This study presents a rapid flood impact assessment framework using Sentinel-1 SAR data and Google Earth Engine, enhancing disaster response capabilities.
SAR Flood Impact Assessment for Agriculture Read More »
The Perito Moreno Glacier, once noted for its stability, is now rapidly changing. Researchers used remote sensing and mass balance equations to measure its ablation rate, uncovering significant ice loss due to warming and droughts, signaling a vital shift in glacier dynamics.
Perito Moreno Glacier’s Rapid Change: A Climate Warning Read More »
This research addresses the disconnect between satellite data and policy-making in West Africa. It introduces advanced Earth observation techniques for soil erosion monitoring and outlines a strategic pathway to integrate these insights into national frameworks, supporting efforts to achieve Land Degradation Neutrality by 2030.
Satellite Data for Soil Erosion Control in West Africa Read More »
This study examines UAV-based LiDAR technology for measuring crop characteristics such as canopy height and leaf area index under day and night conditions.
Crop Measurement with UAV LiDAR Read More »
Researchers have integrated mobile lidar technology and open-source tools to automate urban tree inventories. This approach enhances efficiency and affordability in mapping and measuring urban trees, which is crucial for environmental planning and ecosystem service assessment, offering significant benefits for city planning and management.
Tree Inventories with Mobile Lidar Read More »
Researchers have introduced a novel ensemble learning framework utilizing UAV imagery and soil auxiliary data to enhance soil salinity estimation.
Soil Salinity Estimation with UAV data Read More »
SELVABOX, the largest open-access dataset for tropical tree crown detection, spans three countries and includes over 83,000 manually labeled crowns.
Tropical Tree Detection Dataset Read More »
This study employs multi-temporal SAR interferometry to monitor vertical displacement in the Tengiz oil reservoir.
Multi-temporal sar for oil reservoir monitoring Read More »
Data-Driven Approach to Quantify Agricultural Losses from Flooding Discover a method that combines Sentinel-2 satellite data, topographic information, and field surveys in a random forest model to classify flood damage in 412 agricultural fields, providing quantitative yield loss estimates for the 2023 Emilia-Romagna event and supporting effective compensation strategies in vulnerable areas. Flood Impacts on
Assessing Crop Flood Damage Using Sentinel-2 Read More »
