Monitoring Land Cover Changes in Tehran City over 5 years (2018 to 2022) using Remote Sensing based Spatial Information

Rapid economic growth has increased the speed of resource changes and many of these changes have rapid and harmful effects Natural environment such as agriculture, forest, water resources, value Cultural things such as historical landscape and health Humans have put Land use changes directly It changes the resources of the earth, which affects the temperature and humidity causes changes in the climate and weather of the region as well It reduces cultivated areas [1]. Considering that one of the main prerequisites for the optimal use of land, obtaining information One of the patterns of land use over time is map design. Related specializations are one of the most important goals in management it is considered natural resource [2]. In recent years, preparing land use maps by digital classification of remote sensing data have been adverted as appropriate alternative for using this type of maps. Remote sensing is a modern and useful technique in updating land use maps and detecting new changes. In this research ArcGIS pro used for classification that is one of the most accurate and updated software for remote sensing’s process for detecting 4 main type of classes in Tehran city in IRAN. standard accuracy in satellite image processing is important criteria in this study with standard kappa coefficient accuracy, and overall accuracy of data calculated for each maps, by considering 4 essential classes in a major city and converted to maps of changes in linear regression concluded that build-up class have a significant slope increase 3422/3 (hectares), plant class is improving during the study period as 2821/71 (hectares) but these increment are inhomogeneous, water class has sharp drop as 443.52 (hectares), Then the most of decrement is for the barren area which named soil class as 5800.48 (hectares). Part of accuracy in this research depends on severity of the numbers of test samples which given for classification that are more than5000 pixels to assessment reliable results. According to the standards of kappa coefficient that provided in USGS earth data site all off maps are acceptable.