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|Title:||A satellite data set for tropical forest area change assessment|
|Authors:||BEUCHLE Rene'; EVA Hugh; STIBIG Hans-Jurgen; BODART Catherine; BRINK Andreas; MAYAUX Philippe; JOHANSSON Desirée; ACHARD Frederic; BELWARD Alan|
|Citation:||INTERNATIONAL JOURNAL OF REMOTE SENSING vol. 32 no. 22 p. 7009-7031|
|Publisher:||TAYLOR & FRANCIS LTD|
|Type:||Articles in Journals|
|Abstract:||A database of largely cloud-free (less than 2.5% of all sites have more than 5% cloud cover), geo-referenced, 20 km by 20 km sample sites of 30 m resolution optical satellite imagery has been prepared for the 1990 and 2000 epochs. This spans the tropics with a systematic sample located at the degree confluence points of the geographic grid. The resulting 4 016 sample pairs are to be used to measure changes in the area of forest cover between the two epochs. The primary data source was the National Aeronautics and Space Administration Global Land Survey (GLS) datasets. Visual screening of GLS images at all 4 016 confluence points from each date identified 2 868 suitable pairs where no better alternatives exist (71.6% of the sample). Better alternatives could be found for 26.6% of the sample, substituting cloudy or missing GLS datasets at one or the other epoch or both (GLS-1990 or GLS-2000). Gaps were filled from the United States Geological Survey (USGS) Landsat archives (1 070 samples), data from other Landsat archives (53 samples) or with alternatives to Landsat, i.e. 15 samples from Satellite Pour l¿Observation de la Terre (SPOT). This increased the effective number of sample pairs to 3 945 representing 98% of all target samples. No suitable image pairs were found for 71 confluence points, which were not randomly distributed, but mostly concentrated in the Congo basin, where around 15% of the region remains un-sampled. Variations in date of image acquisition and geometric fidelity are documented. Results highlight the importance of combining systematic data processing schemes with targeted image acquisition and archiving strategies for global scale applications such as deforestation monitoring and show that by replacing cloudy or missing GLS data with alternative imagery, the overall coverage of the sample sites within the ecological zones ¿Tropical rainforest¿ and ¿Tropical mountain system¿can be improved by 16%.|
|JRC Institute:||Institute for Environment and Sustainability|
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