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Time series analysis of optical remote sensing data for the mapping of temporary surface water bodies in sub-Saharan western Africa
Authors:EM Haas  E Bartholom  B Combal
Institution:aGlobal Environment Monitoring Unit, Institute for Environment and Sustainability, Joint Research Centre – European Commission, Via E. Fermi 2749, I-21027 Ispra (VA), Italy
Abstract:A map of temporary small water bodies (TSWB) at 1 km resolution was derived for the arid, semi-arid and dry sub-humid regions of sub-Saharan western Africa where the spatio-temporal distribution of actual surface water occurrence exhibits high inter- and intra-annual variability. Water bodies and humid areas have been mapped and characterized by the analysis of 10 daily small water bodies (SWB) maps based on SPOT VEGETATION (VGT) data spanning the period January 1999–September 2007. Further analysis of the SWB time series provided additional information about the seasonal recurrence of water bodies as well as their hydrological function. A map derived from a continuous time series assures the inclusion of temporary features, a clear advantage compared to other datasets, which are based on several single date observations. The method described in this paper targets at a rapid creation of TSWB maps based on the SWB time series for different time intervals and regions.An accuracy assessment has been carried out with a stratified random sampling approach and a one-stage cluster analysis that relies on high-resolution satellite data to verify the detected water bodies. The overall accuracy, considering only the commission error, is 95.4% for the whole study region, with best results in the arid and semi-arid climate zone. The method to map water bodies delivers satisfactory results, particularly for sparsely vegetated areas as well as flat areas of the study region. In more humid, more vegetated areas and in mountainous areas, the possibility of false detections increases due to surface characteristics.
Keywords:Remote sensing  Seasonality  Mapping  Monitoring  SPOT
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