AI and modern tooling are reshaping geospatial work by enabling free satellite data, cloud platforms, and machine learning models to process imagery at scale. Practical workflows now use open-source l…
Researchers introduced GeoDisaster, a benchmark for operational geospatial disaster reasoning with 2,921 instances across 43 question types, and proposed an orchestrated multi-agent framework with 18 …
The Tessera team released v1.1 of their geospatial embedding model, improving temporal stability and reducing noise in regions with sparse satellite observations. The update eliminates grid-like seams…
Researchers released Biomazon, a 20-meter multimodal benchmark dataset covering the Amazon Basin that pairs GEDI relative height (RH) profiles and aboveground biomass density (AGBD) targets with satel…
Researchers have developed a self-supervised deep learning framework that enhances Sentinel-1 Stripmap imagery by exploiting azimuth subaperture decomposition, generating paired training data without …
Researchers have developed AGFlow, a spatiotemporal flow-matching model that fuses asynchronous Sentinel-1 radar and Sentinel-2 optical satellite data to remove clouds and reconstruct missing time-ser…