Surface Soil Moisture Retrieval over Irrigated Wheat Crops in Semi-Arid Areas using Sentinel-1 Data
(2020) 2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020 In 2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020 - Proceedings p.212-215- Abstract
The sensitivity of the backscattering coefficient and the interferometric coherence to surface soil moisture changes and wheat crops growth was analyzed using the time series derived from C-band Sentinel-1. Results show that the interferometric coherence is sensitive to wheat biomass while the backscatter intensity is more influenced by the surface soil moisture (SSM) changes. A new method to retrieve SSM combining the interferometric coherence and C-band backscattering coefficient acquired by Sentinel-1 is tested over two irrigated wheat plots during two growth seasons around Marrakech city (center of Morocco). It is shown that SSM can be estimated with a reasonable accuracy from sowing to harvest (R=0.65; RMSE =0.07... (More)
The sensitivity of the backscattering coefficient and the interferometric coherence to surface soil moisture changes and wheat crops growth was analyzed using the time series derived from C-band Sentinel-1. Results show that the interferometric coherence is sensitive to wheat biomass while the backscatter intensity is more influenced by the surface soil moisture (SSM) changes. A new method to retrieve SSM combining the interferometric coherence and C-band backscattering coefficient acquired by Sentinel-1 is tested over two irrigated wheat plots during two growth seasons around Marrakech city (center of Morocco). It is shown that SSM can be estimated with a reasonable accuracy from sowing to harvest (R=0.65; RMSE =0.07 m3m3; bias =0.01 m3m3). These results enhance the potentialities of Sentinel1 data for SSM retrieval even in the presence of a dense canopy.
(Less)
- author
- Ouaadi, Nadia
; Jarlan, Lionel
; Ezzahar, Jamal
; Zribi, Mehrez
; Khabba, Said
; Bouras, Elhoussaine
LU
and Frison, Pierre Louis
- publishing date
- 2020-03
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- backscattering coefficient, interferometric coherence, semi-arid area, Surface soil moisture, Water Cloud Model, wheat crops
- host publication
- 2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020 - Proceedings
- series title
- 2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020 - Proceedings
- article number
- 9105282
- pages
- 4 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020
- conference location
- Tunis, Tunisia
- conference dates
- 2020-03-09 - 2020-03-11
- external identifiers
-
- scopus:85086711430
- ISBN
- 9781728121901
- DOI
- 10.1109/M2GARSS47143.2020.9105282
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2020 IEEE.
- id
- 88d04cb1-755b-475d-8ef9-74aaf0aa9c44
- date added to LUP
- 2023-01-04 09:52:09
- date last changed
- 2023-09-25 15:28:25
@inproceedings{88d04cb1-755b-475d-8ef9-74aaf0aa9c44, abstract = {{<p>The sensitivity of the backscattering coefficient and the interferometric coherence to surface soil moisture changes and wheat crops growth was analyzed using the time series derived from C-band Sentinel-1. Results show that the interferometric coherence is sensitive to wheat biomass while the backscatter intensity is more influenced by the surface soil moisture (SSM) changes. A new method to retrieve SSM combining the interferometric coherence and C-band backscattering coefficient acquired by Sentinel-1 is tested over two irrigated wheat plots during two growth seasons around Marrakech city (center of Morocco). It is shown that SSM can be estimated with a reasonable accuracy from sowing to harvest (R=0.65; RMSE =0.07 m<sup>3</sup>m<sup>3</sup>; bias =0.01 m<sup>3</sup>m<sup>3</sup>). These results enhance the potentialities of Sentinel1 data for SSM retrieval even in the presence of a dense canopy.</p>}}, author = {{Ouaadi, Nadia and Jarlan, Lionel and Ezzahar, Jamal and Zribi, Mehrez and Khabba, Said and Bouras, Elhoussaine and Frison, Pierre Louis}}, booktitle = {{2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020 - Proceedings}}, isbn = {{9781728121901}}, keywords = {{backscattering coefficient; interferometric coherence; semi-arid area; Surface soil moisture; Water Cloud Model; wheat crops}}, language = {{eng}}, pages = {{212--215}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020 - Proceedings}}, title = {{Surface Soil Moisture Retrieval over Irrigated Wheat Crops in Semi-Arid Areas using Sentinel-1 Data}}, url = {{http://dx.doi.org/10.1109/M2GARSS47143.2020.9105282}}, doi = {{10.1109/M2GARSS47143.2020.9105282}}, year = {{2020}}, }