The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W12-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 231–235, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-231-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 231–235, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-231-2020

  06 Nov 2020

06 Nov 2020

DEPTH RETRIEVAL FROM A RESERVOIR USING A CONDITIONAL-BASED MODEL

M. B. Nunes1, A. P. Dal Poz1, E. Alcântara1, and M. Curtarelli2 M. B. Nunes et al.
  • 1São Paulo State University (UNESP), Brazil
  • 2Federal University of Santa Catarina (UFSC), Brazil

Keywords: bathymetry, Landsat-8, Lyzega, dam, accuracy, Amazonian region, multispectral sensor

Abstract. Water depth is an important measure for nautical charts. Accurate methods to provide water depth information are expensive and time costing. For this reason, since late 70’s, it started to be estimate by multispectral sensors with empirical models. In the literature there is no investigation using empirical models partitioned in depth intervals, for this reason, we evaluated the accuracy of partitioned and single bathymetric models. The results have shown that to retrieve depth in from 0 to 15 m the single model provided an RMSE of 3.57 m, with a bias of about −0.83 m; while the RMSE for the partitioned model was 2.29 m with a bias of 0.41 m. For updating nautical charts using multispectral sensors it was concluded that the partitioned model can provide a better result than using a single model.