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Proceedings Paper

Spatio-temporal robustness of fractional cover upscaling: a case study in semi-arid Savannah's of Namibia and Western Zambia
Author(s): Julian Zeidler; Martin Wegmann; Stefan Dech
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Paper Abstract

Vegetation cover is a key parameter in analyzing the state and dynamics of ecosystems. Africa's semi-arid savanna's are particularly prone to degradation, due to increasing population pressure as well as ongoing climatic changes. In most global land cover classifications inhomogeneous areas are aggregated into few discrete classes, delivering unsatisfying results in highly variable biomes, especially savanna's with their small scale patches of woody and herbaceous vegetation and bare soil. Fractional cover(FC) classifications, which provide an estimate of sub-pixel continuous cover percentages of underlying land cover classes, and are therefore an improved thematic representation, can deliver additional information for monitoring and decision making. Prior research demonstrated that multi-scale approaches are suitable for transferring en-detail information from a small subset to a larger study area via statistical up-scaling (e.g. Random Forest). In this case study the robustness of this up-scaling approach and the limits of the spatial and temporal transferability at the very high and intermediate resolution were analysed in the Caprivi Strip in Namibia and the adjacent Western Province of Zambia. The key research questions were to quantify i) the robustness of the upscaling, ii) the loss of accuracy depending on the lag in image acquisitions, iii) the loss of accuracy dependent on the time of image acquisition in the phenological cycle. To this end 12 Worldview(WV) and all usable Landsat TM and ETM+ images, covering all phases of the vegetation cycle were obtained. The analysis showed that continuous FC mapping is a highly suitable concept for semi-arid ecosystems with gradual transitions. The optimal time for WV acquisition was at the beginning of the dry season. The RMSE was unusable for LS images recorded in the rainy season between November and March, but otherwise it was usable even for larger lags up to a month, with deviations below 15%. As long as the spatial training subset(s) cover the whole occurring range of vegetation densities, comparably small WV scenes are sufficient to reliably scale to regional results.

Paper Details

Date Published: 25 October 2012
PDF: 10 pages
Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 85380S (25 October 2012); doi: 10.1117/12.970623
Show Author Affiliations
Julian Zeidler, Julius-Maximilians-Univ. Würzburg (Germany)
Martin Wegmann, Julius-Maximilians-Univ. Würzburg (Germany)
Stefan Dech, Julius-Maximilians-Univ. Würzburg (Germany)
Deutsches Zentrum für Luft- und Raumfahrt e.V. (Germany)

Published in SPIE Proceedings Vol. 8538:
Earth Resources and Environmental Remote Sensing/GIS Applications III
Shahid Habib; Ulrich Michel; Daniel L. Civco; David Messinger; Antonino Maltese; Manfred Ehlers; Karsten Schulz; Konstantinos G. Nikolakopoulos, Editor(s)

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