Assessment of Effective Roughness Parameters for Simulating Sentinel-1A Observation and Retrieving Soil Moisture over Sparsely Vegetated Field Article Swipe
The variability of surface roughness may lead to relatively large dynamic of backscatter coefficient observed by the synthetic aperture radar (SAR), which complicates the soil moisture (SM) retrieval process based on active remote sensing. The effective roughness parameters are commonly used for parameterizing the soil scattering models, the values of which are often assumed to be constant during different study periods for the same site. This paper investigates the reasonableness of this hypothesis from the perspective of backscatter coefficient simulation and SM retrieval using high resolution SAR data. Three years of Sentinel-1A data from 2016 to 2018 were collected over a sparsely vegetated field within the REMEDHUS SM monitoring network. The advanced integral equation model (AIEM) and Dobson dielectric mixing model were combined for optimizing the effective roughness parameters, as well as simulating the backscatter coefficient and retrieving the SM. The effective roughness parameters were optimized at different temporal periods, such as 2016, 2017, 2018, 2016 + 2017, 2017 + 2018, and 2016 + 2017 + 2018, to analyze their temporal dynamics. It was found that: (1) the effective roughness parameters optimized at different temporal periods are very close to each other; (2) the simulated backscatter from AIEM is consistent with Sentinel-1A observation with root mean square errors (RMSEs) between 1.133 and 1.163 dB and correlation coefficient ® value equals to 0.616; (3) the seasonal dynamics ofin situ SM is well-captured by the retrieved SM with R values floating at 0.685 and RMSEs ranging from 0.049 to 0.052 m3/m3; and (4) inverse of the AIEM with the implementation of effective roughness parameters achieves better performance for SM retrieval than the change detection method. These findings demonstrate that the assumption on the constant effective roughness parameters during the study period of at least three years is reasonable.
Related Topics
Concepts
Backscatter (email)
Remote sensing
Environmental science
Surface roughness
Synthetic aperture radar
Surface finish
Root mean square
Water content
Mean squared error
Correlation coefficient
Scattering
Soil science
Materials science
Geology
Optics
Computer science
Physics
Mathematics
Statistics
Geotechnical engineering
Wireless
Telecommunications
Composite material
Quantum mechanics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs14236020
- https://www.mdpi.com/2072-4292/14/23/6020/pdf?version=1669628938
- OA Status
- gold
- Cited By
- 4
- References
- 60
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4310179623
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4310179623Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs14236020Digital Object Identifier
- Title
-
Assessment of Effective Roughness Parameters for Simulating Sentinel-1A Observation and Retrieving Soil Moisture over Sparsely Vegetated FieldWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-28Full publication date if available
- Authors
-
Xiaojing WuList of authors in order
- Landing page
-
https://doi.org/10.3390/rs14236020Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/14/23/6020/pdf?version=1669628938Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-4292/14/23/6020/pdf?version=1669628938Direct OA link when available
- Concepts
-
Backscatter (email), Remote sensing, Environmental science, Surface roughness, Synthetic aperture radar, Surface finish, Root mean square, Water content, Mean squared error, Correlation coefficient, Scattering, Soil science, Materials science, Geology, Optics, Computer science, Physics, Mathematics, Statistics, Geotechnical engineering, Wireless, Telecommunications, Composite material, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
60Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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