YUE Yanli, LUO Mingliang, ZHANG Bin. Study on Spatial Distribution of DEM Interpolation Errors in the Gully of Dry-Hot Valley[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 1122-1128. DOI: 10.13203/j.whugis20160302
Citation: YUE Yanli, LUO Mingliang, ZHANG Bin. Study on Spatial Distribution of DEM Interpolation Errors in the Gully of Dry-Hot Valley[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 1122-1128. DOI: 10.13203/j.whugis20160302

Study on Spatial Distribution of DEM Interpolation Errors in the Gully of Dry-Hot Valley

Funds: 

The National Natural Science Foundation of China 41101348

the Basic Scientific Research Foundation of China West Normal University 15C002

More Information
  • Author Bio:

    YUE Yanli, postgraduate, specializes in soil and water conservation and desertification combating. E-mail:Yulisa258@163.com

  • Corresponding author:

    LUO Mingliang, PhD, professor. E-mail:lolean586@163.com

  • Received Date: December 26, 2016
  • Published Date: July 04, 2018
  • To analyze the interpolation errors spatial distribution characteristics of the typical gully of Yuanmou dry-hot valley, the measured elevation points were interpolated by inverse distance weighting (IDW), local polynomial interpolation (LPI), spline with tension (ST), disjunctive Kriging (DK) and triangulated irregular network (TIN)model to generate DEM. Cross validation, relative difference coefficient and the valley lines discrepancy were used to evaluate the interpolation accuracy. The error points with elevation error greater than 1 m were extracted, and their spatial distribution characteristics were analyzed by coefficient of variation(CV), global Moran's index and Getis-Ord Gi* index. The results show that DK and TIN model had higher interpolation accuracy, the height error points of five interpolation methods were overall aggregating distribution, and the degree was TIN > LPI > DK > ST > IDW. Height errors were significantly positive spatial autocorrelation and TIN model had the highest autocorrelation degree, the hot spots of errors were distributed in the area with large slope.
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