Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation

TL;DR

This paper introduces a novel satellite data-driven method to generate high-resolution, temporal canopy height maps across Europe from 2019 to 2022, aiding ecological monitoring and biomass estimation.

Contribution

It presents the first 10m resolution temporal canopy height map for Europe using Sentinel satellite data and GEDI LiDAR ground truth, enabling large-scale forest monitoring.

Findings

Accurate multi-year canopy height predictions over Europe.

First high-resolution temporal canopy height map for the continent.

Publicly available pipeline and data for ecological research.

Abstract

With the rise in global greenhouse gas emissions, accurate large-scale tree canopy height maps are essential for understanding forest structure, estimating above-ground biomass, and monitoring ecological disruptions. To this end, we present a novel approach to generate large-scale, high-resolution canopy height maps over time. Our model accurately predicts canopy height over multiple years given Sentinel-1 composite and Sentinel~2 time series satellite data. Using GEDI LiDAR data as the ground truth for training the model, we present the first 10m resolution temporal canopy height map of the European continent for the period 2019-2022. As part of this product, we also offer a detailed canopy height map for 2020, providing more precise estimates than previous studies. Our pipeline and the resulting temporal height map are publicly available, enabling comprehensive large-scale monitoring of forests and, hence, facilitating future research and ecological analyses.