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Two-Phase Forest Damage Assessment with Sentinel-2 NDVI Double Differencing and UAV-Based Segmentation in the Sopron Mountains

Remote Sensing · 6 Mar 2026 · 10.3390/rs18050803

Abstract

Due to climate change, drought periods are becoming more frequent and more intense, posing substantial stress to Central European forest stands, especially climatically sensitive conifer forests. The early detection and accurate spatial delineation of forest damage are essential for supporting adaptive forest management decisions. This study presents a two-tier, multi-step forest damage assessment approach that combines Sentinel-2 satellite-based NDVI double-difference analysis with UAV-based high-resolution photogrammetric evaluation. In the first phase, potential damaged forest patches were identified in two sample areas of the Sopron Mountains using double-difference maps derived from monthly window NDVI maxima calculated from Sentinel-2 data. In the second phase, UAV surveys were carried out over the selected forest compartments, resulting in individual-tree-level canopy segmentation and object-based NDVI analysis. The photogrammetric point clouds were combined with ground points derived from airborne laser scanning to enable the accurate generation of canopy height models. The results confirmed that NDVI double-difference analysis is suitable for the spatial detection of both gradual drought-related damage and sudden disturbances—such as forest fire—even under sequences of drought and moderate years occurring in a sporadic pattern. The UAV-based analysis corroborated the satellite observations in detail and enabled an accurate inventory of damaged trees as well as the exploration of their spatial distribution. The proposed methodology provides an efficient, cost-effective, and operational tool for multi-scale monitoring of forest damage, contributing to the timely recognition of climate-change impacts and to the substantiation of targeted forest management interventions.

Plant phenotyping relevance

衛星・UAV画像、NDVI差分、樹冠セグメンテーションを用いて森林の個体レベル損傷を抽出する手法が研究の中心であるため。

abstractThis study presents a two-tier, multi-step forest damage assessment approach that combines Sentinel-2 satellite-based NDVI double-difference analysis with UAV-based high-resolution photogrammetric evaluation.
abstractThe UAV-based analysis corroborated the satellite observations in detail and enabled an accurate inventory of damaged trees as well as the exploration of their spatial distribution.

Code and data availability

The supplied blocks describe Sentinel-2 NDVI double-differencing and UAV photogrammetric segmentation for forest damage assessment, but contain no data availability statement, public repository deposit, or author URL for the paper's imagery, point clouds, segmentation outputs, or the EVELIN software. The EVELIN package

No evidence-backed public reproduction asset is currently recorded.

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