High resolution mapping of inundation area in the Amazon basin from a combination of L-band passive microwave, optical and radar datasets

Abstract

In this paper, we present a methodology to map inland water in tropical areas under dense vegetation at high spatial and temporal resolution using multi-source remote sensing data. A new inundation product (SWAF-HR) is presented. It is characterized by a high spatial resolution (30′, 1 km) and high temporal resolution (3 days). The SWAF-HR product is estimated over the Amazon basin for the 2010–2016 period. It is based on a downscaling procedure and the synergistic use of: (1) water surface fraction at coarse spatial resolution from an L-band passive microwave sensor (Soil Moisture and Ocean Salinity – SMOS), (2) Global Surface Water Occurrence from Landsat (GSWO) and (3) the Digital Elevation Model (DEM) Multi-Error-Removed-Improved-Terrain (MERIT) based on the Shuttle Radar Topography Mission (SRTM). Thanks to the high capability of L-band microwave emission to reveal surface water under all-weather conditions and beneath the vegetation, the inundated area extent estimated by the SWAF-HR product is always larger than GSWO estimates obtained by the optical sensor (Landsat). SWAF-HR data is compared to ESA CCI and IGBP land covers, two SAR images and flooded areas over the Purus basin computed by the MGB-IPH model simulation. The results show the coherence of spatial and temporal dynamics of the SWAF-HR data. We show that the flooded area of the Branco River floodplain in Roraima (Brazil) varies from 0.2 × 104 to 2.7 × 104 km2 whereas the extent of the Bolivian floodplain (Llanos de Moxos) inundation ranges between 0.8 × 104 and 8.1 × 104 km2 during 2010–2016. The flooded area in the Branco floodplain gradually decreased from 2010 to 2015 but in 2016, the flooded area has increased during the rainy season. During 2010–2016, the minimum of the inundated surface extent was reached during 2015–2016 reflecting to a drought event related to ENSO. The most important uncertainties of the DEM are located over tropical areas but this information is essential in the downscaling procedure. Therefore, we investigate the impact of the choice of the DEM for the downscaling procedure. It is found that the choice of the DEM introduces 5% of error in the instantaneous water surface extent estimate but can reach up to 10% in the flood probability estimations over seven years. This new SWAF-HR product will be helpful for the understanding of the water, carbon and biogeochemical cycles of the Amazon.