Automated Remote Sensing of Underground Features
Below ground mapping can now better utilize remotely sensed data to create more accurate maps.
Using Crowdsourcing and Deep Learning to Map Human Settlements
Machine learning techniques are being used to map new urban and land use patterns that were previously difficult to detect using crowdsourcing data.
Using Satellite Imagery to Map Obesity Rates
One study recently looked at about 150,000 high resolution satellite images of cities in the United States along with census data of these areas in order to understand obesity rates in the built environment.
Geospatial Artificial Intelligence: Emerging Trends and Challenges
There are both challenges and opportunities that Artificial Intelligence (AI) has in applying geospatial and GIS knowledge that also addresses issues of time and spatial bias.
Future of Mobile Spatial Applications and Image Recognition
Image recognition software and algorithm development is likely to be increasingly applied with spatial applications.
Detecting Flooded Roads From Satellite Imagery
Mapping flood damage by manually examine imagery is a time-intensive and expensive process. New, automated methods using satellite data that compare pre and post-flood conditions are being developed.