A novel downscaling methodology for intermediate resolution radiometer data for SMAP

A novel downscaling methodology for intermediate spatial resolution radiometer data is developed in view of forthcoming SMAP mission. It is based on an active and a passive microwave forward model coupled by its ancillary parameters. The combined active/passive model introduced in this work yields b...

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Detalles Bibliográficos
Publicado: 2015
Materias:
downscaling
Radar
radiometer
SMAP
soil moisture
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814799_v2015-November_n_p1972_Bruscantini
http://hdl.handle.net/20.500.12110/paper_97814799_v2015-November_n_p1972_Bruscantini
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_97814799_v2015-November_n_p1972_Bruscantini
record_format dspace
spelling paper:paper_97814799_v2015-November_n_p1972_Bruscantini2023-06-08T16:37:44Z A novel downscaling methodology for intermediate resolution radiometer data for SMAP downscaling Radar radiometer SMAP soil moisture A novel downscaling methodology for intermediate spatial resolution radiometer data is developed in view of forthcoming SMAP mission. It is based on an active and a passive microwave forward model coupled by its ancillary parameters. The combined active/passive model introduced in this work yields backscatter and emission observations relation consistent with Aquarius/SAC-D observations and with what it has been reported in previous papers. Furthermore, merging spatial resolution between radar-derived and radiometer-based brightness temperature (Tb) is performed in a least-square framework. Methodology is tested using a synthetic numerical simulation example which showed that this approach leads to an increase of downscaled Tb accuracy. © 2015 IEEE. 2015 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814799_v2015-November_n_p1972_Bruscantini http://hdl.handle.net/20.500.12110/paper_97814799_v2015-November_n_p1972_Bruscantini
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic downscaling
Radar
radiometer
SMAP
soil moisture
spellingShingle downscaling
Radar
radiometer
SMAP
soil moisture
A novel downscaling methodology for intermediate resolution radiometer data for SMAP
topic_facet downscaling
Radar
radiometer
SMAP
soil moisture
description A novel downscaling methodology for intermediate spatial resolution radiometer data is developed in view of forthcoming SMAP mission. It is based on an active and a passive microwave forward model coupled by its ancillary parameters. The combined active/passive model introduced in this work yields backscatter and emission observations relation consistent with Aquarius/SAC-D observations and with what it has been reported in previous papers. Furthermore, merging spatial resolution between radar-derived and radiometer-based brightness temperature (Tb) is performed in a least-square framework. Methodology is tested using a synthetic numerical simulation example which showed that this approach leads to an increase of downscaled Tb accuracy. © 2015 IEEE.
title A novel downscaling methodology for intermediate resolution radiometer data for SMAP
title_short A novel downscaling methodology for intermediate resolution radiometer data for SMAP
title_full A novel downscaling methodology for intermediate resolution radiometer data for SMAP
title_fullStr A novel downscaling methodology for intermediate resolution radiometer data for SMAP
title_full_unstemmed A novel downscaling methodology for intermediate resolution radiometer data for SMAP
title_sort novel downscaling methodology for intermediate resolution radiometer data for smap
publishDate 2015
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814799_v2015-November_n_p1972_Bruscantini
http://hdl.handle.net/20.500.12110/paper_97814799_v2015-November_n_p1972_Bruscantini
_version_ 1768542010210254848

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