{"data":{"id":"10.6084/m9.figshare.1008322.v4","type":"dois","attributes":{"doi":"10.6084/m9.figshare.1008322.v4","prefix":"10.6084","suffix":"m9.figshare.1008322.v4","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Vorel, Jakub","nameType":"Personal","givenName":"Jakub","familyName":"Vorel","affiliation":[],"nameIdentifiers":[]},{"name":"Grill, Stanislav","nameType":"Personal","givenName":"Stanislav","familyName":"Grill","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Land use change propensity maps"}],"publisher":"Taylor \u0026 Francis","container":{},"publicationYear":2015,"subjects":[{"subject":"Microbiology"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Neuroscience"},{"subject":"59999 Environmental Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Earth and related environmental sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Earth and related environmental sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"39999 Chemical Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Chemical sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Chemical sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Ecology"},{"subject":"20199 Astronomical and Space Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Physical sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Physical sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Sociology"},{"subject":"FOS: Sociology","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Sociology","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"69999 Biological Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"Cancer"},{"subject":"Inorganic Chemistry"}],"contributors":[],"dates":[{"date":"2015-11-16","dateType":"Created"},{"date":"2017-11-01","dateType":"Updated"},{"date":"2015","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1080/17445647.2014.911709","relatedIdentifierType":"DOI"},{"relationType":"IsIdenticalTo","relatedIdentifier":"10.6084/m9.figshare.1008322","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["22183642 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Land-use control and planning instruments face new challenges amid growing pressure for urbanization and annexation of valuable agricultural land and natural areas. This paper presents the land-use change propensity map, which shows the local potential for specific land-use changes. Propensity is derived empirically on the basis of historical land-use changes, with an explicit evaluation of characteristics that contributed to land-use change. Each step in creating a propensity map is described: selecting data that best represents land-use changes, identifying potential drivers of land-use change and the statistical inference of their impact on land-use change on the basis of observed historical land-use changes. The resulting propensity for land-use change is represented in the form of a binary logit model that evaluates the probability of specific land-use changes. A series of propensity maps for the territory of the Tábor microregion in the Czech Republic was created to demonstrate the method. The scale of the propensity maps is 1:310,000, and they cover an area of 1002 km\u003csup\u003e2\u003c/sup\u003e. Each propensity map represents the specific propensity for conversion from non-urban uses to family, multi-family and individual recreation houses. The evaluated propensity can be further compared to existing or proposed land-use regulations.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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