Publication: A Novel Approach for Rapid Detection of Forest Degradation and Diseases Through Anomaly Analysis of Sentinel-2 Spectral Data

26 April 2025

Traditional forest monitoring methods, including visual inspections, are limited and labor-intensive, often failing to detect problems in a timely manner, especially in remote or hard-to-reach forest areas. In contrast to traditional methods, Earth observation satellites are an effective tool for monitoring forests over large areas. They allow for real-time collection of detailed information on vegetation health, soil moisture, surface temperature, and other parameters.

In this work, SWIFTT partners from the Space Research Institute of Ukraine present a simple yet effective method for detecting forest degradation using freely available Sentinel-2 satellite data and an anomaly detection approach. The aim of this study was to develop an accessible and reliable technique that could match the performance of more complex algorithms while using minimal computational resources. The research focused on spectral bands with 10-20 m resolution and vegetation indices (NDVI, NDMI, GCI, PSSRa) to analyze forest damage in the Harz region. The method involved identifying anomalies in the spectral data relative to randomly selected reference points from healthy forest areas, which were verified with high-resolution imagery from Google Earth Pro. This method provides an efficient tool for monitoring forest health with minimal data requirements and computational effort, offering a promising solution for forest managers and conservationists worldwide.

Read the paper in the link below.