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 352154
Title Mapping East African tropical forests and woodlands : a comparison of classifiers
Author(s) Nangendo, G.; Skidmore, A.K.; Oosten, H. van
Source ISPRS Journal of Photogrammetry and Remote Sensing 61 (2007)6. - ISSN 0924-2716 - p. 393 - 404.
DOI https://doi.org/10.1016/j.isprsjprs.2006.11.003
Department(s) Forest Ecology and Forest Management
Wildlife Ecology and Conservation
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2007
Keyword(s) thematic mapper data - expert-system - classification - management - imagery - vegetation - terrain - biomass - uganda - model
Abstract In mapping the forest¿woodland¿savannah mosaic of Budongo Forest Reserve, Uganda, four classification methods were compared, i.e. Maximum Likelihood classifier (MLC), Spectral Angle Mapper (SAM), Maximum Likelihood combined with an Expert System (MaxExpert) and Spectral Angle Mapper combined with an Expert System (SAMExpert). The combination of conventional classifiers with an Expert System proved to be an effective approach for forest mapping. This was also the first time that the SAMExpert had been used in the mapping of tropical forests. SAMExpert not only maps with high accuracy, but is also fast and easy to use, making it attractive for use in less developed countries. Another advantage is that it can be executed on a standard PC set up for image processing. Combining the conventional classifiers (MLC and SAM) with the Expert System significantly improved the classification accuracy. The highest overall accuracy (94.6%) was obtained with SAMExpert. The MaxExpert approach yielded a map with an accuracy of 85.2%, which was also significantly higher than that obtained using the conventional MLC approach. The SAMExpert classifier accurately mapped individual classes. Of the four classes of woodland mapped, the Open Woodland (with Terminalia) and Wooded Grassland classes were more accurately mapped using SAMExpert. The Open Woodland had been previously identified by ecologists, but had never been mapped.
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