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Automatic building detection with ohsome2label and Tensorflow

Accurate and complete geographic data of human settlement is crucial for humanitarian aid and disaster response. OpenStreetMap (OSM) can serve as a valuable source, especially for global south countries where buildings are largely unmapped. In a previous blog, we introduced … Read More

Detecting OpenStreetMap missing buildings by transferring pre-trained deep neural networks

Recently, a new research paper “Detecting OpenStreetMap missing buildings by transferring pre-trained deep neural networks” (Pisl, J., Li, H., Herfort, B., Lautenbach, S., Zipf, A. 2021) has been accepted at the the 24th AGILE conference 2021. The conference will take … Read More

Introducing ohsome2label tool to generate training samples from OpenStreetMap for geospatial deep learning

After more than a decade of rapid development of volunteered geographic information (VGI), VGI has already become one of the most important research topics in the GIScience community. Almost in the meantime, we have witnessed the ever-fast growth of geospatial … Read More

Tools for Disaster Risk Reduction by HeiGIT – Celebrating the International Day for Disaster Risk Reduction

Today we celebrate the International Day for #DisasterRiskReduction. HeiGIT offers a growing set of tools and services that support humanitarian aid during and before disasters. Examples include work in the context of the Missing Maps initiative, like conceptualising and extending … Read More

Mapping Human Settlements with Higher Accuracy and Less Volunteer Efforts by Combining Crowdsourcing and Deep Learning

Our new paper on Machine Learning and Humanitarian Mapping Nowadays, Machine Learning and Deep Learning approaches are steadily gaining popularity within the humanitarian (mapping) community. New tools such as the ML Enabler or the rapId editor might change the way … Read More

MapSwipe for Change Detection Analysis

The Humanitarian OpenStreetMap Team (HOT) , the Heidelberg Institute of Geoinformation Technology (HeiGIT) , and the wider MapSwipe Community started working on an MapSwipe extension to monitor changes in satellite imagery. The goal of the two-month project is to extend … Read More

Empower Humanitarian Mapping with Deep Neural Networks to Detect Human Settlements

Recently, earth observation by satellites has shown great capability in supporting a range of challenges such as disaster assessment, agriculture monitoring, and humanitarian mapping. MapSwipe, as a humanitarian mapping app, provides a crowdsourcing platform to collect volunteered geographical information (VGI), … Read More

Put the world’s most vulnerable people on the map with MapSwipe

Humanitarian organizations can’t help people if they can’t find them. This was the simple reason to create MapSwipe back in 2016 and it is still as pressing as in the very beginning. In the last 2,5 years volunteers have contributed … Read More