Comparative analysis of some winter crops area estimation using landsat-8 and sentinal-2 satellite imagery

Estimating crop area is a key factor for any crop monitoring and agricultural management system. Having annual information on crop acreage and production change is sufficient for agricultural decision makers and planners. The aim of this study is to monitor changes in cultivated areas and to estimate wheat crop area using satellite imagery with different spatial resolutions and time series normalize different vegetation index (NDVITs). The study is focusing on using accuracy assessment from maximum likelihood classification methods applied to multi-spatial resolution scenes (30, 20 and 10 meters) derived from Landsat8 and Sentinel-2 satellites. More specifically, NDVITs estimates from Landsat 30m, Sentinel-2 (20m), and (10m) spatial resolutions are compared to discriminate wheat crop. The study area is located in El-Minya governorate, Egypt. The results showed that the accuracy of using NDVITs data from different imageries showed higher accuracy than using one single date. The NDVITs estimate from the Sentinel-2(10m) has (81%) as an overall accuracy and (0.74) as Kappa coefficient where Sentinel-2(20m) NDVITs data has (69.38%) as an overall accuracy and (0.58) as Kappa coefficient. The lowest accuracy (64.38%) and Kappa coefficient (0.51) resulted from occurred with Landsta8 (NDVITs) data.