Global Evaluation of SMAP/Sentinel-1 Soil Moisture Products
Mohseni, Farzane LU ; Mirmazloumi, S. Mohammad ; Mokhtarzade, Mehdi ; Jamali, Sadegh LU
and Homayouni, Saeid
(2022)
In Remote Sensing
14(18).
- Abstract
- SMAP/Sentinel-1 soil moisture is the latest SMAP (Soil Moisture Active Passive) product derived from synergistic utilization of the radiometry observations of SMAP and radar backscattering data of Sentinel-1. This product is the first and only global soil moisture (SM) map at 1 km and 3 km spatial resolutions. In this paper, we evaluated the SMAP/Sentinel-1 SM product from different viewpoints to better understand its quality, advantages, and likely limitations. A comparative analysis of this product and in situ measurements, for the time period March 2015 to January 2022, from 35 dense and sparse SM networks and 561 stations distributed around the world was carried out. We examined the effects of land cover, vegetation fraction, water... (More)
- SMAP/Sentinel-1 soil moisture is the latest SMAP (Soil Moisture Active Passive) product derived from synergistic utilization of the radiometry observations of SMAP and radar backscattering data of Sentinel-1. This product is the first and only global soil moisture (SM) map at 1 km and 3 km spatial resolutions. In this paper, we evaluated the SMAP/Sentinel-1 SM product from different viewpoints to better understand its quality, advantages, and likely limitations. A comparative analysis of this product and in situ measurements, for the time period March 2015 to January 2022, from 35 dense and sparse SM networks and 561 stations distributed around the world was carried out. We examined the effects of land cover, vegetation fraction, water bodies, urban areas, soil characteristics, and seasonal climatic conditions on the performance of active–passive SMAP/Sentinel-1 in estimating the SM. We also compared the performance metrics of enhanced SMAP (9 km) and SMAP/Sentinel-1 products (3 km) to analyze the effects of the active–passive disaggregation algorithm on various features of the SMAP SM maps. Results showed satisfactory agreement between SMAP/Sentinel-1 and in situ SM measurements for most sites (r values between 0.19 and 0.95 and ub-RMSE between 0.03 and 0.17), especially for dense sites without representativeness errors. Thanks to the vegetation effect correction applied in the active–passive algorithm, the SMAP/Sentinel-1 product had the highest correlation with the reference data in grasslands and croplands. Results also showed that the accuracy of the SMAP/Sentinel-1 SM product in different networks is independent of the presence of water bodies, urban areas, and soil types. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3f245ddc-add7-42ae-adbe-200d081d461e
- author
- Mohseni, Farzane
LU
; Mirmazloumi, S. Mohammad
; Mokhtarzade, Mehdi
; Jamali, Sadegh
LU
and Homayouni, Saeid
- organization
- publishing date
- 2022-09-16
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Remote Sensing
- volume
- 14
- issue
- 18
- article number
- 4624
- publisher
- MDPI AG
- external identifiers
-
- scopus:85138682222
- ISSN
- 2072-4292
- DOI
- 10.3390/rs14184624
- language
- English
- LU publication?
- yes
- id
- 3f245ddc-add7-42ae-adbe-200d081d461e
- alternative location
- https://www.mdpi.com/2072-4292/14/18/4624
- date added to LUP
- 2022-09-19 09:17:15
- date last changed
- 2022-12-28 14:12:26
@article{3f245ddc-add7-42ae-adbe-200d081d461e,
abstract = {{SMAP/Sentinel-1 soil moisture is the latest SMAP (Soil Moisture Active Passive) product derived from synergistic utilization of the radiometry observations of SMAP and radar backscattering data of Sentinel-1. This product is the first and only global soil moisture (SM) map at 1 km and 3 km spatial resolutions. In this paper, we evaluated the SMAP/Sentinel-1 SM product from different viewpoints to better understand its quality, advantages, and likely limitations. A comparative analysis of this product and in situ measurements, for the time period March 2015 to January 2022, from 35 dense and sparse SM networks and 561 stations distributed around the world was carried out. We examined the effects of land cover, vegetation fraction, water bodies, urban areas, soil characteristics, and seasonal climatic conditions on the performance of active–passive SMAP/Sentinel-1 in estimating the SM. We also compared the performance metrics of enhanced SMAP (9 km) and SMAP/Sentinel-1 products (3 km) to analyze the effects of the active–passive disaggregation algorithm on various features of the SMAP SM maps. Results showed satisfactory agreement between SMAP/Sentinel-1 and in situ SM measurements for most sites (r values between 0.19 and 0.95 and ub-RMSE between 0.03 and 0.17), especially for dense sites without representativeness errors. Thanks to the vegetation effect correction applied in the active–passive algorithm, the SMAP/Sentinel-1 product had the highest correlation with the reference data in grasslands and croplands. Results also showed that the accuracy of the SMAP/Sentinel-1 SM product in different networks is independent of the presence of water bodies, urban areas, and soil types.}},
author = {{Mohseni, Farzane and Mirmazloumi, S. Mohammad and Mokhtarzade, Mehdi and Jamali, Sadegh and Homayouni, Saeid}},
issn = {{2072-4292}},
language = {{eng}},
month = {{09}},
number = {{18}},
publisher = {{MDPI AG}},
series = {{Remote Sensing}},
title = {{Global Evaluation of SMAP/Sentinel-1 Soil Moisture Products}},
url = {{http://dx.doi.org/10.3390/rs14184624}},
doi = {{10.3390/rs14184624}},
volume = {{14}},
year = {{2022}},
}