Title | ||
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Daily High-Resolution Land Surface Freeze/Thaw Detection Using Sentinel-1 and AMSR2 Data |
Abstract | ||
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High-resolution surface freeze/thaw (F/T) information is valuable for hydrological, frost creep and gelifluction/solifluction, and climate prediction studies. Currently, large-scale, high-resolution F/T detection is restricted by low spatial resolution of passive microwave remote sensing sensors or low temporal resolution of synthetic aperture radar (SAR) data. In this study, we propose a new method for detecting daily land surface F/T state at 1 km spatial resolution by combining the Sentinel-1 radar and the Advanced Microwave Scanning Radiometer 2 (AMSR2) with leaf area index (LAI) data. A non-linear relationship is established between the 1 km F/T index from Sentinel-1 with 1 km F/T index from AMSR2 (FTI) and 1 km LAI data. The 1 km FTI is a disaggregation of the 25 km FTI obtained from AMSR2. This non-linear relationship is then applied to daily 1 km FTI and LAI data to predict the 1 km daily F/T index, based on which the F/T status is detected with grid-cell-based F/T thresholds. The overall accuracy of this daily 1 km F/T is more than 88.1% when evaluated with the in situ 5 cm soil temperature over China and Canada. This study is valuable for detecting daily, high-resolution F/T status and is helpful for studies related to disaster and climate prediction. |
Year | DOI | Venue |
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2022 | 10.3390/rs14122854 | REMOTE SENSING |
Keywords | DocType | Volume |
detection of freeze, thaw status, sentinel-1, AMSR2, 1 km resolution, vegetation | Journal | 14 |
Issue | ISSN | Citations |
12 | 2072-4292 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jian Wang | 1 | 1 | 1.02 |
Lingmei Jiang | 2 | 34 | 7.85 |
Kimmo Rautiainen | 3 | 0 | 0.34 |
Cheng Zhang | 4 | 54 | 16.15 |
Zhiqiang Xiao | 5 | 164 | 32.08 |
Heng Li | 6 | 0 | 0.68 |
Jianwei Yang | 7 | 58 | 12.73 |
Huizhen Cui | 8 | 0 | 0.34 |