Open Repository for Geospatial Training Data Released
Radiant Earth has launched Radiant MLHub, a cloud-based open library for training geospatial data used by machine learning algorithms.
Using Machine Learning and Surface Deformation Data to Predict Earthquakes
There is no easy solution for earthquake prediction, but machine learning in particular has made forecasting far better.
Optimizing Traffic with Autonomous Vehicles and Machine Learning
One way to improve traffic is to integrate technologies within autonomous cars, particularly as they are forecast to be soon on our streets, including sensors for driving, and information from different external sources.
When AI Goes Wrong in Spatial Reasoning
Machines can learn ‘wrong’ or biased information, creating large problems and poor conclusions when it comes to spatial data.
Using Machine Learning and Satellite Imagery for Street Address Generation
Researchers from Facebook and MIT Labs have proposed a new methodology that uses machine learning and satellite imagery to generate street addresses in areas of the world where individual buildings don’t have a unique address.
Mapping Tree Species in the Amazon Using Satellite Imagery and Machine Learning
Researchers have developed a method of modeling tree species distribution in Peruvian lowland Amazonia using satellite imagery and machine learning techniques.
Detecting Storm Intensity from Satellite Imagery Using Machine Learning
The Deep Learning-based Hurricane Intensity Estimator is an experimental portal that uses machine learning techniques to analyze spatial patterns in infrared satellite imagery in order to predict tropical cyclone intensity.
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.