dc.contributorUniversidade Estadual Paulista (UNESP)
dc.contributorUniversidade Federal de Santa Catarina (UFSC)
dc.date.accessioned2022-04-28T19:29:24Z
dc.date.accessioned2022-12-20T01:13:11Z
dc.date.available2022-04-28T19:29:24Z
dc.date.available2022-12-20T01:13:11Z
dc.date.created2022-04-28T19:29:24Z
dc.date.issued2020-03-01
dc.identifier2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Proceedings, p. 121-125.
dc.identifierhttp://hdl.handle.net/11449/221571
dc.identifier10.1109/LAGIRS48042.2020.9165636
dc.identifier2-s2.0-85091623291
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5401700
dc.description.abstractWater 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.
dc.languageeng
dc.relation2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Proceedings
dc.sourceScopus
dc.subjectaccuracy
dc.subjectAmazonian region
dc.subjectbathymetry
dc.subjectdam
dc.subjectLandsat-8
dc.subjectLyzega
dc.subjectmultispectral sensor
dc.titleDepth Retrieval from A Reservoir Using A Conditional-Based Model
dc.typeActas de congresos


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