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DOI:10.22059/jci.2021.322146.2537
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Estimation of Agricultural Cultivation Area by Landsat 8 Satellite Images (Case study: Shushtar Province)
Mohammad Abiyat1*, Saeid Amanpour2, Mahmud Abiyat3, Majedeh Abiyat3
1. Former M.Sc. Student, Department of Environmental Sciences, Islamic Azad University, Tehran (Khuzestan) Science and Research Branch, Ahvaz, Iran.
2.Associate Professor, Department of Geography and Urban Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
3. Former M.Sc. Student, Department of Geography and Urban Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
Received: April 16, 2021 Accepted: August 18, 2021 Abstract
Satellite images have a high capability to estimate the area under agricultural crops. This study aims at identifying the area under dominant crops such as in Shushtar Province, using Landsat 8 satellite images during the growing season during 2019. With Maximum Probability technique and Support Vector Machine in the first approach and using NDVI index in the second one, crops in different growing seasons and according to their calendar, a cropping pattern map has been drawn. In order to evaluate the results’ accuracy, the generated maps have been examined with the reference data.
Agricultural Jihad statistics of Khuzestan are also used with the results showing that Kappa coefficient and overall accuracy are calculated as 90% and 80% in the Maximum Probability technique, 92% and 90% in the Support Vector Machine, and 95% and 93% in the NDVI, respectively. Based on the results, the cultivation area of wheat, barley, rice, and corn, in the Maximum Probability technique, in comparison with the statistics of Agricultural Jihad, has had an error of 12.6%, 16.4%, 8.7%, and 6.6%, respectively and in case of the Support Vector Machine, an error of 10.1%, 8.3%, 5.1%, and 7.2%, respectively. However, using the NDVI index as the best approach to estimate the cultivation area in this region, in comparison with the statistics of Agricultural Jihad, has had an error of 2.4%, 1.5%, 4.3%, and 4.6%, respectively, which indicates the high capability of vegetation indices to estimate the Cultivation Area, in accordance with their phenological stage.
Keywords: Classification, cultivation pattern, NDVI, satellite imagery, Shushtar.
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