3 papers
cs.LG2026
From Machine Learning to Large-Scale EO Products: Best Practices for Making Maps
Ghjulia Sialelli, Robin Young, Yuchang Jiang +9
Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by advances in machine learning (…
cs.CV2025
GSR4B: Biomass Map Super-Resolution with Sentinel-1/2 Guidance
Kaan Karaman, Yuchang Jiang, Damien Robert +3
Accurate Above-Ground Biomass (AGB) mapping at both large scale and high spatio-temporal resolution is essential for applications ranging from climate modeling to biodiversity asse…
cs.CV2023
Accuracy and Consistency of Space-based Vegetation Height Maps for Forest Dynamics in Alpine Terrain
Yuchang Jiang, Marius Rüetschi, Vivien Sainte Fare Garnot +4
Monitoring and understanding forest dynamics is essential for environmental conservation and management. This is why the Swiss National Forest Inventory (NFI) provides countrywide…