HeiGIT Technology and Projects

HeiGIT Technology

openrouteservice.org

openrouteservice.org offers routing services based on user-generated, communally collected, free geographic data from OpenStreetMap. It is more than just routing, the ORS also offers accessibility analyses with isochrones, distance matrices and specific search capabilities regarding POIs.

openrouteservice to vaccination centers

The route planning app helps you answer the question: “Where is the closest Covid-19 vaccination center and what is the best way to get there?” by suggesting routes to the nearest vaccination center. It is built on the basis of HeiGIT’s openrouteservice technology and uses data from OpenStreetMap (OSM). The application also offers written navigation instructions and further information about vaccination centers. It works online and can be used through modern web browsers on a PC, or on newer smartphones and tablets.

openrouteservice for Disaster Management

The ongoing HeiGIT project openrouteservice for Disaster Management is a collaboration between the openrouteservice Team and the Geoinformation for Humanitarian Aid Team. The goal is to provide reliable and up-to-date data of the infrastructure network in disaster-stricken areas by improving both quantity and quality of OSM road network data, by providing dynamic real-time information, as well as an offline mobile client tool, and much more. We focus on the humanitarian aspect by improving situational awareness, especially regarding the (changing) conditions of the road network during disasters. The openrouteservice for Disaster Management makes use of HeiGIT’s openrouteservice and is supported with additional information by the Geoinformation for Humanitarian Aid Team.

Humanitarian OSM Stats

Humanitarian OSM Stats is an ongoing HeiGIT project which aims at presenting statistics and graphs concerning mapping in OpenStreetMap (OSM) for humanitarian purposes by combining the analysis of data from the HOT Tasking Manager, population data sets, and OSM History data using the HeiGIT technology OSHDB.

MapSwipe

MapSwipe is an open-source mobile application that aims to make mapping around the world more coordinated and efficient. Since its start in 2015, MapSwipe has scaled to 29,000 users who have mapped 1,300,000 km². MapSwipe is an opensource project that is still ongoing and apart of HeiGIT technologies. It is built and maintained by volunteers with the support of the British Red Cross, the GIScience Research Group, the Humanitarian OpenStreetMap Team and the organization Médecins Sans Frontières. The team at the Heidelberg Institute for Geoinformation Technology (HeiGIT) and the GIScience Research Group at Heidelberg University have shaped MapSwipe’s development from the very beginning by designing the crowdsourcing approach behind MapSwipe, providing the tools needed to manage such a global project, and by making use of the data in a timely manner. Our work ensures that volunteer efforts can turn into meaningful data for humanitarian organizations.

OpenStreetMap History Database (OSHDB)

The OSHDB allows enables theto investigatione of the evolution of the amount of data quantity and the contributions of this data to the OpenStreetMap project. The OSHDB has been designed for efficient storage of and access to OpenStreetMap’s data history. In order to ensure the scalability of the system, OSHDB builds on a partitioning schema which allows distributed data storage and parallel execution of computations. We implemented aAn API, the OSHDB API, implemented by HeiGIT, which provides an interface to the OSHDB in the Java programming language.

ohsome History Explorer (ohsomeHeX)

The ohsome History Explorer (ohsomeHeX), one of HeiGIT’s technologies, allows the spatio-temporal exploration of OSM data on a global scale by using the ohsome API to aggregate the data of selected features into a set of globe spanning hexagonal grids in a monthly resolution. This allows for the analysis of the evolution of the data, provides insight into the quality and visual exploration history of OSM Data, and presents an opportunity to uncover interesting semantic connections.

 

ohsome API

The ohsome API is a HeiGIT technology based on the OSHDB that is under continuous development to improve its features. It is a REST-based API that enables extraction and analysis of complete OpenStreetMap’s data history via HTTP requests. The data are avaiable as CSV, JSON or GeoJSON to make OpenStreetMap’s data history more easily accessible for various kinds of data analytics tasks on a global scale.

