Startups and the Future of Spatial Analysis
A growing number of startups are developing new approaches to advanced spatial analysis for everyday solutions across many fields and industries.
Forecasting Fire: Earth Observation and GIS
New techniques in GIS, remote sensing, and machine learning are incorporating land-based data along with temperature, precipitation and other weather factors in developing more accurate fire prediction models.
Creating Ground-level Views from Satellite Imagery
Recreating a ground-level image and perspective using satellite imagery has only recently been developed.
Future of Mobile Spatial Applications and Image Recognition
Image recognition software and algorithm development is likely to be increasingly applied with spatial applications.
Using Machine Learning to Speed Up Electrical Grid Mapping
Development Seed, working for the World Bank Group, created a methodology for integrating machine learning with manual mapping in order to speed up the mapping of  high-voltage (HV) grids in developing countries.
The Role of GIS in Predicting Road Conditions
Recent developments in GIS and analytical applications have demonstrated that predicting road conditions, and thus preventing traffic accidents and possibly even traffic in the first place, is possible.
Transforming Satellite Imagery Classification with Deep Learning
Deep learning has a potential to transform image classification and its use for the spatial sciences, including GIS.
Will 2017 be Remembered as a Stellar Time for Earth Observation?
Joe Francica, Managing Director Location Intelligence Solutions with Pitney Bowes discusses the growth and direction of Earth Observation satellites. Â
GIS and Machine Learning for Habitat Protection
With gains in computational power and accessibility to off the shelf models, often used in commercial or open source software, applying machine learning techniques with GIS has become far easier for conservation and habitat specialists.
Researchers are Using Machine Learning to Better Predict Weather Patterns
The enormous amount of data from Earth-observing satellites is pushing researchers to use machine learning to mine the information and improve climate models.
Using Visual Search to Find Geographically Similar Features on Satellite Imagery
Descartes Labs recently unveiled its GeoVisual Search application which uses machine learning to visually search satellite imagery for similar geographic features.
Using Machine Learning and Satellite Imagery to Estimate Corn Crop Production
Descartes Lab, a start-up organization, has created crop production analysis that uses millions of satellite images and machine learning to produce accurate data about the production of agricultural crops.