Universitätssiegel
Adresse
Geographisches Institut
Im Neuenheimer Feld 368
69120 Heidelberg
 
 
Sekretariat
Bettina Knorr
Im Neuenheimer Feld 368
69120 Heidelberg
 
Kontaktinformation
knorr@uni-heidelberg.de
Tel: +49 (0) 6221 54-5560
Fax: +49 (0) 6221 54-4529
 
Besuchsinformation
Zimmer 108, 1. OG
Bürozeiten:
Mo–Do, 9:00–12:00 Uhr
 
Institutionelle Zugehörigkeiten
HCE – Heidelberg Center for the Environment

IWR – Interdisciplinary Center for Scientific Computing
 
Mitgliedschaften
Humanitarian
OpenStreetMap
missing maps
AGILE – Logo
OSGeo GeoForAll
OGC – Logo
ISDE – Logo
GeoIT
Geomer-mrn-Logo
 

Professur für Geoinformatik / GIScience (GIS)

Titelbild

Die Abteilung Geoinformatik betreibt Grundlagenforschung und angewandte Forschung im Bereich GIScience und Geoinformatik. Dabei liegt ein Fokus auf der Untersuchung nutzergenerierter Geoinformationen (VGI, Crowdsourcing, Citizen Science). Zu diesem Zweck entwickeln wir innovative Methoden und Analyseverfahren u.a. in den Bereichen Humanitäre Hilfe (Katastrophenmanagement), Smart Mobility und Big Spatial Data Analytics (VGI Datenqualität etc.). Das „Heidelberg Institute for Geoinformation Technology“ (HeiGIT), dessen Aufbau aktuell von der Klaus Tschira Stiftung unterstützt wird, erlaubt uns dabei, die in der Forschung erlangten Erkenntnisse in praktische Lösungsansätze umzusetzen. Zudem unterstützen wir die Lehre in unseren Geographie-Studiengängen in Form eines breiten Kursangebotes - im Master Geographie ist dabei die Wahl eines ausgewiesenen Schwerpunktes "Geoinformatik" möglich.

Beachten Sie bitte unsere offenen Stellenangebote.

Aktuelle Nachrichten

Tagesaktuelle Nachrichten aus unserer Forschungsgruppe finden Sie auf giscienceblog.uni-hd.de (dieser ist auch als RSS-Feed erhältlich). Unsere Publikationen in wissenschaftlichen Journalen und Beiträge auf Konferenzen finden sich jeweils auf eigenen Seiten. Sie können uns ebenfalls auf Facebook und Twitter folgen.

18.06.2019 10:29
Estimating tree height from TanDEM-X data at the northwestern Canadian treeline

A new paper on tree height estimation from TanDEM-X data has just been published in Remote Sensing of Environment. The article finds that tree height can be predicted using TanDEM-X metrics (backscatter, bistatic coherence, and interferometric height) in the sparse forest patches of the Arctic treeline zone at the transition from forest to tundra. Taking [...]

14.06.2019 09:56
3DGeo at the Geospatial Week 2019

This week, the 3DGeo participated in the ISPRS Geospatial Week 2019 with two presentations among the sessions of the Laser Scanning Workshop with many interesting talks and poster. Presentations were given by Ashutosh Kumar in the Machine Learning Session and Katharina Anders in the Change Detection Session. Highlight: The work by Ashutosh Kumar on feature relevance in [...]

07.06.2019 11:57
The potential of Open Geospatial Data to address the Sustainable Development Goals- Geospatial World Magazine Article on how HOT and HeiGIT are supporting current approaches

Geospatial data is key for empowering citizens around the globe and to achieve the SDGs— if geodata is made openly available and easy to be put to use. The Humanitarian OpenStreetMap Team (HOT) is in this regard coordinating and supporting humanitarian action and community resilience through open mapping. The GIScience Research Group has supported HOT’s work [...]

06.06.2019 13:31
Constraints in multi-objective optimization of land use allocation – Repair or penalize?

Land is a spare resource so it makes sense to think about how to use it most efficiently. This leads to the problem of land use allocation under consideration of trade-offs. Multi-objective optimization algorithms are a tool quantify the trade-offs by estimating the Pareto-optimal land use allocations. Often, constraints in the solution space have to [...]

05.06.2019 18:15
Comparison of Three Algorithms for the Evaluation of TanDEM-X Data for Gully Detection in Krumhuk Farm (Namibia)

Namibia is a dry and low populated country highly dependent on agriculture, with many areas experiencing land degradation accelerated by climate change. One of the most obvious and damaging manifestations of these degradation processes are gullies, which lead to great economic losses while accelerating desertification. The development of standardized methods to [...]

05.06.2019 15:22
Understanding human mobility from social media data for epidemic surveillance in urban environment

Vector-born diseases – such as Malaria, Dengue or Zika are serious health hazards in tropical regions. The outbreaks show high temporal and spatial variability. For example, the number of dengue cases in the state of São Paulo increased by 2,124% in the first 11 weeks of 2019 (up to March 16, 229,064 cases were reported), [...]

05.06.2019 10:50
Support the global OSM Climate Protection Map at WorldEnvironmentDay

Today, June 5 is the #WorldEnvironmentDay. World Environment Day is the United Nations day for encouraging worldwide awareness and action to protect our #environment. Above all, World Environment Day is the “people’s day” for doing something to take care of the Earth. That “something” can be local, national or global. This is a good opportunity to [...]

31.05.2019 19:08
The Triangle of Shared Data Sources

Todays data production, maintenance, and use have changed in the last years.  While these tasks were reserved to professionals until a few years ago, the situation has changed.  This is no different in the geographical domain. Volunteers gather general information in Wikipedia and geographical information in OpenStreetMap.  Twitter users provide not only text snippets but [...]

31.05.2019 16:14
Paper on High-Frequency 3D Geomorphic Observation using Hourly LiDAR Time Series

Can you imagine how much sand is being moved on the beach in the course of a week? Did you ever observe truckloads of sand being transported on the beach in the absence of storms and bulldozers? It is hardly possible to estimate to the naked eye, but can be quantified with permanent terrestrial laser [...]

31.05.2019 16:12
Paper on Analysis of Feature Relevance in Deep Learning for 3D Point Cloud Classification

A paper investigating the relevance of (pre-calculated) features for 3D point cloud classification using deep learning was just published in the ISPRS Annals of Photogrammetry and Remote Sensing. The study presents a non-end-to-end deep learning classifier for 3D point clouds using multiple sets of input features and compares it with an implementation of the state-of-the-art [...]

GIScience Teamfotos
GIScience Team

GIScience-Team (Aufnahme nach einem Jour-Fixe-Meeting in 2017)

GIScience Team

GIScience-Team (Aufnahme nach einem Jour-Fixe-Meeting in 2014)

GIScience Team

GIScience-Team bei einem Retreat in Trifels-Annweiler im Februar 2013

GIScience Team

GIScience-Team (Aufnahme nach einem Jour-Fixe-Meeting in 2012)

In Memoriam Peter Meusburger
Peter Meusburger

Am 18. Dezember 2017 starb viel zu früh Prof. Dr. Dr.h.c. Peter Meusburger. Wir trauern um einen großen Wissenschaftler, Lehrer und geschätzten Kollegen. Mitte der 90er etablierte er den ersten GIS-Pool an der Universität Heidelberg und startete GIS-bezogene Forschungsaktivitäten. Wir werden Ihn nicht vergessen. (Trauermeldung der Universität)

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Letzte Änderung: 21.05.2019
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