Using MERIS on Envisat for land cover mapping in the Netherlands

This paper describes the results of a feasibility study to test the usefulness of MERIS for land cover mapping. The Netherlands was used as a test site because of its highly fragmented landscape. Results showed that the geometric and radiometric properties of the studied MERIS images of the Netherlands are suitable for land applications. Calculation of principal components and correlation coefficients revealed that the 15 MERIS bands provided a lot of redundant spectral information. For land applications, information came from the visible part of the spectrum on the one hand and from the near-... Mehr ...

Verfasser: Clevers, J G P W
Schaepman, Michael E
Mücher, C A
de Wit, A J W
Zurita‐Milla, R
Bartholomeus, H M
Dokumenttyp: Journal article
Erscheinungsdatum: 2007
Verlag/Hrsg.: Taylor & Francis
Schlagwörter: Institute of Geography / 910 Geography & travel
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27224198
Datenquelle: BASE; Originalkatalog
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Link(s) : https://www.zora.uzh.ch/id/eprint/62438/

This paper describes the results of a feasibility study to test the usefulness of MERIS for land cover mapping. The Netherlands was used as a test site because of its highly fragmented landscape. Results showed that the geometric and radiometric properties of the studied MERIS images of the Netherlands are suitable for land applications. Calculation of principal components and correlation coefficients revealed that the 15 MERIS bands provided a lot of redundant spectral information. For land applications, information came from the visible part of the spectrum on the one hand and from the near-infrared part on the other hand. In addition, the red-edge slope of the reflectance curve (in particular MERIS band 9 at about 708nm) provided supplementary information. The Dutch land use database LGN5 was used as a reference for classifications in this study after aggregation from 25 m to 300 m and recoding to 7 relevant land cover classes. For land cover classification best results in terms of classification accuracies were obtained for the image of 14 July 2003. For the seven land cover classes selected the overall classification accuracy was 67.2%. A multitemporal classification did not improve the overall classification accuracy.