Virtual water level stations in the Amazon floodplains measured by radar echoes classification

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Virtual water level stations in the Amazon floodplains measured by radar echoes classification
Enguehard, Pauline; Frappart, Frédéric; Zeiger, Pierre; Blarel, Fabien; Satge, Frédéric; Bonnet, Marie-Paule, 2023, "Virtual water level stations in the Amazon floodplains measured by radar echoes classification", https://doi.org/10.23708/HOZKPW, DataSuds, V1, UNF:6:MEl7erA/2OZZ7MbVWo5szw== [fileUNF]
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Description
This dataset was obtained using altimetry data, from CTOH (Center for Topographic studies of the Ocean and Hydrosphere, http://ctoh.legos.obs-mip.fr/), of the ENVISAT (2002-2010) and SARAL (2013-2016) satellite missions acquired over the Curuai floodplain along the Amazon and the Jurua watershed.

The dataset contains classification results of radar altimetry echoes performed with the unsupervised K-means method (netCDF4 files) with each satellite missions (ENV for ENVISAT and SRL for SARAL) based on echo backscatter and normalized water height (sh) parameters. For each area, four classes were created to best represent the different hydrological regimes in the Amazon without over-interpreting radar echoes. The four classes are rated from 0 to 3. Class 0 is very often located on open water (lakes or rivers); on the contrary, class 3 is mainly located in non-flooded areas (not used here). Classes 1 and 2 correspond to intermediate hydrological environment such as permanently or seasonally flooded and seasonally or infrequently flooded, respectively.

For each cluster of echoes classified in the same class along an altimetric track, a station is created containing the time series of local water level variation (.txt files). This is an important densification of water level information in the Amazon floodplains. (2023-01-12)
Subject Earth and Environmental Sciences
Keyword Radar altimetry, Amazon, Floodplains, Unsupervised classification, Automatic generation of water level gauges, Hydrological connectivity
Related Publication Pauline Enguehard, Frédéric Frappart, Pierre Zeiger, Fabien Blarel, Frédéric Satgé, Marie-Paule Bonnet. (2023) "Contribution of automatically generated radar altimetry water levels from unsupervised classification to study hydrological connectivity within Amazon floodplains", Journal of Hydrology: Regional Studies, vol.47. Elsevier BV. doi: 10.1016/j.ejrh.2023.101397
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ClassifWLstations_dataset_summary.txt
Classif_WLstations/Plain Text - 1.6 KB
Published May 3, 2023
7 Downloads
MD5: 760e030e2958315a85d522d24cfcbdd4
Dataset citation and description
Documentation
classif_Curuai_ENV_sh.nc
Classif_WLstations/Network Common Data Form - 27.0 KB
Published May 3, 2023
6 Downloads
MD5: cb6ed7bf54dbdeeba2c3adae72c6a0a4
netCDF4 format
Data
classif_Curuai_SRL_sh.nc
Classif_WLstations/Network Common Data Form - 31.3 KB
Published May 3, 2023
5 Downloads
MD5: 050631ad8c269e6f6d09d74ba1270476
netCDF4 format
Data
classif_Jurua_ENV_sh.nc
Classif_WLstations/Network Common Data Form - 122.3 KB
Published May 3, 2023
5 Downloads
MD5: c0a278fb8f2c4e30fbdc782a925d4c8d
netCDF4 format
Data
classif_Jurua_SRL_sh.nc
Classif_WLstations/Network Common Data Form - 233.0 KB
Published May 3, 2023
5 Downloads
MD5: 2713b22854beef2be0222c5c01b5be6d
netCDF4 format
Data
WL_Curuai_class0_ENV_sh.tab
Classif_WLstations/Tabular Data - 34.9 KB
Published May 3, 2023
8 Downloads
802 Variables, 21 Observations UNF:6:CZaZa6Ira2BGC3tMACnxtw==
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WL_Curuai_class0_SRL_sh.tab
Classif_WLstations/Tabular Data - 4.7 KB
Published May 3, 2023
7 Downloads
204 Variables, 8 Observations UNF:6:spo0JpDGL+ILLDEswTd36w==
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WL_Curuai_class1_ENV_sh.tab
Classif_WLstations/Tabular Data - 25.8 KB
Published May 3, 2023
7 Downloads
646 Variables, 17 Observations UNF:6:3uRl0ywZrHLOYYVOrkvwNg==
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WL_Curuai_class1_SRL_sh.tab
Classif_WLstations/Tabular Data - 2.4 KB
Published May 3, 2023
7 Downloads
105 Variables, 5 Observations UNF:6:8WdiyM1jPCMTuZdwSTB5Jg==
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WL_Curuai_class2_ENV_sh.tab
Classif_WLstations/Tabular Data - 47.8 KB
Published May 3, 2023
7 Downloads
724 Variables, 30 Observations UNF:6:J7OqeVyWGDSzK16MsJWdCg==
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