Tag: landuse
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EuroGEOSS Workshop: Crowdsourcing Land Use Map Validation
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…
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MeinGrün – project proposal approved (mFund BMVI)
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…
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A discussion of crowdsourced geographic information initiatives and big Earth observation data architectures for land-use and land-cover monitoring
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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Associating OpenStreetMap tags to CORINE land-cover classes using text and semantic similarity measures
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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LandSense Innovation Challenge
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…
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Abteilung Geoinformatik: Studentische Hilfskräfte GIS gesucht (auch Praktika)
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 humanitäre Hilfe (Geoinformatik für Katastrophenmanagement) z.B. MapSwipe Analytics etc. Intelligente…
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ECSA Webinar on #citizenscience for monitoring urban landscape dynamics with GIScience Heidelberg
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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OSMlanduse.org + Remote Sensing = New conterminous land use data set for Germany released – filling gaps in OSM through machine learning
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…
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Context-Based Classification of Urban Blocks According to Their Built-up Structure
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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LandSense is Project of the Week @ “Doing It Together Science”.
The EU H2020 project LandSense (A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring) has been featured as project of the week by “Doing It Together Science“. http://togetherscience.eu/blog/project-of-the-week-10-landsense. Thanks to our partners at IASA etc. for this! In addition to organizing mapathons and related research research activities, in the context of…
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Open land cover from OpenStreetMap and remote sensing
In a recently published study (1), we produced a web based land use land cover (LULC) product based on OSM tags which are constantly updated by contributors/volunteers, and present a Remote Sensing based solution when tags were absent for a test site. We harness the combined benefit of an open source and ever-growing machine generated…
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LandSense Questionnaire
http://bit.ly/2upEw7a <- LandSense Questionnaire LandSense aims to develop an online marketplace where companies that develop IT solutions using LULC data in one of three themes – urban, rural, and forestry, can acquire this information and further develop their products. By completing this questionnaire, you help us develop and further enhance our platform. Thank you very…