Mohammad Abiyat; Saeid Amanpour; Mahmud Abiyat; Majedeh Abiyat
Abstract
Satellite images have a high capability for estimating the area under agricultural crops. The aim of this study was to identify 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 ...
Read More
Satellite images have a high capability for estimating the area under agricultural crops. The aim of this study was to identify 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 approach, crops in different growing seasons and according to their calendar, a cropping pattern map was drawn. In order to evaluate the accuracy of the results, the generated maps with reference data were examined. Agricultural Jihad statistics of Khuzestan were also used. The results showed that Kappa coefficient and overall accuracy were 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, had an error of 12.6, 16.4, 8.7 and 6.6%, respectively and in the Support Vector Machine had an error of 10.1, 8.3, 5.1 and 7.2%, respectively. However, using the NDVI index as the best approach for estimating the cultivation area in this region, in comparison with the statistics of Agricultural Jihad, has 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, According to their phenological stage.