Automatic Detection of Inland Water Bodies along Altimetry Tracks for Estimating Surface Water Storage Variations in the Congo Basin

Surface water storage in floodplains and wetlands is poorly known from regional to global scales, spite of its importance the hydrological carbon balances, as wet areas are an important compartment which delays transfer, modifies sediment transport through sedimentation erosion processes, a source for greenhouse gases. Remote sensing powerful tool monitoring temporal variations both extent, level, volume, using synergy between satellite images radar altimetry. Estimating levels over flooded area altimetry observation difficult. In this study, unsupervised classification approach applied on backscattering coefficients discriminate non-flooded Cuvette Centrale Congo. Good detection (open water, permanent seasonal inundation) above 0.9 ENVISAT Jason-2. Based these results, time series were automatically produced. They exhibit good agreement with regime Centrale. Comparisons against manually generated same missions at locations show very two processes (i.e., RMSE ≤ 0.25 m more than 80%/90% cases R ≥ 0.95 95%/75% Jason-2, respectively). The use rivers improves spatial pattern annual amplitude It also leads decrease by factor four surface estimates area, compared case where only considered.