Detecting forest storm damage with multi-temporal Sentinel-1 InSAR coherence time series

Extreme weather events pose substantial risks to forest ecosystems and forestry operations. Synthetic Aperture Radar (SAR) can address these challenges due to its ability to operate in all weather conditions and penetrate cloud cover. This study demonstrates, to the best of our knowledge, for the first time the potential of Sentinel-1 (S1) interferometric SAR (InSAR) coherence time series for rapid detection of windthrow-induced forest damage.

The study focuses on a severe storm near Otok (45°09′N, 18°53′E), Croatia, on 19 July 2023. We analyzed 84 forest plots, categorized into five damage classes: A – no damage (0–10%, 13 plots), B – minor (10–20%, 18), C – moderate (20–50%, 19), D – significant (50–80%, 22), and E – severe damage (80–100%, 12). Each plot represented a 50-meter radius area (~0.8 hectares).

Coherence magnitudes in VV and VH polarizations were calculated from consecutive image pairs for three S1 relative orbits (51, 73, 175). The pre-storm (25 June–18 July) and post-storm (1–24 Aug) periods were analyzed, each spanning 24 days and six S1 images (2 per orbit). Image pairs with second images from 19–31 July were excluded to avoid interference from the storm. Data were grouped by damage class, and statistical differences were assessed using the Mann-Whitney U test.

Post-storm, intra-group median VV coherence magnitudes differed significantly between no-damage and heavy-damage groups (e.g., A vs. D, and A vs. E). However, the coherence signal was near noise levels, reflecting the subtlety of the damage signature (Table 1). No significant differences were observed during the pre-storm period, underscoring VV coherence's sensitivity to storm-induced structural damage. VH coherence and VV and VH backscatter were not sensitive to windthrow.

This study highlights the potential of Sentinel-1 InSAR coherence in forest monitoring frameworks, supporting operational planning in forestry. The inclusion of Sentinel-1C will reduce the temporal baseline (from 12 to 6 days) further mitigating temporal decorrelation and enabling denser time series.

Table 1. Inter-group comparison (Mann-Whitney U test) and intra-group statistics.
	Post-storm				Pre-storm
P-value (Significance ≤ 0.001)	A	D	E		A	D	E
D	0.0003	-			0.5799	-
E	7.0e-06	0.0903	-		0.5410	0.7479	-
Group size	78	132	72		78	132	72
Median coherence	0.145	0.196	0.227		0.127	0.129	0.136
IQR of coherence	0.096	0.132	0.141		0.103	0.094	0.108