Preliminary Study on the use of Sentinel-2A Image for Mapping of Dry Marginal Agricultural Land

Abstract

The availability of medium resolution satellite imagery (i.e. Sentinel-2A) provides the rapid, low-cost and more accurate mapping. This report presents the use of satellite imagery (Sentinel-2A) for mapping of marginal Agricultural Land in the eastern part of Situbondo Regency. The study area covers three (3) districts, i.e., Arjasa, Jangkar, and Asembagus. This study uses two methods of image classifications (i.e., unsupervised and supervised). Sentinel-2A images for dry seasons of 2018 use for this study. The dry season of this region usually occurs from April to November. Then, 450 ground control point for training areas collected during the fields surveys between June until Octobre 2019. This study also uses multi-band (i.e., 2,3,4,5 and 8A) of the sentinel 2a image. Image treatments use “ Multispect” and SNAP, two open-source image processing software. The procedures include image enhancement, registration, clipping, and classification. The classification consists of preprocessing,

processing and post-processing tasks. Then, classification results evaluated by confusion-matrix (overall and kappa accuracy). Furthermore, the thematic maps produce from both unsupervised and supervised classification are then compared to existing thematics maps and statistics data. The unsupervised method use iso-data algorithm and produce five (5) class of land uses, i.e., (1) forestry and plantation; (2) build-up area, (3) irrigated paddy field, (4) non-irrigated rural areas (ladang/tegalan). The unsupervised method did the overall accuracy = 79 % and kappa accuracy = 72%. The supervised methods use maximum-likelihood algorithms and produce six (6) class, i.e., (1) forestry - plantation; (2) urban or build area, (3) irrigated paddy field, (4) non-irrigated rural areas, (5) dry-marginal land and (6) water body. Supervised method provide overall accuracy = 95,8% and kappa accuracy = 93,2%. The result shows the potential use of Sentinel 2A to map dry-marginal agricultural land in the study area.