Using Sentinel-2A to Identify the Change in Dry Marginal Agricultural Land Occupation

Abstract

Dry marginal agricultural land (DryMAL) potentially use as an alternative resource for crop production. DryMAL de- fined as land having low natural fertility due to its intrinsic properties and forming environmental factors. This study uses Sentinel-2A imagery to map the spatial extent, compare the result of the classification, and identify the change in DryMAL occupation. The area of study (461.9 km 2 ) is part of Situbondo Regency and is located at the eastern part of East Java, In- donesia. Sentinel-2A image captured in dry-season of 2018 use for this study. Then, supervised image classification using a maximum likelihood algorithm use for image treatment and processing. Furthermore, 450 ground control points for training areas collected during the field surveys. Five bands use in the classification process. The maps produced from the classification process were then compared to the land-use map from the year 2000. The change in DryMAL occupation from 2000 to 2018 was calculated by comparing the classified and land-use map. Supervised classification yielded an overall accuracy of 95.8% and a kappa accuracy of 93.2%. The classification produced six (6) classes of land use: (1) forest, (2) pavement or built-up area, (3) irrigated paddy field, (4) non-irrigated rural area, (5) dry marginal land and (6) water body. Globally, during the last two decades, regional development led by the Regency occupied more DryMAL area for developing plantation. The effort reduces the amount of non-irrigated and converting to the plantation, pavement areas, and irrigated paddy-field.