@Article{FassoniAndradePaiRudBarNov:2020:CaStAm,
               author = "Fassoni Andrade, Alice C{\'e}sar and Paiva, Rodrigo Cauduro Dias 
                         de and Rudorff, Conrado de Moraes and Barbosa, Cl{\'a}udio 
                         Clemente Faria and Novo, Evlyn M{\'a}rcia Le{\~a}o de Moraes",
          affiliation = "{Universidade Federal do Rio Grande do Sul (UFRGS)} and 
                         {Universidade Federal do Rio Grande do Sul (UFRGS)} and {Centro 
                         Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "High-resolution mapping of floodplain topography from space: A 
                         case study in the Amazon",
              journal = "Remote Sensing of Environment",
                 year = "2020",
               volume = "251",
                pages = "e112065",
                month = "Dec.",
             keywords = "Flood frequency, Water level, Topography, Digital elevation model, 
                         MERIT, SRTM, Amazon, Lakes, Floodplain, Geomorphology changes, 
                         Storage volume, Altimetry, ICESat, Landsat, Global surface water, 
                         Google earth engine.",
             abstract = "Terrain elevation is essential for land management, navigation, 
                         and earth science applications. Remote sensing advancements have 
                         led to an increase in the availability of a range of digital 
                         elevation models with global to quasi-global land coverage. 
                         However, the generation of these models in water bodies requires 
                         specialized approaches, such as the delimitation of the shorelines 
                         (isobaths) of lakes over time. Therefore, the processing costs are 
                         high in complex areas with many lakes. Currently, there is no 
                         systematic topographic mapping of lakes and channels in large and 
                         complex floodplains using remote sensing data. We present here the 
                         first high-resolution topographic mapping (30 m) of the 
                         non-forested portion of the middle-lower Amazon floodplain using a 
                         new method based on in-situ Amazon river water levels and a 
                         flood-frequency map derived from the Landsat Global Surface Water 
                         Dataset. Validation using locally derived bathymetry showed a root 
                         mean square error (RMSE) of 0.89 m for floodplain elevation and a 
                         good representation of spatial patterns with Pearson's correlation 
                         coefficient of 0.77. Our approach for improving topographic 
                         representation in open water areas is an alternative to SRTM3 DEM 
                         or MERIT DEM, which represents these areas as a flat surface. We 
                         also generated the Amazon River bathymetry using nautical charts 
                         from the Brazilian Navy (average RMSE of 7.5 m and bias of 5 m), 
                         and floodplain depths maps corresponding to the high- and 
                         low-water periods of the river flood wave. The results show that 
                         the storage volume in the open-water floodplain varies 104.3 km3 
                         on average each year (from 11.9 km3 in low-water to 116.2 km3 in 
                         high-water). The method can be applied to any temporarily flooded 
                         area to provide the often missing underwater digital topographic 
                         data required for hydrological, ecological, and geomorphological 
                         studies. The data set developed in this study can be found at 
                         
                         https://doi-org.ez61.periodicos.capes.gov.br/10.17632/vn599y9szb.1.",
                  doi = "10.1016/j.rse.2020.112065",
                  url = "http://dx.doi.org/10.1016/j.rse.2020.112065",
                 issn = "0034-4257",
             language = "en",
           targetfile = "andrade_high.pdf",
        urlaccessdate = "27 abr. 2024"
}