Ohsome Quality analysT (OQT)

OQT is a service still under development that end users, i.e. humanitarian organisations and public administration, can use to access information on the quality of OSM data for their specific region and use-case. It is a web-based application that builds upon HeiGIT’s OSM analysis infrastructure ohsome, but also provides an API and command line interface. Further, it functions as a data integration tool that brings together a variety of intrinsic and extrinsic OSM data quality metrics.

ohsome Dashboard

The ohsome dashboard, a HeiGIT technology building upon the ohsome API, is a dashboard that allows you to perform analyses of OpenStreetMap’s full-history data without the need of programming skills by generating accurate statistics and plotting them directly in the dashboard. Statistics about the historical development of OpenStreetMap data can be selected for any arbitrary region or time period, custom filtering of all available OpenStreetMap tags and types can be applied, and results can also be grouped in various different ways.

ohsome2X

ohsome2X is an opensource utility used to create the data for time-series maps of OSM’s historic development. Internally, we also use the tool to create time-series data for HeiGIT’s ohsome OSM History Explorer OhsomeHeX. With ohsome2X, you will be able to create your own OSM History Stats Maps, for your areas of interests. The tool uses HeiGIT’s ohsome API to query the relevant statistics and combines the results with any input of polygons (admin areas, regular grids, etc). For small tasks, you can upload a geojson; for larger tasks you can link to a PostGIS DB and process your data iteratively in digestible chunks.

ohsome2label

The GIScience project ohsome2label, with support from HeiGIT, uses historical OpenStreetMap objects as machine learning training samples to create a flexible label preparation for satellite machine learning applications. With the help of HeiGIT’s ohsome API all kinds of geospatial objects may be retrieved from OSM.

Ongoing Projects


Global Exposure Data for Risk Assessment

The Global Exposure Data for Risk Assessment project funded by HeiGIT aimed at developing an API mapping opensource global dataset of potentially vulnerable features to natural disasters per United Nation’s Sendai Framework (disaster preparedness). The aggregated data can be used by different disaster teams of the Emergency Response Coordination Centre for early response and risk assessment. The extraction of this data is accomplished through the ohsome API provided by HeiGIT. The project is currently in phase II with possible extension. The idea is to make it an integral part of the existing disaster risk assessment pipeline within the JRC ecosystem.

Healthcare Access Analysis

The Healthcare Access Analysis project is a collaboration between the ORS and healthsites.io funded by HeiGIT. By analyzing and comparing the accessibility of healthcare facilities around the globe, by assessing data quality, and by detecting potential spatial patterns therein, the best way of transport to facilities can be determined. Healthsites.io provides the input data, which is then analyzed with the help of ORS’s isochrone functionality.


Missing Maps

HeiGIT and the GIScience Research Group at Heidelberg University are supporting the Missing Maps project since 2015. The HeiGIT team supports Missing Maps in monitoring and visualizing its achievements and impact using information from the HOT Tasking Manager and our ohsome framework. We advance current research about OSM and it’s application in disaster risk reduction and disaster management and make this available to the wider public through joint publications, presentations and partnerships.

Healthsites Quality

The Healthsites Quality project funded by HeiGIT aims to develop a framework for assessing the quality of health-related data in OSM in terms of completeness, accuracy (temporal & technical), and trustworthiness, and for visualizing the development of OSM health data over time. This is accomplished by comparing OSM health data with health data from other sources (i.e. the WHO, healthsites.io, KEMRI, etc.). By providing critical information on the completeness and reliability of health data on OSM, targeted improvement of humanitarian aspect is accomplished. The project is based on HeiGIT’s ohsome API and supported with knowledge, ideas, and implementation tasks.

Waterproofing Data

The GIScience Waterproofing Data project is supported by HeiGIT and uses HeiGIT’s ohsome API. It aims to investigate the governance of water-related risks by rethinking flood data production and flow. The focus of this project lies on social and cultural aspects of data practices thus helping to transform and build more sustainable, flood resilient communities.

meinGrün

In the meinGrün project, a GIScience project with support of HeiGIT and using the openrouteservice, partners from science, municipal practice and business are developing the basis for novel, interactive information services. The aim is to describe green spaces in cities in greater detail and show how they can be easily accessed. Users of green spaces can rate them and city administrations receive tips on potential for improvement. Furthermore, a routing service for pedestrians and cyclists is in development which recommends healthy routes that avoid high solar radiation, unnecessary noise, and that focus on the presence of vegetation.

