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Turkana camp roof mapping
April 2024
This project automates the identification of buildings and solar panels in aerial imagery, aiding humanitarian mapping. In many developing regions, maps are often outdated or missing, hindering development planning and disaster response. Our work accelerates the creation of up-to-date maps,…
Damage Assessment Visualizer
November 2022
The Damage Assessment Visualizer leverages satellite imagery from a disaster region to visualize conditions of building and structures before and after a disaster. It includes a visual layer on top of the satellite images which predicts the extent of damage…
Satellite Imagery Labeling Tool
November 2022
This is a lightweight web-interface for creating and sharing vector annotations over satellite/aerial imagery scenes.
Building Damage Assessment CNN Siamese
December 2021
A Microsoft AI for Humanitarian Action study in collaboration with the NLRC 510 global initiative. In this study, we leverage high-resolution satellite imagery to conduct building footprint segmentation and train a classifier to assign each building’s damage severity level via…
Temporal Cluster Matching
December 2021
An implementation of the temporal cluster matching method for detecting change in structure footprints from time series of remotely sensed imagery.
TorchGeo
December 2021
TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data. The goal of this library is to make it simple: for machine learning experts to use geospatial data in their workflows, and…
Land Cover Mapping
July 2020
Part of the AI for Earth Land Cover Mapping project, this repository holds both the frontend web-application and backend server that make up our “Land Cover Mapping” tool.