Ainia Walidaroyani
ABSTRACT
The latest land cover information in the form of maps resulting from image classification can be obtained through remote sensing techniques that utilize satellite imagery, such as Landsat 8 and Sentinel-2. However, no study compares the two satellite images with high classification algorithm accuracy. The previous literature describes several techniques that can be used to classify land cover, but there has been no specific use of similar techniques in the Ir. Sutami. In this study, the author uses a classification technique using the CART (Classification and Regression Tree) algorithm which can present the classification results as a simple tree structure to make the classification process easier and closer. The results of processing Landsat 8 and Sentinel-2 satellite imagery in 2020 show accuracy test results at 91% and 97% for vegetation classes, water bodies, built land, open land, and rice fields. We hope this research can help in providing information to cover the land in the area around Ir. Sutami to avoid the negative impacts of future land-use changes.
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