Windthrow Mapping with Sentinel-2 and PlanetScope in Triglav National Park: A Regional Case Study

Abstract

Highlights: This regional case study uses multi-temporal Sentinel-2 and PlanetScope imagery to map windthrow and estimate parcel-level timber damage in alpine forests. The findings reflect within-sample performance for a single event in Triglav National Park. The comparison with official sanitary-logging records (n = 8, non-probability) is preliminary and not generalisable. What are the most important results? Within-sample overall accuracy for PlanetScope 72.9% (95% CI: 71.2–74.6%) and Sentinel-2 69.2% (95% CI: 67.4–71.2%) in this alpine regional case study. Detection was size-dependent: gaps larger than 0.5 ha were consistently detected, while gaps smaller than 0.1 ha were frequently omitted. Omissions were higher for Sentinel-2 and lower for PlanetScope, indicating a modest advantage for smaller fragmented patches in this sample. Linking satellite-derived change maps with available forest stand data enabled parcel-level estimates of damaged timber volume. Across n = 8 non-probability parcels, compared with official sanitary-logging records, mean absolute deviations were 5–7%; these figures are preliminary and not generalisable. What are the implication of the main finding? The study documents within-sample performance from a regional case study in alpine terrain. Any broader generalisation will require larger, probability-based validation across additional events and forest types, as well as broader access to parcel-level official records. In our sample, PlanetScope omitted fewer smaller fragmented gaps than Sentinel-2, while gaps smaller than 0.1 ha often required field verification or VHR/UAV follow-up. The reported bootstrap confidence intervals express within-sample uncertainty and do not constitute operational performance guarantees. Extreme weather increasingly damages forest ecosystems, and affected areas are often remote or inaccessible, limiting field surveys. In such contexts, remote sensing can complement damage assessment. This study presents a regional case study evaluating established multi-temporal optical change detection for windthrow mapping in Triglav National Park (Slovenia) using Sentinel-2 and PlanetScope imagery. Bitemporal index differencing and fixed thresholds were applied, with accuracy quantified via a block bootstrap to account for spatial autocorrelation. Within-sample overall accuracy was 69.2% (95% CI: 67.4–71.2%) for Sentinel-2 and 72.9% (95% CI: 71.2–74.6%) for PlanetScope. Detection was strongly size-dependent: gaps greater than 0.5 ha were consistently detected, whereas gaps smaller than 0.1 ha were frequently omitted, particularly with Sentinel-2. Linking satellite-derived change maps with forest stand data enabled parcel-level estimates of damaged timber volume; this linkage was examined on a small, non-probability set of parcels and is therefore preliminary. We position the work strictly as a case study documenting within-sample performance in alpine terrain. Broader generalisation will require probability-based validation across additional events and forest types, and wider access to parcel-level official records.