Abstract
This research presents the methodology of map** a situation of the natural-landscape resources of Khuzestan province in Iran using time-varying space data according to seasonal changes of the indicators of SAVI and LST. The novelty of this research is the combined use of GIS techniques, optical and thermal remote sensing for map** the situation of the natural-landscape resources aimed at territorial planning. In this research, a classification was carried out for the study area based on the potential of the natural-landscape resources. The Landsat 7 and 8 materials from the periods of 2011–2013 and 2017–2019 were used to perform this research using ERDAS Imagine, ENVI, ArcGIS, and Priznak software. Variations of LST and SAVI were analyzed for 10 seasons of year from April to September. The results showed that both increasing the area of bare soils (wasteland) and residential areas and decreasing the extent of the water resources, forests, and rangeland in Khuzestan province have caused the surface temperature to rise over a period of 9 years. Whereas, matching of the Entisols and Inceptisols with areas having high natural resource potential in Khuzestan province was indicated by the results of this study. And also, the Badlands, Rock-outcrops, and Dunelands are the areas with low natural resource potential. It has been shown that integral indicator of the situation of the natural-landscape resources that calculated using the materials of multispectral space imagery is a stable indicator and criterion for land assessing in terms of their suitability for agricultural use. The results of this study can be used to provide a territorial management and planning in accordance with the goals of land use planning and sustainable development, by potential assessment and map** a status of the natural-landscape resources.
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The authors are grateful to the United States Geological Survey (USGS) for providing satellite data.
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Sajad, Z., Mostafa, K. The natural resources potential assessing aimed at territorial planning using time-varying space data of vegetation index and LST. Environ Monit Assess 192, 503 (2020). https://doi.org/10.1007/s10661-020-08476-y
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DOI: https://doi.org/10.1007/s10661-020-08476-y