Paper
19 January 2006 Possibilities of MERIS for sub-pixel regional land cover mapping
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Abstract
The Medium Resolution Imaging Spectrometer, MERIS, on board of ENVISAT-1 fulfils the information gap between the current high and low spatial resolution sensors. In this respect, the use of MERIS full resolution data (300 m pixel size) has a great potential for regional and global land cover mapping. However, the spectral and temporal resolutions of MERIS (15 narrow bands and a revisit time of 2-3 days, respectively) might be further exploited in order to get land cover information at a more detailed scale. The performance of MERIS for extracting sub-pixel land cover information was evaluated in this study. An iterative linear spectral unmixing method designed to optimize the number of endmembers per pixel was used to classify 2 MERIS full resolution images acquired over The Netherlands. The latest version of the Dutch land use database, the LGN5, was used as a reference dataset both for the validation and for the selection of the endmembers. This dataset was first thematically aggregated to the main 9 land cover types and then spatially aggregated from its original 25m to 300m. Because the fractions of the different land cover types present in each MERIS pixel were computed during the aggregation, a sub-pixel accuracy assessment could be done (in addition to the traditional assessment based on a hard classification). Results pointed out that MERIS has a great potential for providing sub-pixel land cover information because the classification accuracies were up to 60%. The correct number of endmembers to unmix every pixel was adequately identified by the iterative linear spectral unmixing. Future research efforts should be put in making use of the high revisit time of the MERIS sensor (temporal unmixing).
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Raul Zurita-Milla, Michael E. Schaepman, and Jan G. P. W. Clevers "Possibilities of MERIS for sub-pixel regional land cover mapping", Proc. SPIE 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII, 59760Y (19 January 2006); https://doi.org/10.1117/12.627670
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KEYWORDS
Vegetation

Sensors

Image classification

Image resolution

Spatial resolution

Associative arrays

Accuracy assessment

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