Martin Schwartz

• Laboratoire des Sciences du Climat et de l'Environnement

Accurate mapping of vegetation canopy height and biomass distribution is essential for effective forest monitoring, climate change mitigation, and sustainable forestry. Here we present high-resolution remote sensing-based canopy height (10 m resolution) and above ground biomass (AGB, 50 m resolution) maps for the forests of the Iberian Peninsula fr...

African tropical forests play a crucial role in global carbon dynamics, biodiversity conservation, and climate regulation, yet monitoring their structure, diversity, carbon stocks and changes remains challenging. Remote sensing techniques, including multi-spectral data, lidar-based canopy height and vertical structure detection, and radar interfero...

Significant efforts have been directed towards adapting self-supervised multimodal learning for Earth observation applications. However, existing methods produce coarse patch-sized embeddings, limiting their effectiveness and integration with other modalities like LiDAR. To close this gap, we present DUNIA, an approach to learn pixel-sized embeddin...

The development of high-resolution mapping models for forest attributes based on remote sensing data combined with machine or deep learning techniques has become a prominent topic in the field of forest observation and monitoring. This has resulted in the availability of multiple, sometimes conflicting, sources of information, but, at face value, i...

Introduction: The knowledge about forest growth, influenced by factors such as tree species, tree age, and environmental conditions, is a key for future forest preservation. Height and age data can be combined to describe forest growth and used to infer known environmental effects. Methods: In this study, we built 14 height growth curves for stands...

Estimating canopy height and canopy height change at meter resolution from satellite imagery has numerous applications, such as monitoring forest health, logging activities, wood resources, and carbon stocks. However, many existing forest datasets are based on commercial or closed data sources, restricting the reproducibility and evaluation of new...

We propose a framework for global-scale canopy height estimation based on satellite data. Our model leverages advanced data preprocessing techniques, resorts to a novel loss function designed to counter geolocation inaccuracies inherent in the ground-truth height measurements, and employs data from the Shuttle Radar Topography Mission to effectivel...

Forests are carbon sinks essential for climate change mitigation. However, increased harvests and natural disturbances across Europe have recently challenged this role. To project the future carbon sink capacity of Europe's forests, we integrated country reports from the United Nations Framework Convention on Climate Change (UNFCCC) with remote sen...

The contribution of forests to carbon storage and biodiversity conservation highlights the need for accurate forest height and biomass mapping and monitoring. In France, forests are managed mainly by private owners and divided into small stands, requiring 10 to 50 m spatial resolution data to be correctly separated. Further, 35 % of the French fore...

The frequency and intensity of summer droughts and heat waves in Western Europe have been increasing, raising concerns about the emergence of fire hazard in less fire-prone areas. This exposure of old-growth forests hosting unadapted tree species may cause disproportionately large biomass losses compared to those observed in frequently burned Medit...

The contribution of forests to carbon storage and biodiversity conservation highlights the need for accurate forest height and biomass mapping and monitoring. In France, forests are managed mainly by private owners and divided into small stands, requiring 10 to 50 m spatial resolution data to be correctly separated. Further, 35 % of the French fore...

Accurate and timely monitoring of forest canopy heights is critical for assessing forest dynamics, biodiversity, carbon sequestration as well as forest degradation and deforestation. Recent advances in deep learning techniques, coupled with the vast amount of spaceborne remote sensing data offer an unprecedented opportunity to map canopy height at...

We estimated the loss of biomass in the forests during the fire season over the period 2020-2022.This estimate is based on a fine resolution method from BAMTs fire polygon, tree height fromSchwartz et al. (2022) and NFI data. In comparison, we extracted biomass data based on treeheights calculated by Potapov, from ESA CCI Biomass data and from the...

The frequency and intensity of summer droughts and heat waves in Western Europe have been increasing, raising concerns about the emergence of fire hazard in less fire prone areas. This exposure of old-growth forests hosting unadapted tree species may cause disproportionately large biomass losses compared to those observed in frequently burned Medit...

In intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10 - 20 meters) is arguably needed to capture the differences in canopy height. In this work, we developed a deep learning model based on multi-stream remote sensing measurements to creat...