972 to 2019). For this purpose, after performing radiometric and atmospheric corrections, maps resulting from plant indices including NDVI, SAVI, OSAVI as well as the maximum likelihood algorithm were prepared in ENVI5 software and classified and evaluated in Spatial Information System (GIS). The results of this study showed that the area of the green cover in region 1 has decreased in terms of hectares in NDVI, SAVI, OSAVI indices respectively and also in the maximum likelihood algorithm has decreased from 1394 to 428, from 789 to 421, from 815 to 419, from 1402 to 439, respectively and in region 6 was decreased from 1374 to 858 (NDVI), from 1160 to 862 (SAVI), from 1149 to 884 hectares (OSAVI) and in the algorithm, the maximum likelihood of similarity has decreased from 1393 to 855 hectares. Investigation of threshold values of plant indices to identify urban green cover showed that the range of threshold values in NDVI was variable from 0.2 to 0.3, in SAVI was variable from 0.44 to 0.47 and in OSAVI was variable from 0.34 to 0.36 and using Pearson test in SPSS software, correlation coefficient values between NDVI, SAVI, OSAVI, maximum likelihood algorithm and the studied years were significant at the 1% level. The results of this test also indicated that there was no significant difference between the results of these methods in this study. This reduction of green cover is considered a serious danger for the citizens of Shiraz

Today, population growth and the consequent physical development of cities have led to a shortage of urban infrastructure and services in new urban areas. The purpose of the present study was to determine the areas deprived of medical services in zone 10, Shiraz municipal, Iran, and to find the optimal locations for use.

The descriptive study was conducted with a citizen-centered approach. The required information was also obtained from the detailed plan of the region. By designing the questionnaire, experts in the field of health and urban planning were asked to rate 3 criteria and 10 sub-criteria, and determine the preference of each criterion. For optimal site selection, hierarchical analysis and geographic information system (GIS) were used.

The high concentration of health care use in the center of Shiraz City had caused the northwestern and southeastern regions to face a shortage of medical use. After reviewing the criteria and sub-criteria, the best spatial locations were proposed for the construction of the hospital.

The distribution of urban services, especially medical services, must be such that spatial justice is respected. Barren and endowment lands, proximity to first-class passages and densely populated areas, have been suggested as top locations for hospitals.

Morphometric analysis is considered as quantitative evaluation of geometric features landforms and landscape. In the study of basin tectonic features, the use of some morphometric parameters can provide very substantial information. Gavkoshak Basin with an area of 46.73 km2 is located in Zagros simply folded belt. The objective of this research is to use the morphometric indices such as hypsometric integral, basin shape, stream length-gradient, asymmetric factor, and the valley width/height ratio. As a result, these indices are converted to the tectonic activity index. This index can be used to assess the overall performance of the region's tectonic activity.Morphometric indices of area are studied by dividing this area into 43 sub-basins, using the Digital-Elevation Model (DEM) and Geographic Information System) GIS). Morphotectonics index method with the use of geographic information systems provide procedures and a powerful tool for estimating tectonic activity in the region. It should be borne in mind that the results of these indices can show different values in different sectors. By examining the relative index of tectonic activity, the basin in this research is divided into two parts namely active (25.6% of the watershed) and semi-active (74.4 % of the watershed). Through statistical analysis, the area under investigation includes four clusters: cluster one with 91. 83% similarity, cluster two with 95.19% similarity, cluster three with 96.18% similarity, and cluster four with 91.09% similarity. In this way, homogeneous regions were determined based on clustering algorithm ward. The active tectonic basin in this research can be studied in another research project, using other morphometric parameters.

