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Working towards a global-scale vegetationwater product from smos optical depth

Grant, Jennifer LU ; Wigneron, Jean-Pierre; Williams, Mathew; Scholze, Marko LU and Kerr, Yann (2014) IEEE International Geoscience and Remote Sensing Symposium (IGARSS) In 2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Abstract
In this study, vegetation optical depth from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite mission is combined with other existing remote sensing, meteorological and literature data in order to obtain values of gravimetric vegetation water content (M-g). The methodology combines an effective medium model valid at passive microwave frequencies with a vegetation dielectric constant model. The algorithm is calibrated for 11 global vegetation classes. The resulting product consists of temporally dynamic similar to 25 km global grids of Mg. The first maps clearly show seasonal differences in vegetation water, which vary for the different continental regions due to variations in e.g. latitude, climate and landcover type. This new... (More)
In this study, vegetation optical depth from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite mission is combined with other existing remote sensing, meteorological and literature data in order to obtain values of gravimetric vegetation water content (M-g). The methodology combines an effective medium model valid at passive microwave frequencies with a vegetation dielectric constant model. The algorithm is calibrated for 11 global vegetation classes. The resulting product consists of temporally dynamic similar to 25 km global grids of Mg. The first maps clearly show seasonal differences in vegetation water, which vary for the different continental regions due to variations in e.g. latitude, climate and landcover type. This new vegetation water product is unique and offers important complementary information to existing vegetation indices. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
SMOS, vegetation optical depth, vegetation water content
in
2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
external identifiers
  • wos:000349688100072
ISSN
2153-7003
2153-6996
language
English
LU publication?
yes
id
defb2dba-2d6a-455a-9389-ebc1738764a9 (old id 5305005)
date added to LUP
2015-04-27 11:32:34
date last changed
2016-04-15 16:43:42
@inproceedings{defb2dba-2d6a-455a-9389-ebc1738764a9,
  abstract     = {In this study, vegetation optical depth from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite mission is combined with other existing remote sensing, meteorological and literature data in order to obtain values of gravimetric vegetation water content (M-g). The methodology combines an effective medium model valid at passive microwave frequencies with a vegetation dielectric constant model. The algorithm is calibrated for 11 global vegetation classes. The resulting product consists of temporally dynamic similar to 25 km global grids of Mg. The first maps clearly show seasonal differences in vegetation water, which vary for the different continental regions due to variations in e.g. latitude, climate and landcover type. This new vegetation water product is unique and offers important complementary information to existing vegetation indices.},
  author       = {Grant, Jennifer and Wigneron, Jean-Pierre and Williams, Mathew and Scholze, Marko and Kerr, Yann},
  booktitle    = {2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)},
  issn         = {2153-7003},
  keyword      = {SMOS,vegetation optical depth,vegetation water content},
  language     = {eng},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Working towards a global-scale vegetationwater product from smos optical depth},
  year         = {2014},
}