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Masaryk University

Project information

Dynamické mapovací metody orientované na řízení rizik a katastrof v éře velkých dat (gis4dis)

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Project Identification
LTACH-17002 (kod CEP: LTACH17002)
Project Period
4/2017 - 12/2019
Investor / Pogramme / Project type
Ministry of Education, Youth and Sports of the CR
MU Faculty or unit
Faculty of Science
Project Website
http://geogr.muni.cz/gis4dis
Keywords
GIS, big data, web map, crisis management, early warning, decision support, cartographic generalisation, adaptive cartography, cartographic visualization

The project is focused on collecting and processing data from different sources and their cartographic presentation in real time (ie. rapid mapping) for crisis management. Efficient methods will be developed for gathering, processing, integration and sharing of spatial data that can be used by entities involved in emergency situations - rescue system, state and local governments and others. These include sensor data from various types of sensor networks, volunteer geographic information (VGI), data obtained through social networking and others, which will be chosen according to their relevance to specific types of emergency situation. Our goal is a generation of cartographic representations from the data gathered that will be used as an effective tool to support the solution of crisis situation.

The project responds to the unresolved issue in the field of early warning and crisis management and builds on current trends of cartography in the era of big data. The amount of data available is constantly increasing, however such an amount of data is difficult to handle. The main benefit of the project is the development of methods for dynamic generation of maps for different regions and crisis events using methods of web cartography using appropriate rules for crisis management. The aim is to create a software environment for creating maps for crisis management in real time, which will be verified in both participating countries.

Publications

Total number of publications: 32

2020

2019

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