Identifying suitable and optimal areas for camouflage of arsenals is very important. The purpose of this study is to investigate and select the optimal and suitable places for camouflage of arsenals in the country using AHP model and mathematical analysis in ARC GIS environment. Locating is a process through which the best place for an activity can be determined based on the conditions and according to the available resources and facilities. Accordingly, in this study, first the effective factors in locating the ammunition slot are examined and the map of each of the effective factors in locating the arsenal such as slope map, slope direction map, Altitude map, Access road map, Distance from big cities map, Distance from medium cities map, Distance from small towns Map, Distance from villages map, Distance from faults map and distance from water level map were prepared in ARC GIS environment and the importance coefficients of criteria and sub-criteria were obtained using Analytic Hierarchy Process (AHP) and Expert Choice software. Then, these coefficients were applied in the layers related to each parameter through a linear weight combination and suitable places for selecting the arsenal were identified with a range of values. Manuscript profile

Preparation of land use maps using traditional methods, in addition to spending a lot of time and money, is mainly about efficiency and it does not have the necessary accuracy. Today, satellite imagery and remote sensing techniques have a wide range of applications in all sectors, including agriculture, natural resources, and land use mapping, due to the provision of timely data and high analysis capabilities, variety of shapes, digitality, and the possibility of processing. Satellite imagery Landsat 8 for August 2020 was used, which after making the necessary corrections in the pre-processing stage, action experimentation or fusion of the desired image using the panchromatic band and spatial resolution of the image was increased from 30 meters to 15 meters. In the next step, four different classification methods, including backup vector machine, maximum probability, Mahalanoob distance, and minimum mean distance were compared. The results showed that the classification method of backup vector machine with average overall coefficients and kappa of 100 and 1, respectively, has higher accuracy than other methods. Priority accuracy of classification methods is in the form of backup vector machine, maximum probability, Mahalanoob distance, and minimum distance from the mean, respectively. Finally, by assessing the accuracy using user accuracy, producer accuracy, overall accuracy, kappa coefficient and error matrix, land use map was prepared in three separate classes. Manuscript profile