Topic
Artificial intelligence, machine learning, big data and cloud platforms applied to geospatial problems.
US states are increasingly adopting advanced geospatial technologies like lidar, machine learning, and satellite imagery to map and mitigate landslide risks. Federal grants are supporting geological surveys in building crucial data infrastructure for hazard mapping and disaster preparedness.
Source: Statescoop
Western Australia's WAVE Pilot, a collaboration between DWER and Landgate, has been shortlisted for a government innovation award. The project utilizes deep learning and satellite imagery to improve native vegetation mapping, particularly in challenging arid environments.
Source: Spatial Source
The Location Innovation Hub has released 'Location & AI: The Basics – A practical guide to GeoAI,' a new free publication exploring how the merger of AI and location data creates opportunities for businesses, public services, and society. It emphasizes GeoAI's role in understanding complex systems…
Source: Spatial Source
Zambian entrepreneur Thomas Lungu co-founded Mytochondria to help African farmers optimize crop management using satellite imagery and artificial intelligence. The platform analyzes soil, moisture, and nutrient levels to guide irrigation, fertilizer use, and forecast harvests, promoting…
Source: We Are Tech Africa
Dr. Feroza Morris from UKZN utilized satellite data and machine learning to develop remote monitoring methods for rivers in the Maloti-Drakensberg region. Her research offers a cost-effective solution to improve water management in poorly monitored catchments, crucial for South Africa's water…
Source: IOL
Research explores automating Scan-to-BIM, questioning if high AI segmentation accuracy guarantees better 3D reconstruction. Findings suggest that while segmentation is key, preserving geometric accuracy during reconstruction is vital for reliable building information models, moving beyond…
Source: Spatial Source
This week's geospatial industry roundup highlights mobile LiDAR applications in construction, the human-centric challenges of urban digital twin implementation, and a critical report from WGIC on ensuring trustworthy, AI-generated geospatial data.
Source: Geo Week News
This article details how to build an Urban Heat Island (UHI) detector using Python, open-source satellite data (Landsat, Sentinel-2), and a machine learning model. The method identifies hotspots for city planners to mitigate heat, demonstrating a reusable geospatial AI pipeline.
Source: Hackernoon
A new book from the University of Melbourne's CSDILA explores how GeoAI, digital twins, and BIM are transforming land administration and the broader geospatial ecosystem. It introduces 'land intelligence' for data-driven, location-based decisions.
Source: Spatial Source
The inaugural Geospatial Sciences Victoria Futures Forum will be held at RMIT University in Melbourne on September 24, 2026. This half-day event will gather industry, academia, and government to discuss the future of the geospatial sector, with a significant portion of the program dedicated to…
Source: Spatial Source