Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 441319
Title Evaluation of the variation in semantic contents of class sets on modelling dynamics of land-use changes
Author(s) Jansen, L.J.M.; Veldkamp, T.A.
Source International Journal of Geographical Information Science 26 (2012)4. - ISSN 1365-8816 - p. 717 - 746.
DOI https://doi.org/10.1080/13658816.2011.609989
Department(s) Land Dynamics
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) use change scenarios - central-america - igbp discover - multiscale - population - database - environment - validation - accuracy - patterns
Abstract Understanding the scale of interaction and the scale of different environmental and social processes is of paramount importance to define and explain the interaction of human-environment systems. There are three dimensions of scale: space, time and the organisational hierarchy as constructed by the observer. The latter is synonymous with the variation in semantic contents of data expressed as differences in categorisation. This dimension of scale has received little attention. In this article the relationship between the semantic contents of data and modelling dynamics is explored using two land-cover data sets for Romania, one based on the Land-Cover Classification System and the other as used in the EURURALIS study. Three levels of semantic contents of the LCCS data and the single semantic level present in the EURURALIS data are used to establish empirical relations between the land-cover class and its explaining factors. The analysis results show that the variations in semantic contents of data within one data set and between two data sets lead to different sets of spatial determinants for land cover. We did not recognise patterns when establishing the organisational hierarchy. Future policy and decision-making depend to a great extent on which organisational hierarchy is present in the data set used to formulate a policy or to make an informed decision. This would mean that if the same results would be found in other data sets using different models not only multi-scale but also multi-semantic analysis are needed in order to make meaningful predictions of spatially explicit land change.
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