A Sentinel-2 based multi-temporal monitoring framework for wind and bark beetle detection and damage mapping

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.3390/rs14236105. This is version 1 of this Preprint.

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Authors

Anna Candotti, Michaela De Giglio, Marco Dubbini, Enrico Tomelleri

Abstract

The occurrence of extreme windstorms and increasing heat and drought events induced by climate change leads to coniferous forests showing severe damage and stress and making trees more vulnerable to spruce bark beetle infestations. The combination of abiotic and biotic disturbances in forests can cause drastic environmental and economic losses. The first step for containing such damage is the establishment of a monitoring framework for early detection of vulnerable plots and distinguishing the cause of forest damage at the scale from management unit to region. For developing and evaluating the functionality of such a monitoring framework, we first selected an area of interest affected by wind throw damages and bark beetles at the border between Italy and Austria in the Friulian Dolomites, Carnic and Julian Alps and the Carinthian Gailtal. Secondly, we implemented a framework for time-series analysis with open access Sentinel-2 data over four years (2017-2020) by quantifying single band sensitivity to disturbances. Additionally, we enhanced the framework by deploying vegetation indices, for monitoring spectral changes and performing supervised image classifications for change detection. A mean overall accuracy of 89% was achieved, thus Sentinel-2 imagery proved to be suitable for distinguishing stressed stands, bark beetle attacked canopies and wind fell patches. The advantages of our methodology are its global, large-scale and “FAIR” principles compliant applicability to monitor forest health, forest cover change and its usability to support the development of forest management strategies for dealing with massive bark beetle outbreaks.

DOI

https://doi.org/10.31223/X50072

Subjects

Life Sciences

Keywords

forests; spruce bark beetle; windstorms; drought; remote sensing; Sentinel-2; spectral signatures; vegetation indices; supervised image classification; forest cover change detection

Dates

Published: 2022-11-18 16:13

License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International

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