Employing recent technological advances in surveying and mapping soil salinity is a step forward in controlling saline soils. The aim of this study was to map the topsoil salinity, the depth of 0-5 cm, using different methods within the environmental context of the area around Tashk & Bakhtegan Lake, with the area of 8062 ha, that in this region soil salinity appears to be a major threat to agriculture production. We used three different methods to produce soil salinity map and then compared the results with the soil salinity data that were measured on the ground. A set of 143 soil salinity sample, electrical conductivity of the water extracted from saturated past (ECe), was systematically sampled on a 750-m grid and was used to assess two mapping methods; regression models (RM) and ordinary kriging (OK). As a third method, supervised classification (Scl) of LISS-III sensor satellite images was employed. We used linear, power and exponential regression models for estimating of salinity values. In these regression models, digital numbers of the satellite images were set as independent variables and ECe values as dependent variable. In order to provide a prediction map of the soil, the salinity data were interpolated using the ordinary kriging method. In case of the satellite images, we classified the training pixels with maximum likelihood algorithm and then the land cover map was prepared. Our results revealed that regression models could not appropriately predict the salinity values and the vegetation indexes had poor correlation with the topsoil salinity values. The salinity percentages obtained from OK and Scl were nearly similar where the salinity was high (≥16dS/m), but differed in other salinity classes. Therefore, in the supervised classification of LISS-III sensor data the bare soil surfaces with high salinity (≥16dS/m) were successfully identified and separated from the rest of the soils. The regression model estimated 100 % of the study area as saline soil. The kriging method predicted 87.6 % of the area to be classified as saline soils (> 4dS/m), while supervised classification predicted that to be 62.5 %. Each of these methods has constrains. Therefore, we recommend the integration of these methods for estimating of soil salinity.

It is crucial to study the widespread growth of saline soils in Iran and having significantimpacts on crop yields. In order to approach the awareness of spatial variability of thisenvironmental phenomenon, we need several samples depending on the expansion of these soils. However, it requires a lot of time and high cost. Therefore, we probably be able to provide proper information on the area with the help of different science and technology considering financial difficulties and time limitations. According to this crisis, in part of Arsanjan plain of Fars Province (8062 h), vicinity of Tashk and Bakhtegan lake, soil salinity maps obtained from Kriging method and then evaluated. Analysis of geostatistics with salinity data was expressive that spatial dependency is moderate. MBE value of estimation of the salinity and sodicity data indicated overestimating in both two Kriging methods, After cross validation, RMSE for ordinary kriging in depth of 0-5 and 0-50 cm was 27.65 and 17.56 for salinity and 12.83 and 12.34 for sodicity data. Estimation of salinity using of digital numbers of LISS III sensor (as secondary data) in cokriging method, had not positive effect on the estimation. The evaluation of the obtained maps indicated salinity values were very high close to lake and decreased one with distance, in center of the plain and increased in agricultural lands because of mismanagement of water resources. In the north of the area there are crops such as barley, alfalfa and wheat which planted with irrigation agriculture. therefore it seems, using unfavorable water, makes the soil saline and rich in sodium.

In this research the data of LISS-IIIsensor used for mapping saline soils on the around of Tashk and Bakhtegan lake, Fars Province. After the corrections of the imagery, the training and control pixels selected and the soil samples (depth of 5 cm) prepaired. Then pixels of the imagery classified in different approaches by maximum likelihood algorithm. Analysis of spectral graphs of classes indicated the most reflectance of saline soils was in visible spectral. The highest of correlation coefficient between salinity values and digital numbers of bands (0.45) observed in band 2. Investigation of feature space graphs indicated, almost single clusters formed in all of the classes except in low and moderate saline soils. The white salt crusts lied in the highest portion of soil line and black salt crusts in lower parts. The roughness and moisture were the main factors in reflectance decreasing of salt crusts in studied region. In non-saline soils the roughness produced by large clods in ploughed areas was the effective factor of reflectance decreasing. Presence of plant cover and residual of the straw caused error in identifying of saline soils. Results of classification of different approaches indicated the highest accuracy of procedure, user, overall and kappa index was observed in integration of all the bands. In all of the approaches, soils with low and moderate salinity had low accuracy. The produced map of LISS-III sensor indicated salinity values above of 16 dS/m there were on the around soils of lake and decreased one with distance, in center of the plain and increased in agriculture lands again.