← All projectstreeai.earthSince Sep 2026

Swiss Standing Deadwood

Mapping standing deadwood across Switzerland from high-resolution aerial imagery, and identifying the climatic and environmental drivers behind it.

Paper
Swiss Standing Deadwood logo

About

A Switzerland-wide forest mortality assessment: semantic segmentation of high-resolution remote sensing data maps standing deadwood, and random forest models identify the climatic and environmental drivers behind it. Results are explorable in a Google Earth Engine app, and the study is published in the ISPRS Journal of Photogrammetry and Remote Sensing.

The assessment covers 2018 to 2023 and is derived from centimeter-scale aerial imagery (SWISSIMAGE 10 cm orthophotos). It finds standing deadwood concentrated upslope, with the highest shares at mid to high elevations around 1,500 m, and relative increases of up to 43% in overlapping survey areas after the 2018 drought; maximum temperature anomalies and conifer dominance were the strongest predictors. The maps — deadwood segmentation at 10 cm, aggregated shares at 10 m and 100 m, and per-canton and per-district shares — can be explored in the Google Earth Engine app on treeai.earth.

Activity

29 Sep 2026ShipPublished in P&RS ↗ISPRS Journal of Photogrammetry and Remote Sensing
12 Mar 2026ShipPreprint on EarthArXiv ↗Nationwide deadwood mapping reveals rising mountain forests vulnerability

ETH AI Club members involved

Luca Ferrari