Forest Disturbances Detection by Sentinel-2 Imagery in Isangi Territory, Democratic Republic of Congo

In recent decades, there has been a significant transformation in global forests, characterized by widespread changes and disruptions, particularly in primary forest areas. The Isangi Territory in “the Democratic Republic of Congo” is one such deforestation hotspot, experiencing rapid forest disturbances. Various studies and government organizations have implemented systems that utilize satellite imagery to provide regular alerts on forest disturbances. However, the effectiveness of optical-based near-real-time monitoring methods is hindered by cloud cover in the humid tropics. To overcome these limitations, satellite missions that revisit an area more frequently have a higher chance of acquiring cloud-free images. The Sentinel-2 satellites presents a valuable opportunity for comprehensive global forest monitoring due to their high spatial resolution of 10 m and the frequent revisit time of 5 days. This study employs a maximum likelihood classification algorithm to map deforestation using Sentinel-2 satellite images from 2017 and 2022. The analysis is conducted at a spatial resolution of 10 meters, which enables enhanced disturbance detection in the tropical forest. The findings facilitate rapid change detection of forest disturbances, such as agricultural expansion and selective logging, within the study area. Sentinel-2 is hence a suitable source of satellite data for monitoring forest degradation in addition to deforestation.