Geoinformation for Humanitarian Aid
User-generated spatial data, such as those provided by the OpenStreetMap project or the Social Web, are a pivotal supplement to official geodata and remote sensing data. Increasingly, user-generated spatial data are becoming ever more crucial for efficient crisis management. By combining different datasets, the resulting situation intelligence enables humanitarian relief organizations and first responders to quickly gain awareness of the situation in the aftermath of a disaster.
This information also plays a central role in mitigating risk, preparing for disaster events, and limiting the potential effects of emergencies. In cooperation with users and relief workers, we are developing innovative processes and services for innovative analysis methods to best utilize the potential of merged data from differing sources. You can find our research papers in the publications list.
Amongst Anticipatory Action strategies, Forecast-based Financing (FbF) offers a novel approach to humanitarian aid. Based on weather forecasts and risk analyses, predefined measures are initiated when a specific threshold is reached. The goal of these measures is to minimize the consequences of emergencies such as extreme weather and save lives by taking preventive action as opposed to deploying resources only after the event has occurred. HeiGIT offers technical support in FbF Projects using state-of-the-art methodologies and HeiGIT technologies (such as Sketch Map Tool and Ohsome Quality Analyst) in order to support tasks like local data collection, historical impact and risk assessment, and trigger development.
We work closely with local partners to set up comprehensive structures and methods for Forecast-based-Action. Recently, HeiGIT has been providing technical support in developing a drought Early Action Protocol (EAP), in Somaliland/Somalia and a riverine flood EAP in Sudan in close collaboration with the local Red Cross Red Crescent Societies, the German Red Cross and the Red Cross Red Crescent Climate Center.
Capacity Building and Knowledge Transfer
We put great emphasis on collaborative knowledge transfer and training. In order to reach a common understanding of local conditions and to empower our partners to carry on with Forecast based Financing projects beyond the project lifetime in the long run
An important step here is the user-friendliness of workflows and the development of easy-to-use tools and services. We make these accessible to non-technical communities.
Creating maps and mapping in OpenStreetMap can be time-consuming and often requires training or previous knowledge. To enable more people to access and contribute to this resource, HeiGIT provides tools that simplify crowd-based data collection through intuitive tools, hide complex data processing tasks, and fit into the structure of open-source projects and communities. Results from research on crowdsourcing geoinformation have been successfully transferred into real-world applications used among numerous humanitarian organizations. We integrate machine learning methods into our crowdsourcing to improve the mapping process and provide enriched datasets.
Sketch Map Tool
We provide an intuitive, simple tool for participatory in-field sketch mapping through the offline collection, digitization and georeferencing of local spatial knowledge. The tool enables community mapping in a paper-based format and provides the mapping results digitally.
This projects allows citizen scientists (mainly students) to contribute in a meaningful way to the detection of permafrost degradation in the Arctic and to actively participate in climate change research. To this end, we provide the UndercoverEisAgenten app for remotely mapping the Arctic land surface.
MapSwipe is an open-source app making worldwide mapping more coordinated and efficient. Humanitarian organizations utilize MapSwipe to identify settled regions. HeiGIT supports MapSwipe‘s crowdsourcing approach by developing and maintaining the app’s back-end tools.
This flexible platform gathers geographic information with the help of volunteers. We have collected valuable data for different use cases, from damage mapping to mapping permafrost structures. We are eager to learn about your applications, which you can submit to firstname.lastname@example.org.
Machine Learning and Humanitarian Mapping
Currently, machine learning and deep learning approaches are steadily gaining popularity within the humanitarian (mapping) community, which is employing these methods to fill vital data gaps insufficiently addressed by other sources. Alongside our cooperating partner team at GIScience Research Group Heidelberg University, HeiGIT’s strategy to integrate artificial inteligence methodologies into geospatial research is to use in-house applications in coordination with the fullest range of data sources and methods available from satellite imagery to Volunteered Geographical Information (VGI) data from OpenStreetMap (OSM) as well as supervised and unsupervised approaches to generate accurate and up-to-date data.
Deep Learning and MapSwipe
This initiative includes leveraging our application MapSwipe to crowdsource the labeling of remote sensing data to be used in conjunction with VGI data from OpenStreetMap in an active learning framework with deep neural networks to identify human settlements with improved accuracy and reduce required human labor.
GeoAI for Water Management
Clean water plays a critical role in human well-being, addressing climate change, and achieving sustainable development goals. Unfortunately, access to clean water remains a challenge for millions of people worldwide. A wastewater treatment plant (WWTP) serves to remove pollutants and purify wastewater for human consumption or release as stormwater into water bodies. The lack of accurate data on WWTP facilities necessitates the development of advanced Machine Learning and Deep Learning models from multimodal sensing data.
Our team specializes in using the in-house developed openrouteservice software for disaster and humanitarian applications. We employ the software to analyze the access, logistics, and optimization within these domains. Below are examples of how openrouteservice has been utilized in humanitarian/disaster contexts:
We enable the integration and consideration of disaster-related information, such as closed or damaged roads, in the form of geodata to manage disaster-aware routing and logistics planning. By updating the openrouteservice database frequently, changes to the infrastructure caused by the disaster are directly considered.
We combine reachability/isochrone products for healthcare facilities with population data to inform how many people are within different time catchments. This helps us understand and optimize healthcare access in disaster-affected areas.
At HeiGIT, we are committed to creating real-world impact through knowledge transfer and impact partnerships. We recognize that working closely with humanitarian organizations is crucial to achieving this goal. In collaboration with our partners, we can develop innovative open technologies to support their work.
Our partners serve as channels for us to understand the challenges faced on the ground. Together, we create solutions tailored to their specific needs. By engaging in knowledge transfer and collaboration, we can develop sustainable solutions that create lasting impacts. We take pride in our ability to work closely with organizations that share our vision of making a positive difference in the world.
Missing Maps is an initiative of various humanitarian organizations to map missing information in areas impacted by natural disasters and other threats in OpenStreetMap even before an emergency occurs. This geospatial data can then be used for preventive measures in advance of natural disasters or in response to support the work of local and international relief organizations.
German Red Cross
The partnership between the German Red Cross (GRC) and HeiGIT enables us to develop geoinformatic data products, methods and technology for the implementation of humanitarian activities of the Red Cross and Red Crescent Movement. At the same time, the knowledge gained from this partnership is incorporated into the work of HeiGIT. In the course of the cooperation between the GRC and HeiGIT, a specialist office for geoinformatics financed by the Klaus Tschira Foundation could be created within the International Cooperation team of the GRC.
|– improvement and extension of the Sketch Map Tool, for real use by the German Red Cross|
|– detection of thawing permafrost in the Arctic by citizen scientists (especially school students)|
|– support for Missing Maps in monitoring and visualizing its performance and impact using information from HOT Tasking Manage|
Cooperation Projects with HeiGIT Support
|Global Exposure Data for Risk Assessment||– global disaster risk reduction dataset|
|– assessing the quality of health-related data in OpenStreetMap|
|– comparing the accessibility of healthcare facilities around the globe|
|– HeiGIT’s Map of Hope provides a geographic overview of planned, ongoing and completed clinical trials|
|– creating new remote employment opportunities for individuals affected by COVID-19 lock downs|
|HOT Mapswipe||– MapSwipe extension to monitor changes in satellite imagery|