Today the time has come: The “meinGrün” web app for Dresden and Heidelberg is officially launched.
With the mobile application you can (re-)discover known and unknown green spaces and find a pleasant route to those. Users can learn about the functions of the app via virtual scavenger hunt. The app is the result of the [...]
Tag Archive 'remote sensing'
Exploration of OpenStreetMap Missing Built-up Areas using Twitter Hierarchical Clustering and Deep Learning in Mozambique
Posted in Crowd Analyser, OSM, Publications, Research, VGI Group on Jun 8th, 2020
Accurate and detailed geographical information digitizing human activity patterns plays an essential role in response to natural disasters. Volunteered geographical information, in particular OpenStreetMap (OSM), shows great potential in providing the knowledge of human settlements to support humanitarian aid, while often the availability and quality of OSM remains a major concern. The majority of existing [...]
GIScience Heidelberg at Annual Meeting of DGPF
Posted in Events, Lidar Group, Publications on Mar 9th, 2020
Last week, members of GIScience Heidelberg participated in the 40th annual meeting of the DGPF (German association for photogrammetry and remote sensing) in Stuttgart, Germany.
Presentations were contributed by PhD students Lukas Winiwarter and Katharina Anders (3DGeo Research Group), as well as former GIScience fellow Jun-Prof. Dr. René Westerholt. Read up on the presented topics in [...]
NASA uses Openrouteservice for study on disaster response times
Posted in External Projects, Press release on Jan 13th, 2020
According to a recent post by NASA, researchers at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, calculated the time that could have been saved if ambulance drivers and other emergency responders had near-real-time information about flooded roads, using the 2011 Southeast Asian floods as a case study. This was the first NASA study to [...]
New DFG project: IdealVGI - Deep Learning with OSM
Posted in OSM, Press release, Research, VGI Group on Nov 4th, 2019
Recently a new DFG project proposal was accepted to the GIScience Research Group Heidelberg within the DFG priority programme VisVGI (Volunteered Geographic Information: Interpretation, Visualisation and Social Computing” [SPP 1894]). It is joint collaboration project together with Prof. Begüm Demir from TU Berlin.
IDEAL-VGI: Information Discovery from Big Earth Observation Data Archives by Learning from Volunteered [...]
MS Wissenschaft beendet Tour zur Künstlichen Intelligenz - aber weiter geht es im Web - auch mit unserem Exponat zu Trainingsdaten für Satellitenbilder
Posted in Events, Press release, Research on Oct 31st, 2019
Gerade beendete die MS Wissenschaft ihre Tour durch 31 Städte zwischen Berlin und Wien in diesem Wissenschaftsjahr zum Thema “Künstliche Intelligenz“.
85.000 Menschen – Schulklassen, Familien und Interessierte aller Altersklassen – besuchten die Ausstellung zum Thema lernende Computersysteme an Bord des Wissenschaftsschiffs.
Zu den Besonderheiten der Ausstellung zählten die zahlreiche Dialog- und Mitmachangebote an Bord.
Mit an Board [...]
Estimating OpenStreetMap Missing Built-up Areas using Pre-trained Deep Neural Networks
Posted in Events, Publications, VGI Group on Jun 26th, 2019
Recently a new paper about Estimating OpenStreetMap Missing Built-up Areas using Pre-trained Deep Neural Networks (DNNs) has been presented at the AGILE GIScience conference 2019 in Cyprus.
Although built-up areas cover only a small proportion of the earth’s surface, these areas are closely tied to most of the world’s population and the economic output, which makes the [...]
Comparison of Three Algorithms for the Evaluation of TanDEM-X Data for Gully Detection in Krumhuk Farm (Namibia)
Posted in 3D, Digital Earth, Lidar Group, Publications, Research on Jun 5th, 2019
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 [...]
Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art
Posted in 3D, Lidar Group, Publications, Research on Mar 25th, 2019
The recent, sharp increase in the availability of data captured by different sensors, combined with their considerable heterogeneity, poses a serious challenge for the effective and efficient processing of remotely sensed data. Such an increase in remote sensing and ancillary data sets, however, opens up the possibility of utilizing multimodal data sets in a joint [...]
Machine Learning for Space and Earth Observation Data (ML-SEOD) 2019 at ICCSA
Posted in Events on Jan 29th, 2019
Machine Learning for Space and Earth Observation Data (ML-SEOD) 2019
Call for Papers
The Earth and Space environments are being monitored by an unprecedented amount of sensors: Earth observation satellites, sensor networks, telescopes working in different wavelengths, human records of Earth and Space events, etc. This generates a huge amount of raw data that must be processed [...]