Xinyi Shen

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Remote sensed images with very high spatial resolution like Ikonos, QuickBird, etc., can distinguish clearly detailed features such as building, roads, vehicles, and trees. However, the amount of shadow increases with the spatial resolution. Shadow occurs when objects totally or partially occlude the direct light projected from a source of illumination [3].(More)
—This paper focuses on assessing the effectiveness of applying orientation angle calibration to polarimetric synthetic aperture radar (PolSAR) data for soil moisture estimation. We employ Cloude-decomposition-based method to estimate the orientation angle because it can relate a scatter-distributed pixel to its major component of an equivalent " pure(More)
This case study describes how course features and individual & social learning analytics were scaled up to support "participatory" learning. An existing online course was turned into a "big open online course" (BOOC) offered to hundreds. Compared to typical open courses, relatively high levels of persistence, individual & social engagement, and(More)
A practical algorithm was proposed to retrieve land surface temperature (LST) from Visible Infrared Imager Radiometer Suite (VIIRS) data in mid-latitude regions. The key parameter transmittance is generally computed from water vapor content, while water vapor channel is absent in VIIRS data. In order to overcome this shortcoming, the water vapor content was(More)
  • Xinyi Shen, Yang Hong, Ke Zhang, Zhengchao Hao
  • 2014
1 Hydrologic modeling is important in water resources management and flood 2 warning. As one of the most important components of hydrologic models, routing 3 module determines model performance to a large degree. In this study, we have 4 proposed a fully distributed linear reservoir (FDLRR) scheme to replace the existing 5 quasi-distributed (QDLRR) scheme(More)
[1] The T-matrix method has been widely used in radar meteorology because hydrometeors approximate to spheroidal shapes and their sizes are comparable to the sensing wavelength. However, it is considered unsuitable to solve in remote sensing problems concerning vegetation because the particles of interest, leaves and branches, are considered extremely(More)