Mapping land cover and forest density in Zagros forests of Khuzestan province in Iran: A study based on Sentinel-2, Google Earth and field data |
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| Institution: | 1. Forest Research Division, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran;2. Khuzestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khuzestan, Iran;1. Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran;2. National Cartographic Center (NCC), Tehran, Iran;3. Department of Remote Sensing and GIS, Faculty of Geographical Sciences, Kharazmi University, Tehran, Iran;4. Department of Remote Sensing and GIS, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran;1. College of Resources and Environment, Jilin Agricultural University, 130118 Changchun, China;2. Key Laboratory of Soil Resource Sustainable Utilization for Jilin Province Commodity Grain Bases, Jilin Agricultural University, 130118 Changchun, China;3. Key Laboratory of Straw Comprehensive Utilization and Black Soil Conservation, Ministry of Education, 130118 Changchun, China;1. Global Change Research Institute of the Czech Academy of Sciences, Bělidla 4a, 60300 Brno, Czech Republic;2. IFER – Institute of Forest Ecosystem Research, ?s.armády 655, 254 01 Jílové u Prahy, Czech Republic;3. Masaryk University, Department of Geography, Faculty of Science, Kotlá?ská 267/2, 611 37 Brno, Czech Republic |
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| Abstract: | Zagros forests in western Iran have widely been destroyed because of various reasons. This study was performed to provide the land cover and forest density maps in Zagros forests of Khuzestan province using Sentinel-2, Google Earth and field data. The forest boundary in Khuzestan province was digitized in Google Earth. Sentinel-2 satellite images were provided for the study area. One 1:25000 index sheet of Iranian Mapping Organization (IMO) was selected as pilot area in the province. Sentinel-2 image of the pilot area was classified using different supervised classification algorithms to select the best algorithm for land cover mapping in Khuzestan province. In addition, to evaluate the accuracy of Google Earth data, field sampling was performed using random plots in different land covers. Field data of forest plots were applied to investigate tree canopy cover percent (forest density), as well. Classification of Sentinel-2 image in Zagros area of Khuzestan province was done using the best algorithm and the land cover was obtained. The forest density map was also obtained using a linear regression model between tree canopy cover percent (obtained from field plots) and normalized difference vegetation index (NDVI) (obtained from NDVI map). Finally, the accuracy of land cover map was assessed by some square plots on Google Earth. Results demonstrated that support vector machine (SVM) algorithm had the highest accuracy for land cover mapping. Results also showed that Google Earth images had a good accuracy in the Zagros forests of Khuzestan province. Results demonstrated that NDVI has been a good predicator to estimate tree canopy cover in the study area. Based on results, an area of 443,091.22 ha is covered by Zagros forests in Khuzestan province. Results of accuracy assessment of the land cover map showed the good accuracy of this map in Khuzestan province (overall accuracy: 91% and kappa index: 0.83). For optimum management of Zagros forests, it is suggested that the land cover and forest density mapping will be performed using SVM algorithm, NDVI, and Sentinel-2 satellite images in Zagros forests of Khuzestan province in the certain periods. |
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