National Agriculture Imagery Program
PulseAugur coverage of National Agriculture Imagery Program — every cluster mentioning National Agriculture Imagery Program across labs, papers, and developer communities, ranked by signal.
-
InfScene-SR enables seamless super-resolution for large remote-sensing scenes
Researchers have developed InfScene-SR, a novel method for seamless super-resolution of large remote-sensing scenes using diffusion models. This approach addresses the limitations of current diffusion models, which are …
-
New SCDF method improves satellite image co-registration accuracy
Researchers have developed a new method called SCDF (self-calibrating displacement fields) for accurately co-registering large optical satellite imagery. This training-free, GPU-free approach uses the displacement field…
-
GeoAI workflow maps urban tree canopy and its link to city temperatures
Researchers have developed a new optical GeoAI workflow to assess urban tree canopy cover in Davis, California. This method utilizes high-resolution imagery and deep learning models like DeepForest and Segment Anything …
-
GeoAI tutorial details building footprint extraction using U-Net, DINO, SAM, and Mask R-CNN
This tutorial details a GeoAI workflow for extracting building footprints from aerial imagery using a combination of deep learning models. It covers setting up the geospatial environment, training a U-Net model with a R…
-
New AI workflow maps farmland extent using satellite imagery and SAM 3
Researchers have developed a new workflow to map farmland extent and boundaries using 1-meter NAIP imagery. The method combines a Residual U-Net model, trained with a Dice-dominant loss, and a Segment Anything Model (SA…
-
New dataset CAFOSat aids CAFO mapping with AI
Researchers have developed CAFOSat, a new dataset designed to improve the mapping of Concentrated Animal Feeding Operations (CAFOs) using high-resolution imagery. This dataset integrates satellite imagery with refined a…