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First Assessment of Sentinel-1A Data for Surface Soil Moisture Estimations Using a Coupled Water Cloud Model and Advanced Integral Equation Model over the Tibetan Plateau
- Source :
- Remote Sensing; Volume 9; Issue 7; Pages: 714, Remote Sensing, Vol 9, Iss 7, p 714 (2017), Remote sensing, 9(7):714. MDPI
- Publication Year :
- 2017
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2017.
-
Abstract
- The spatiotemporal distribution of soil moisture over the Tibetan Plateau is important for understanding the regional water cycle and climate change. In this paper, the surface soil moisture in the northeastern Tibetan Plateau is estimated from time-series VV-polarized Sentinel-1A observations by coupling the water cloud model (WCM) and the advanced integral equation model (AIEM). The vegetation indicator in the WCM is represented by the leaf area index (LAI), which is smoothed and interpolated from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) LAI eight-day products. The AIEM requires accurate roughness parameters, which are parameterized by the effective roughness parameters. The first halves of the Sentinel-1A observations from October 2014 to May 2016 are adopted for the model calibration. The calibration results show that the backscattering coefficient (σ°) simulated from the coupled model are consistent with those of the Sentinel-1A with integrated Pearson’s correlation coefficients R of 0.80 and 0.92 for the ascending and descending data, respectively. The variability of soil moisture is correctly modeled by the coupled model. Based on the calibrated model, the soil moisture is retrieved using a look-up table method. The results show that the trends of the in situ soil moisture are effectively captured by the retrieved soil moisture with an integrated R of 0.60 and 0.82 for the ascending and descending data, respectively. The integrated bias, mean absolute error, and root mean square error are 0.006, 0.048, and 0.073 m3/m3 for the ascending data, and are 0.012, 0.026, and 0.055 m3/m3 for the descending data, respectively. Discussions of the effective roughness parameters and uncertainties in the LAI demonstrate the importance of accurate parameterizations of the surface roughness parameters and vegetation for the soil moisture retrieval. These results demonstrate the capability and reliability of Sentinel-1A data for estimating the soil moisture over the Tibetan Plateau. It is expected that our results can contribute to developing operational methods for soil moisture retrieval using the Sentinel-1A and Sentinel-1B satellites.
- Subjects :
- 010504 meteorology & atmospheric sciences
Science
0211 other engineering and technologies
Soil science
02 engineering and technology
01 natural sciences
Surface roughness
MODIS LAI
Tibetan Plateau
Sentinel-1A
Leaf area index
Water cycle
Water content
021101 geological & geomatics engineering
0105 earth and related environmental sciences
geography
Plateau
geography.geographical_feature_category
Moisture
AIEM
soil moisture
WCM
ITC-ISI-JOURNAL-ARTICLE
Soil water
General Earth and Planetary Sciences
Environmental science
Moderate-resolution imaging spectroradiometer
ITC-GOLD
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Database :
- OpenAIRE
- Journal :
- Remote Sensing; Volume 9; Issue 7; Pages: 714
- Accession number :
- edsair.doi.dedup.....20aa2a74be0c4522e31b8759a6eb4ae7
- Full Text :
- https://doi.org/10.3390/rs9070714