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A primary study on downscaling microwave soil moisture with MOD16 and SMAP

  • role： First author第一作者
  • Affiliation：

    College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China

  • Email：sunhao@cumtb.edu.cn
  • Introduction：孙灏，1986年生，男，副教授，研究方向为资源环境遥感。E-mail: sunhao@cumtb.edu.cn
SUN Hao1,  
  • Affiliation：

    College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China

ZHOU Baichi1,  
  • Affiliation：

    Remote Sensing Survey and Mapping Institute of Ningxia Hui Autonomous Region (Ningxia Remote Sensing Center), Yinchuan 750021, China

LI huan2,  
  • Affiliation：

    College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China

RUAN Lin1

реферат

Improving the spatial resolution of microwave Soil Moisture (SM) production is of great significance for hydrological and agricultural applications on a regional scale. Downscaling microwave satellite SM with optical/thermal infrared and microwave fusion method shows great application potential. However, it mostly relies on remote sensing surface temperature (LST) or the SM index derived by LST decomposition, which is limited by the cloud contamination problems, LST decomposition uncertainties, and the decoupling effect between LST and SM. To circumvent these problems, we made a primary study on downscaling microwave SM by coupling MOD16 and SMAP data. In this study, we constructed three parameterized downscaling functions (i.e., exponent, cosine, cosine squared) between Land surface Evapotranspiration Efficiency (LEE) and SM. MOD16 products is employed to calculate LEE, which has a spatial resolution of 500 m. Combining the parameterized downscaling functions and the high-resolution LEE, original SMAP SM (spatial resolution, 36 km) data were successfully downscaled to a spatial resolution of 500m. The downscaled SM was evaluated in terms of dynamic range, energy conservation, in situ SM at sparse stations, and in situ SM at Core Validation Station (CVS). Results demonstrated that the downscaling algorithm increases the spatial detail characteristics of original SM, maintains the dynamic range of SM, and preserves energy during the downscaling process. Moreover, it maintains the performance of the original SM as compared with in situ SM at CVS and sparse stations. Sensitivity analysis showed that the cosine-square downscaling function is less sensitive to errors in MOD16 production than the other two downscaling functions.

ключеви́че слова́

microwave soil moisture;spatially downscaling;land surface evapotranspiration efficiency;MOD16;SMAP

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