Zoning of natural resources of Iran using indicators and criteria that can be extracted from satellite images on desert and semi-desert areas

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

The main objective of the present study is to delineate all-natural resources of Iran with the priority of desert and semi-desert areas using indicators and criteria extracted from remote sensing data and new satellite image classification techniques. Accordingly, desert, semi-desert, and salinity areas of Iran in conjunction with other natural resources areas (such as forests, rangelands, water bodies, and farmlands) were studied using time-series MODIS satellite images and different indices and parameters such as Albedo, NDVI, and surface temperature during day and night along with the temperature difference between day and night. Here, unlike the classical classification methods, based on using one-single satellite image and features such as vegetation density or surface temperature, the behavior of different natural resources over time, extracted from satellite images, was analyzed. Accordingly, the temporal behavior of each of the mentioned natural resource areas during 2019 was studied and analyzed using the remote sensing criteria. The basic object classification method was used to classify the country using the mentioned indicators using the least distance technique based on fuzzy logic. Based on results, about 41.2%, 14.8%, and 3.9% of Iran (totally about 60% of Iran) are classified as desert, semi-desert, and salty areas, respectively. By considering the percentage of rocky mountainous areas (11.3%), about 71.2% of Iran has no biological conditions (unsuitable for agricultural activities). As expected, desert and semi-desert areas are concentrated in central, eastern, southeastern, and southern regions of Iran, and no signs of such areas are found in the northern, northwestern, and western of the country.

Language:
Persian
Published:
Iranian Journal of Range and Desert Research, Volume:28 Issue: 4, 2022
Pages:
652 to 671
https://magiran.com/p2397718  
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