A climate event portal for knowledge discovery
Partners: Bayerische Klimaforschungsnetzwerk (BayKlif): Prof. Dr. Annette Menzel, Technische Universität München, Prof. Dr. Dieter Kranzlmüller, Leibniz-Rechenzentrum, Prof. Dr. Susanne Jochner-Oette, Katholische Universität Eichstätt-Ingolstadt, Prof. Dr. Jörg Ewald, Hochschule Weihenstephan-Triesdorf, Prof. Dr. Wolfgang W. Weisser, Technische Universität München, Prof. Dr. Ulrike Ohl, Universität Augsburg, Prof. Dr. Arne Dittmer, Universität Regensburg, Prof. Dr. Henrike Rau, Ludwig-Maximilians-Universität München
Contact: Liqiu Meng
The PhD or post doc researcher will be working with multidisciplinary teams in a Research Cluster on “Bavarian Synthesis Information Citizen Science Portal for Climate research and Scientific Communication” (BAYSICS - Bayerisches Synthese-Informations-Citizen Science Portal für Klimaforschung und Wissenschaftskommunikation).
Project webpage: www.bayklif.de/verbundprojekte/baysics/teilprojekt-3/
A Visual Computing Platform for the Industrial Innovation Environment in Yangtze River Delta
The aim of the joint project is to develop a visual computing platform dedicated to monitoring the dynamic innovation and investment ecosystem in Yangtze River Delta. The platform combines the power of intuitive human vision with that of analytical computing, thus serves as an enabler for users to explore the interactions between the regularly updated geo-infrastructure data and the continuously evolving geo-economic data, and to preview the complex influence factors of industrial innovation. The anticipated platform will be prototypically implemented with three extendable components – a geovisualization toolkit, a geospatial analytical computing toolkit and a geo-economic event collector. These components will be tailored to the needs and knowledge profiles of three target groups who are involved or interested in the innovation ecosystem in Yangtze River Delta – governmental agencies, industrial enterprises and investors.
Geospatial Information Services for Smart Cities Driven by Big Data
Within this cooperation, Chair of Cartography TUM conducts a research on integrating multiple sources of geo-referenced urban data to derive valuable geospatial services for smart city applications. As a result, an open geo-collaborative portal with a set of interactive services will be developed. The portal will contain an interactive user interface, an extendable visualization toolkit and an analytical toolkit. The anticipated components will serve as descriptive, diagnostic, predictive and prescriptive tools for city management. The functionalities of the portal will be developed during the series of workshops and user tests with three target groups – urban citizens, domain experts and decision makers. Each target group will participate in the knowledge construction process in a two-fold role – as information receiver and data contributor.
Semantically Enriched and User Orientated Multi-Modal Navigation
The Federal Ministry of Transport and Digital Infrastructure (BMVI) leads a data-oriented R&D- funding programme for the period 2016 to 2020 in a form of the modernity fund (mFUND). Within this programme, Chair of Cartography TUM conducts a research on early developments of digital innovations in mobility. Ongoing project aims to show the added value of extending the existing traffic data with semantic information. The pre-study examines the possibilities of (1) the enrichment of the multimodal traffic database with semantic information to be gained from user behaviour data, Volunteered Geographic Information (VGI) and social media and (2) development of the user-oriented multimodal navigation service. As a result, a demo app version will be developed to present the following scenarios relevant for the urban and mobility design: multiscale representation of transportation nodes, automatic detection of the smombie danger and managing hotspots of negative events in the cities. Semantically enriched, multimodal and user-oriented navigation service will be evaluated in two test areas of Berlin and Munich.
Sense-Making Image Mapping from Remotely Sensed GLC30m
Contact: Ekaterina, Chuprikova
This joint project between the Lehrstuhl für Kartographie at TUM (TUM-LfK) and the National Geomatics Centre of China (NGCC) aims to visually empower the uniquely available GLC30m (global land cover of 30m resolution) at NGCC with the uniquely available attentionguiding design framework of concise image maps at TUM-LfK. Both partners are committed to developing a globally accessible open-source platform for GLC30m. The platform will provide a metadata catalogue and (semi)automatic value-adding services to enable the continuous validation, updating and efficient use of GLC30m incl. visual query, visual narratives of query results and creation of web-based image maps for selected applications and target groups. Across the fields of remote sensing, geoinformatics, visual perception and neuropsychology and cartography, innovative methods are anticipated to (a) interlace the first-hand information from raster images with the second-hand information from map symbols and labels at multiple visual levels rather than just a figure-ground composition; (b) unite the pixel resolution reflecting the degree of ground-truth with the map scale reflecting the cognitive abstraction in the visual storytelling; (c) convert the globally accessible land cover types into personalized visualizations for efficient data understanding.
Event detection and visualization of Volunteered Geographic Information (VGI)
Contact: Polous, Khatereh
With rapid spread concept that uses web as “participatory platform”, assessing spatio-temporal processes and detailed change mapping, which highly demand accurate and up-to-date data, has become more affordable. Many studies have been already conducted for detection, monitoring and visualization of changes from multi-temporal, multi-spectral and multi-sensor data. But, it is less discussed how the detected changes should be decomposed and formulated to reveal an event. The aim of this study is to detect location-based events from Volunteered Geographic Information (VGI) in Munich. The work concentrates on detection and pattern recognition of events, which are bound to a specific time and place from delivered information by internet users.