LI Jian, ZHOU Qu, CHEN Xiaoling, TIAN Liqiao, LI Tingting. Spatial Scale Study on Quantitative Remote Sensing of Highly Dynamic Coastal/Inland Waters[J]. Geomatics and Information Science of Wuhan University, 2018, 43(6): 937-942. DOI: 10.13203/j.whugis20160174
Citation: LI Jian, ZHOU Qu, CHEN Xiaoling, TIAN Liqiao, LI Tingting. Spatial Scale Study on Quantitative Remote Sensing of Highly Dynamic Coastal/Inland Waters[J]. Geomatics and Information Science of Wuhan University, 2018, 43(6): 937-942. DOI: 10.13203/j.whugis20160174

Spatial Scale Study on Quantitative Remote Sensing of Highly Dynamic Coastal/Inland Waters

  • Spatial scale issues of coastal and inland waters include spatial variation in the scale, requirements for remote sensing monitoring, and uncertainties in multi-source remote sensing data caused by inconsistent spatial resolution. Aiming at the highly dynamic water bodies, this study focuses on spatial scale issues in remote sensing. Taking advantage of the high spatial resolution GF-1 WFI (16 m) dataset, the scales in spatial variation of coastal water/inland lakes and open sea (taking suspended particulate matter (SPM) as an example) were demonstrated as less than 150 m and higher than 300 m respectively, using the spatial semivariation analysis. Based on the spatial variation continuity of water quality parameters and Taylor series expansion, the scale uncertainty function was quantified. Decreased spatial resolution, significantly increased the SPM errors caused by spatial scale variation, influenced by spatial variations and the non-linear retrieval model of water environmental parameters. This study highlights the crucial need for correction of spatial scale errors of coastal/inland waters, as well as a need for high-precision and consistent remote sensing monitoring from multi-resolution data.
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