Reliability of Machine Learning Maps
Academics are increasingly adopting machine learning maps to better understand what can happen for a range of environmental events.
Run AI-Mapping in QGIS over high-resolution satellite imagery
Mapflow is a QGIS plugin that lets users extract real-world objects from satellite imagery.
Mapping Schools with Artificial Intelligence
Researchers are using AI to map schools in countries where many schools are undocumented so as to connect children with schools.
Algorithmic Warfare: “Imagine” and “Implement”
Though conceptual Artificial Intelligence (AI) has been around since the 1950’s, its methods were not adopted by the United States Department of Defense (DOD) until recently.
Machine Learning and Object Detection in Spatial Analysis
Picterra offers a relatively easy to use interface that allows users train AI on satellite and aerial imagery to detect features.
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.