Environmental Mapping Based on Spatial Variability and Computational Vision Models

dc.contributor.author	Kovalevskaya, Nelley
dc.contributor.author	Mitrophanova, Elena
dc.contributor.editor	Gnauck, Albrecht
dc.contributor.editor	Heinrich, Ralph
dc.date.accessioned	2019-09-16T09:33:42Z
dc.date.available	2019-09-16T09:33:42Z
dc.date.issued	2003
dc.description.abstract	Environmental maps show the probable environmental states of different types of land use or development of landscape in a geographic context. Remotely sensed data are particularly efficient for environmental mapping in order to outline major environmental types. Novel models of piecewise-homogeneous V images are used in environmental mapping to segment real images. The models consider both an image and a land cover map. Such a pair constitutes an example of a Markov random field specified by a joint Gibbs probability distribution of images and maps. Addition of spatial attributes v appears to be necessary in most areas where the differences in spatial data between regions in the image occur.	de
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/27113
dc.publisher	Metropolis
dc.relation.ispartof	The Information Society and Enlargement of the European Union
dc.relation.ispartofseries	EnviroInfo
dc.title	Environmental Mapping Based on Spatial Variability and Computational Vision Models	de
dc.type	Text/Conference Paper
gi.citation.publisherPlace	Marburg
gi.conference.date	2003
gi.conference.location	Cottbus
gi.conference.sessiontitle	Applications - Geographical Information Systems

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