As a heat dome drives dangerous temperatures across much of the United States and renews concerns about extreme heat, USC ...

As cyber operations continue to support regional conflicts, threat groups are targeting a wider range of information, including geospatial mapping and global positioning systems (GPS) data that can be ...

Deep learning model inferencing in ArcGIS is implemented on top of the Python raster function framework. This repository serves to provide guidance on deep learning Python raster functions in ArcGIS, ...

The WRF-Hydro GIS Pre-processor provides various scripts and tools for building the geospatial input files for running a WRF-Hydro simulation. gdal 3.6.3 netcdf4 1.6.3 numpy 1.24.2 packaging 23.0 ...

Open the Planetary Computer data catalog and you will find all kinds of useful data: from decades’ worth of satellite imagery to biomass maps, from the US Census to fire data. All together, there are ...

Interested in data, science, GIS, finance, agriculture and technology. First off, let's talk about the satellites and sensors themselves. There are many options today, each with unique capabilities.

Across mapping, engineering, disaster response, and natural resource work, geospatial thinking underpins the tools we use every day. If your career now calls for sharper GIS skills—or you want a fast, ...

Wind hazards often result in significant damage to the built environment cascading into impacts on the socio-economic systems within a community. The increasing frequency and intensity of hurricane ...