Aufbau des Heidelberg Institute for Geoinformation Technology
Das Projekt lief bis Juni 2019 und wurde als HeiGIT gGmbH weitergeführt. Aktuelle Informationen finden sich auf der Webseite des HeiGIT
getragen von der Klaus Tschira Stiftung
Das Projekt zum Aufbau des Heidelberg Institute for Geoinformation Technology (HeiGIT) ist an der Abteilung Geoinformatik am Geographischen Institut der Universität Heidelberg angesiedelt. Das Ziel ist es den Wissens- und Technologietransfer aus der Geoinformatik-Grundlagenforschung in die Praxis auf Basis innovativer Geoinformationstechnologien zu verbessern. Der Fokus liegt auf der Umsetzung praxisbezogener Projekte und Dienste vor allem in den Bereichen
- Big Spatial Data Analytics,
- Intelligente Ortsbasierte Dienste und Navigation, sowie
- Disaster-Mapping für humanitäre Hilfen.
Big Spatial Data Analytics | Navigation Intelligence & Location Based Services |
Analyse, Veredelung und Nutzung von Geoinformationen aus nutzergenerierten Geodaten durch Spatial Data Mining, Machine Learning und Geocomputation
Leistungen und Referenzen |
Innovative Verkehrs- und Mobilitätslösungen, Routing- und Navigationsdiensten auf Basis veredelter Daten von OpenStreetMap und des Social Web
Leistungen und Referenzen |
Disaster Mapping - (V)GI für humanitäre Hilfe |
Unterstützung humanitärer Aktionen durch innovative Geo-Dienste und aktuelle Karten für das Katastrophenmanagement v.a. auf Basis nutzergenerierter Geodaten (Crowdsourcing, OSM, Social Web...)
Leistungen und Referenzen |
Aktuelle Neuigkeiten:
The novel coronavirus disease (COVID-19) generated significant health concerns worldwide, leading policymakers and health care experts to implement nonpharmaceutical public health interventions to mitigate the spread of the virus. While these interventions played a crucial role in controlling transmission, they also resulted in substantial economic and societal costs, necessitating strategic deployment, particularly during periods of […]
Fig. 1: New feature: combining attributes We recently added the attribute completeness indicator to the Ohsome Dashboard, and we’re now happy to introduce major upgrades to its functionalities. The ohsome quality API (OQAPI) and the ohsome dashboard The ohsome quality API was built to provide data quality estimations for OpenStreetMap data. There are currently four […]
Wastewater treatment plants (WWTPs) play a crucial role in maintaining ecological balance and public health and are essential for advancing social sustainable development goals. However, the diverse architectural styles, scales, and environmental contexts of WWTPs—shaped by climate, topography, and regional economic conditions—pose significant challenges for generalizing segmentation algorithms. To address this, integrating knowledge from different […]
Road traffic and residential heating are the two main sources of CO₂ emissions in many cities. HeiGIT´s new emission inventories map these emissions and can simulate the effects of new policies and interventions. We calculated how emissions would change in Heidelberg, Germany, if we introduced a 30 km/h road speed limit and replaced oil and […]
Free and open-source map data has become a keystone for research across diverse fields. The extensive coverage of OpenStreetMap (OSM) data allows scientists to conduct independent studies without relying on corporate collaborations or investing heavily in proprietary datasets. However, OSM data coverage completeness varies significantly by location. Moreover, the latest data updates cannot always be […]
The renewable energy (RE) sector is a cornerstone of global climate action, yet its workforce remains marked by gender inequality. Women are significantly underrepresented, often relegated to lower-paid, non-technical roles. Traditional analyses of this disparity frequently ignore the spatial dimensions that influence women’s employment opportunities—factors like public transportation access, safety, and neighborhood walkability. Addressing these […]
Studies have long assessed people’s accessibility to amenities through public transportation, typically using General Transit Feed Specification (GTFS) data. GTFS reflects planned transportation schedules, detailing the intended services and routes of transit systems. However, this approach raises an important question: are we missing critical insights by not incorporating real-time information? A recent study led by […]
The ohsome-py Python package is a client for the ohsome API, designed to facilitate the extraction and analysis of historical OpenStreetMap (OSM) data. The package simplifies handling API requests and responses by converting them into pandas or GeoPandas data frames, making data analysis and visualization easier. With ohsome-py, you gain all the functionalities of the […]
In the field of humanitarian aid, Anticipatory Action (AA) is emerging as an important strategy to mitigate the impacts of natural disasters. At HeiGIT, we have been actively working with this approach to support local communities in building resilience. Unlike traditional reactive responses, AA aims to initiate predefined actions based on weather forecasts and risk […]
With 2024 drawing to a close, we reflect on a year filled with events, accomplishments and opportunities to make a positive impact. Halfway through the year, we celebrated HeiGIT’s fifth anniversary—a moment to appreciate how far we’ve come and everything we’ve accomplished together. From our early days to the milestones of 2024, our growth sets […]
Anticipatory Action for Disaster Management In the field of humanitarian aid, Anticipatory Action (AA) is emerging as an important strategy to mitigate the impact of hazards. Anticipatory Action is an innovative mechanism that intends to make humanitarian resources available before the disaster happens, based on prior data-driven forecasts and risk assessments. This approach seeks to […]