WIN project “Shared Data Sources”

The WIN project “Shared Data Sources” uses OpenStreetMap as an example to investigate how individual cognitive processes affect convergence on a collective scale. Part of the analysis is to estimate whether local knowledge is present in the OSM data. HeiGIT supports this project by providing its OSHDB API which allows for the analysis of OSM tag changes and contributor statistics.

IDEAL VGI

The GIScience project IDEAL VGI (Information Discovery from Big Earth Observation Data Archives by Learning from Volunteered Geographic Information) aims to identify and assess the importance, uncertainty, and quality of different OSM derived features in order to promote relevant semantic OSM content. Furthermore, the integration of supporting complementary VGI data streams, developing machine learning for remote sensing image classification, and automatically refining and assigning OSM tags are important goals. HeiGIT supports this project by providing both its OSHDB technology and technical knowledge.

OSM Landuse Landcover

The GIScience project OSM Landuse Landcover is a WebGIS application exploring landuse and landcover information in the OpenStreetMap database. Missing OSM data (gaps) in Europe are filled (ongoing) using data derived from Sentinel-2 10 m RGB imagery and deep learning methods. The project is support by HeiGIT and uses the HeiGIT technology ohsome API.

Climate Action California

The GIScience project “Shaping Climate Action in a Sound Way – Case Study Baden-Württemberg/California” is a pilot study within the Heidelberg Center for the Environment’s project “Climate Action Science” supported by HeiGIT. It aims at analyzing the accessibility and quality of geoinformation of greenhouse gases from measuring networks, government data, and citizen science. The project examines the usefulness of OSM data for the estimation of greenhouse gas emissions. OSM tags are analyzed and aggregated according to the Intergovernmental Panel on Climate Change (IPCC) Emission Factor Database (EFDB). The OSM data extraction uses HeiGITs ohsome API technology.

Completed Projects

Mapping COVID-19 Research

HeiGIT’s “Map of Hope” provides a geographical overview of planned, ongoing, and completed clinical trials regarding COVID-19. The global scientific and medical communities have immediately responded to the new threat with focused research activities that in turn have led to clinical trials and scientific publications worldwide. This project aims to provide an up-to-date overview of these activities with links to the underlying sources as well as many informative maps to track the spread of the virus. Medical expertise is provided by Prof. Dr. Markus Ries from the Center for Pediatrics and Adolescent Medicine, University Hospital Heidelberg with support from Dr. Konstantin Mechler and Donna Smith. The data pre-processing and the service deployment is done by HeiGIT and geocoding was accomplished using HeiGIT’s openrouteservice API.

TARDUR – Temporal Access Restrictions for Dynamic Ultra-Flexible Routing

The mFUND project, with support from HeiGIT’s openrouteservice Team, integrated information about temporal road access/restrictions in ORS and GraphHopper with the aim of enabling time-dependent and therefore more accurate routing by developing an algorithm that takes time constraints into account when calculating routes. The algorithm was then implemented in the commercial platform GraphHopper and the HeiGIT openrouteservice technolgy. The project was funded by the Federal Ministry of Transport and Digital Infrastructure as part of the mFUND initiative.

DFG-OSM-Quality

The GIScience DFG-OSM-Quality project aimed at fostering research about data quality measures related to OSM by creating a collection of OSM data quality measures and describing the “Fitness for Purpose” of OSM data. The goal was to create a repository for OSM data quality measures. This was accomplished partially by relying on HeiGIT’s OSHDB as well as technical support provided by HeiGIT.

LandSense

The aim of the LandSense project, a collaboration of GIScience, HeiGIT, and several other partners, was to build a far-reaching citizen observatory for Land Use and Land Cover (LULC) monitoring that would also function as a technology innovation marketplace. Integrating these citizen-driven in-situ data collections with established authoritative and open access data sources helpes to reduce costs, extend GEOSS and Copernicus capacities, and supports comprehensive environmental monitoring systems. The project uses HeiGIT’s ohsome API.