Remote sensing data with the conditional latin hypercube sampling

Yu Pin Lin, Hone Jay Chu, Cheng Long Wang, Hsiao Hsuan Yu, Yung Chieh Wang

研究成果: Chapter


This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the Chi-Chi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures, and spatial variability of landscapes caused by these large disturbances. The conditional Latin hypercube sampling (LHS) approach was applied to select samples from multiple NDVI images. Kriging and sequential Gaussian simulation (SGS) with sufficient samples were then used to generate maps of NDVI images. The variography of NDVI image results demonstrate that spatial patterns of disturbed landscapes were successfully delineated by variogram analysis in study areas. The high-magnitude Chi-Chi earthquake created spatial landscape variations in the study area. After the earthquake, the cumulative impacts of typhoons on landscape patterns depended on the magnitudes and paths of typhoons, but were not always evident in the spatiotemporal variability of landscapes in the study area. The statistics and spatial structures of multiple NDVI images were captured by 3,000 samples from 62,500 grids in the NDVI images. Kriging and SGS with the 3,000 samples effectively reproduced spatial patterns of NDVI images. However, the proposed approach, which integrates the conditional LHS (cLHS) approach, variogram, kriging, and SGS in remotely sensed images, efficiently monitors, samples, and maps the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial variability and heterogeneity.

主出版物標題Earth Science
主出版物子標題New Methods and Studies
發行者Apple Academic Press
出版狀態Published - 2011 1月 1

All Science Journal Classification (ASJC) codes

  • 一般農業與生物科學
  • 一般環境科學
  • 一般地球與行星科學


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