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This study is aimed at identifying of depopulated rural settlements over a quarter century since 1365 (1986) by 1390 (2011) in Isfahan province and representing a geographically interpretation of the phenomena, using statistical methods and spatial analysis in the geographic information system environment. To do this, at first, layers of the spatial distribution of settled villages of 1365 and identified depopulated ones over the two and a half decades period of the study have based on the detailed reports of public censuses’ results of Iran statistical center identified and prepared in ArcGIS environment. Afterwards, the rural settlements exodus analyzed based on the prepared, corrected and classified natural parameter layers of altitude, slope, aspect, temperature, land types and distance from wells and springs, spatially. Definition and calculation of two spatio-statistical indicatorsdad been the basis of analysis; “the settled villages density at the beginning year of 1365” and “relative percent of depopulated villages over the study period with respect to the total beginning settled ones”. The indicators calculated for each of the layers’ zones using the “zonal mean statistic” function from the spatial analyst tool of ArcGIS and analyzed statistically by correlation and Chi-Square tests. Results revealed that there is a significant relationship between exoduses and natural factors of slope, land types, altitude and distance from wells respectively. While that was not true for aspect parameter. The influence knowhow of natural factors on rural exodus, helps the landuse planning projects to more consider them and ensure the more stability of rural settlements agains the more exodus in the future.

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Studying the spatial pattern of thermal islands with satellite imagery is one of the major challenges in the urban development process of developing countries. If this growth is dispersed and unplanned, many problems and problems will arise in the management and urban planning process.  The purpose of this study is to identify the distribution and temperature difference of different regions of Qom city with respect to its suburbs in order to discover thermal islands and to map its temperature. In this study, using remote sensing and Landslide and OLI and TIRS satellite imagery during six consecutive months from January 1979 to June 1398 cold months to hot months, we investigate the LST surface heat distribution in Qom and its lands. Its margin was scattered in relation to the use and NDVI vegetation index factor. During the research, it is suggested that the thermal islands in Qom be prevented by preventing the destruction of agricultural fields and the construction of urban parks in the desert and open urban areas.
 
 

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Abstract:
Studies show that landing area crops and crop growth curves for countries have provided them with several million new jobs and billions of dollars in gross income, with more than 50% of them being farmers. Due to the growth curve of crops in 8 plots of land applied to Landsat 8 images, alfalfa (105) had the best, most lively and least stressful vegetation, and alfalfa (303) had the least vegetation at peak vegetation growth and also The highest coefficient of variation was in its growth curve. According to the results obtained from the crop area of  NDVI image, we found that wheat (304) had the highest difference and wheat (108) had the least difference. In the year 98, the total area of these 8 plots is 82.775 hectares and according to the results of the company was 89 hectares. In other words, the area calculated from the NDVI image in 1398 was only about 7% lower.

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this paper is to compare the PPK schemes with RTK help of GCPs in the images for the second time with the help of GCPs in the images is to map the map and the second time with the help of GCPs the map is prepared and without the help of GCPs the map is prepared in this research different types of effective geometric errors in spatial accuracy of agricultural land cadastre map were investigated the accuracy of check points geometric displacement of parts and error of sampling stations in the area were calculated . considering the geometric errors obtained and using the geometric mean of these errors we achieve a comprehensive geometric error for converting UAV images into cadastre map . due to the geometrical errors and using the geometric mean of these errors, we achieve a comprehensive geometric error for converting the attitude of UAV to execution map of cadastre. in this study, due to the examination of points of checks, geometric displacement station error in the region we obtained 0.011746, 0.0815715, 0.054557, which can be achieved due to geometrical errors and using the geometric mean of these errors we achieve a total geometrical error of 0.098835 m for converting the attitude of UAV to cadastre map. This amount of error is suitable due to the direction of the mapping organization to provide maps of 1: 1000