Working towards a global-scale vegetationwater product from smos optical depth
(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:
https://lup.lub.lu.se/record/5305005
- author
- Grant, Jennifer LU ; Wigneron, Jean-Pierre ; Williams, Mathew ; Scholze, Marko LU and Kerr, Yann
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- SMOS, vegetation optical depth, vegetation water content
- host publication
- 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)
- conference dates
- 2014-07-13 - 2014-07-18
- 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
- 2016-04-01 10:44:19
- date last changed
- 2018-11-21 19:50:18
@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}}, keywords = {{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}}, }