Posted in Events on Oct 22nd, 2018
Last week our team member Dr. Michael Schultz successfully defended his PhD Defence about
Tropical deforestation monitoring using Landsat time series and breakpoint detection
at Wageningen University and Research (WUR). It was supervised by Prof. Dr M. Herold (Professor of Geo-information Science and Remote Sensing at Wageningen University & Research). We congratulate cordially! Keep up the good [...]
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Posted in Events, Land use, OSM, Services on Oct 4th, 2018
At the recent EuroGEOSS Workshop in Geneva, LandSense researchers from IIASA and Heidelberg University hosted an interactive mapping session to showcase the power of crowdsourcing for map validations as announced earlier.
Using the openly available Land Cover Validation Platform (LACO-Wiki), participants collaboratively validated a land use and land cover map of Geneva, which brings together data from [...]
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Posted in Research, Services on Sep 29th, 2018
Informationen und Navigation zu urbanen Grünflächen in Städten – meinGrün
Neues mFund Kooperations-Projekt meinGrün wird vom BMVI gefoerdert.
Problemstellung
Um in Städten trotz Wachstum und Nachverdichtung eine hohe Lebensqualität zu sichern, spielen Grünflächen eine essentielle Rolle, da sie sich positiv auf Stadtklima und Biodiversität auswirken und als Orte der Naturerfahrung und Entspannung dienen. Bürgerinnen und Bürger sollten daher [...]
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Posted in Publications, VGI Group on Jun 3rd, 2018
The effective monitoring of land-use and land-cover changes (LULCC) is a basic requirement for understanding socio-enviromental processes of local to global scales. Remote sensing data and methods have long been established as the most effective approach for monitoring LULCC. The potential for further increasing the effectiveness of this approach is proportional to the astonishingly large [...]
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Posted in Events, OSM, Publications, VGI Group on May 12th, 2018
With the aim of rapidly estimating the updated state of the CORINE land-cover map at the frequency with which the OpenStreetMap (OSM) dataset is edited and extended, we propose an approach for automatically associating widely used OSM tags to Level 1 and Level 2 CORINE land-cover classes. This association is probabilistic and is undertaken based [...]
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Posted in Events on Mar 8th, 2018
The LandSense Team is thrilled to announce the first LandSense Innovation Challenge, which targets individuals, web-entrepreneurs, start-ups and SMEs coming from all participating H2020 countries, to present innovative IT solutions in addressing one of the three LandSense domains: Urban Landscape Dynamics, Agricultural Land Use, and Forest & Habitat Monitoring (learn more here).
The focus of this challenge [...]
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Posted in Jobs on Feb 7th, 2018
Die Abteilung Geoinformatik sucht Studentische Hilfskräfte zur Unterstützung in mehreren hoch aktuellen Forschungsbereichen in einem interdisziplinären dynamischen Team, u.a. z.B. für:
Big Spatial Data Analytics z.B. OpenStreetMap History Analysen, Social Media Analytics etc. z.B. http://ohsome.org
Landnutzungsklassifikation auf Basis von OpenStreetMap, Satellitenbildern, etc. z.B. http://OSMlanduse.org
Disaster-Management für [...]
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Posted in Events on Jan 27th, 2018
Join the next ECSA webinar on “Citizen Science for monitoring urban landscape dynamics”!
The European Citizen Science Association (ECSA) will host a webinar on the topic of “Citizen Science for monitoring urban landscape dynamics”. The webinar will include two talks:
Assessing urban green space in Vienna (by Gebhard Banko and Barbara Birli from the Austrian Environmental [...]
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Posted in OSM, Publications, Services, VGI Group on Jan 19th, 2018
Land use data created by humans (OSM) was fused with satellite remote sensing data, resulting in a conterminous land use data set without gaps. The first version is now available for all Germany at OSMlanduse.org.
When human input (OSM data) was absent a machine generated missing land use information learning from human inputs and using remote [...]
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Posted in Publications on Jan 16th, 2018
A recently published paper presents an approach for classifying urban blocks according to their built-up structure based on high-resolution spaceborne InSAR images. Most attributes considered in the classification describe the geometric structure and spatial disposition of the polygon and line features extracted from each block. The feature extraction is carried out on two intensity images [...]
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