Annisa Nur Rasyidah, Ike Sari Astuti, Ita Carolita
Analysis of deforestation using remote sensing satellite imagery is carried out for monitoring and as an effort to reduce deforestation rates to maintain the ecological function of the forest. One of the causes of deforestation are land clearing and land conversion. Based on BPS data in 2020th, the forest area is decreasing and the area of oil palm is increasing every year. This research was conducted in Tanah Bumbu Regency, the data used were Landsat 7 ETM+ and Landsat 8 OLI/TIRS images. The method used is a guided classification with Support Vector Machine (SVM). Analysis of deforestation uses the results of image processing classification in time series by taking into account the reduction of forest that occurs every year. Based on the results of image classification in 2010th using SVM, forest has an area of 2161.1 km2 and oil palm is 1063.6 km2. Both of these land uses underwent changes in 2020th with forest area experiencing a reduction of 1493.42 km2 and oil palm having an additional area of 865.62 km2. The classification results have an overall accuracy value of above 80% and a kappa accuracy of 78%. The results of the analysis show that there is a relationship between the incidence of deforestation and the expansion of oil palm land. Based on the results of the regression analysis, R2 = 0.95 with a change value of 935.42 km2. © Published under licence by IOP Publishing Ltd.
Malang State University, Jl. Semarang No. 5, East Java, Malang, Indonesia; Remote Sensing Application Center, LAPAN, Jl. Kalisari No.08, Pekayon, Pasar Rebo, DKI Jakarta, East Jakarta, Indonesia
