Large-scale wall-to-wall mapping of bark beetle damage and forest practices using the distance red swir index and operational harvester data

• Published in: Ecological indicators Vol. 162; p. 112036
• Main Authors: Persson, Henrik J., Kärvemo, Simon, Lindberg, Eva, Huo, Langning
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-05-2024; Elsevier
• Subjects: Bark beetles; Disturbance; Ecology; Ekologi; Forest Science; Harvester; Ips typographus; Mapping; Picea abies; Sentinel; Skogsvetenskap; Sentinel; Disturbance; Bark beetles; Mapping; Picea abies; Ips typographus; Harvester
• ISSN: 1470-160X; 1872-7034; 1872-7034
• DOI: 10.1016/j.ecolind.2024.112036

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•Developed a new ΔDRS vegetation index based on Sentinel-2 images.•ΔDRS was useful to detect spruce bark beetle attacked forest.•ΔDRS was accurate in classifying clear-cut forest.•Reference data from operational harvesters•Method feasible for large-scale operational use
Satellite-based inventories of bark beetle attacks are increasingly used for detecting and monitoring infested forest at the landscape scale. The Normalized Distance Red & SWIR index is one of few indices that have shown higher accuracies than commonly used vegetation indices. In this study, the temporal changes of the distance red swir (ΔDRS) index were analyzed, validated and applied to multi-temporal Sentinel-2 images covering one tile of 110 x 110 km2. The main purpose was to assess the applicability of a new ΔDRS vegetation index to detect spruce forest after bark beetle (Ips typographus) attacks. Harvester data from a private forest company were used to validate the method. The normalized DRS index has previously been developed and tested at test site level, while this study explored and demonstrated the use of ΔDRS in an applied context on a larger scale. Water and chlorophyll induced changes and different disturbances were effectively identified across the landscape. A linear-discriminant analysis was used to classify 274 clusters as attacked and healthy forest, with an overall accuracy of 78%. The largest ΔDRS values in our study (>0.06) corresponded well to clear-cuts, and all 172 clear-cuts were correctly classified. We conclude that the ΔDRS index has a potential to map vegetation changes related to water and chlorophyll changes in the Scandinavian forests and that it can be useful to identify bark beetle-infested forest within 1 year after the attacks and clear-cuts.