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.
Researchers at the University of Turku have a developed a method of modeling tree species distribution in Peruvian lowland Amazonia using satellite imagery and machine learning techniques in order to produce higher resolution habitat suitability maps.
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.
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.
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.