Mapping tropical forest cover and deforestation with Planet NICFI satellite images and deep learning in Mato Grosso State (Brazil) from 2015 to 2021
Monitoring changes in tree cover for assessment of deforestation is a premise for policies to
reduce carbon emission in the tropics. Here, a U-net deep learning model was used to map …
reduce carbon emission in the tropics. Here, a U-net deep learning model was used to map …
Integration of deep learning algorithms with a Bayesian method for improved characterization of tropical deforestation frontiers using Sentinel-1 SAR imagery
Tropical deforestation frontiers continue to expand at alarming rates, but their fine-scale
temporal patterns (eg, start timing, patch forming speed, temporal clustering within a year) …
temporal patterns (eg, start timing, patch forming speed, temporal clustering within a year) …
[HTML][HTML] How textural features can improve SAR-based tropical forest disturbance mapping
Spatially and timely accurate information about tropical forest disturbances is crucial for
tracking critical forest changes, supporting forest management, and enabling law …
tracking critical forest changes, supporting forest management, and enabling law …
Leveraging past information and machine learning to accelerate land disturbance monitoring
Near real-time (NRT) monitoring of land disturbances holds great importance for delivering
emergency aid, mitigating negative social and ecological impacts, and distributing resources …
emergency aid, mitigating negative social and ecological impacts, and distributing resources …
[HTML][HTML] Deep learning and automatic reference label harvesting for Sentinel-1 SAR-based rapid tropical dry forest disturbance mapping
The advent of temporally dense radar data such as the Sentinel-1 SAR have opened the
door for rapid forest disturbance detection in the humid tropics. Tropical dry forest …
door for rapid forest disturbance detection in the humid tropics. Tropical dry forest …
Globally vs. Locally Trained Machine Learning Models for Landslide Detection: A Case Study of a Glacial Landscape
Landslide risk mitigation is limited by data scarcity; however, this could be improved using
continuous landslide detection systems. To investigate which image types and machine …
continuous landslide detection systems. To investigate which image types and machine …
Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring
J Doblas Prieto, L Lima, S Mermoz… - … Journal of Remote …, 2023 - Taylor & Francis
More than half a decade after the launch of the Sentinel-1A C-band SAR satellite, several
near real-time forest disturbances detection systems based on backscattering time series …
near real-time forest disturbances detection systems based on backscattering time series …
Towards the use of satellite-based tropical forest disturbance alerts to assess selective logging intensities
Illegal logging is an important driver of tropical forest loss. A wide range of organizations and
interested parties wish to track selective logging activities and verify logging intensities as …
interested parties wish to track selective logging activities and verify logging intensities as …
A multi-source change detection algorithm supporting user customization and near real-time deforestation detections
The abundance of free and accessible satellite data has revolutionized our ability to study
deforestation with remote sensing. Recent advances have enabled us to monitor …
deforestation with remote sensing. Recent advances have enabled us to monitor …
ReCuSum: A polyvalent method to monitor tropical forest disturbances
Y Bertrand, F Frederic, W Jean-Pierre… - ISPRS Journal of …, 2023 - Elsevier
Change detection methods based on Earth Observations are increasingly used to monitor
rainforest in the intertropical band. Until recently, deforestation monitoring was mainly based …
rainforest in the intertropical band. Until recently, deforestation monitoring was mainly based …