Retrieval of Surface Soil Moisture From Sentinel-1 Time Series for Reclamation of Wetland Sites
| Autor: | Thomas Puestow, Igor Zakharov, Michael D. Henschel, Jon Hornung, Sarah Kohlsmith, Mark Howell, Mark Kapfer |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Synthetic aperture radar
oil sands Atmospheric Science reclamation 010504 meteorology & atmospheric sciences Backscatter Geophysics. Cosmic physics 0211 other engineering and technologies Soil science Wetland 02 engineering and technology 01 natural sciences Land reclamation Precipitation Computers in Earth Sciences TC1501-1800 Water content 021101 geological & geomatics engineering 0105 earth and related environmental sciences geography geography.geographical_feature_category Change detection algorithm QC801-809 Vegetation synthetic aperture radar (SAR) Ocean engineering Soil water Sentinel-1 Environmental science soil moisture |
| Zdroj: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 3569-3578 (2020) |
| ISSN: | 2151-1535 1939-1404 |
| DOI: | 10.1109/jstars.2020.3004062 |
| Popis: | Soil moisture is a key factor in the reclamation of wetland habitats. Understanding the distribution and relative amount of water can be critical in reintroducing trees and grasses to disturbed soils. Soil moisture is also one of the main factors affecting microwave radar backscatter from the ground; while there are other factors determining backscatter levels (for instance, surface roughness, vegetation, and incident angle), relative variations in soil moisture can be estimated using space-based, high resolution, multitemporal synthetic aperture radar (SAR). In this work, relative soil moisture indicators are derived from a time series of Sentinel-1 SAR data over previously mined oil sands in Alberta, Canada. The algorithm provides a relative assessment of soil moisture and requires calibration over wet and dry periods. An evaluation of the soil moisture product is validated using in situ measurements at multiple sites with observations showing agreement from May to August. Comparisons with precipitation records show that SAR derived surface soil moisture is influenced by discreet precipitation events; that is, rainfall that is coincident with the satellite observation reduces the effectiveness of the measurement. The resulting algorithm controls for rain events by including local weather records to adjust estimates based on the known precipitation. |
| Databáze: | OpenAIRE |
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