Quantitative Analysis of Moisture Effect on Black Soil Reflectance
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2020, International Journal of Applied Earth Observation and GeoinformationCitation Excerpt :Hyperspectral remote sensing technology is extensively used to obtain spectral information in great detail with the aim of improving the soil property prediction accuracy; the significant advantage of this approach lies in the enormous amount of band information that can be acquired in comparison with the abilities of multispectral satellites. Taking the Landsat OLI sensor as an example, an entire OLI image contains a total of 9 bands, and thus, limiting any information may cause some prediction-related details to be ignored (Fig. 11); furthermore, the wavelength range correlated with the soil prediction is several times smaller than the 600−800 nm band, which has a high correlation with laboratory SOC predictions; thus, only 2/5 of the information is included, this band information is not sufficiently detailed, and unfortunately, different research results cannot be supported or verified with this lack of band information (Brown et al., 2006; Dalal and Henry, 1986; Daniel et al., 2004; Hummel et al., 2001; Kweon and Maxton, 2013; Liu et al., 2009a,b; Palacios-Orueta and Ustin, 1998; Rossel et al., 2006; Shepherd and Walsh, 2002; Sudduth and Hummel, 1991). In the model with the highest prediction accuracy, most of the selected bands are not in the spectral range of multispectral satellites, and the spectral differences of different SOC contents are not obvious in the multispectral data (Fig. 11).
Project supported by the National Key Technology Research and Development Program of China (Nos. 40801167 and 2006BAD05B05), the Knowledge Innovation Program of the Chinese Academy of Sciences (No. KZCX3-SW-356), and the Foundation of the Chinese Academy of Sciences for the Field Stations of Resources and Environment.