Mapping Forest Condition Based on Time Series Tasseled Cap Transformation (Case Study: Leuweung Sancang Nature Reserve, West Java, Indonesia)

Monitoring forest ecosystem is crucial steps for sustainable management. Development of various remote sensing sensors and algorithms for detecting forest change has increase the capability of multitemporal forest condition analysis. The Leuweung Sancang Nature Reserve (LSNR) is home for various endemic flora and fauna in Western Java. Forest condition information for this reserve is still limited, and various anthropogenic related development and activities has been increasing in recent years. This study aims to assess forest condition changes in LSNR by applying a multitemporal analysis using the Disturbance Index (DI), derived from the Tasseled Cap Transformation of Landsat sensors. We analyzed forest conditions within the LSNR borders from 1991 to 2023. Based on the DI for each year, the forest disturbance in LSNR have fluctuated, although generally decrease throughout the year. The change analysis mapped three forest condition, disturbance, regrowth, and stable from 1991 - 2023. We compared the ∆DI of 2000 – 2023 in order to match the analysis with the Hansen Global Forest Change dataset. Disagreement metrices resulted in 19.8% quantity disagreement and 81.15% allocation disagreement. The low quantity disagreement indicate that DI manage to produce similar result in term of class proportion quantity, although resulted in higher miss-classification.