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Spatial Variability of Remotely Sensed Surface Temperatures at Field Scale
Author(s) -
Yates S. R.,
Warrick A. W.,
Matthias A. D.,
Musil S.
Publication year - 1988
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj1988.03615995005200010007x
Subject(s) - kriging , autocorrelation , variogram , spatial analysis , environmental science , estimator , spatial distribution , spatial dependence , spatial variability , spatial ecology , sampling (signal processing) , scale (ratio) , mathematics , random field , soil science , atmospheric sciences , remote sensing , statistics , geology , geography , physics , cartography , ecology , optics , detector , biology
Bare soil surface temperatures (BST) and crop canopy temperatures (CCT) were collected from a 1‐ha field in central Arizona using an infrared thermometer to determine whether they were spatially correlated. The measurements were taken from a two‐dimensional random sampling pattern for selected dates and times to investigate the spatial and temporal distribution. Three measures of the correlation distance including two integral scales were calculated. Kriging, which produces the best linear unbiased estimator, was used to show the spatial pattern of the BST and CCT in the field on selected dates. The results indicate that the BST and CCT are spatially dependent random functions with integral scales that varied from 2 to 15 m for wet and dry conditions, respectively. The autocorrelation as the lagged distance approaches zero was greater than 0.4 except under wet soil conditions, where the autocorrelation for the CCT was found to be lower. The results are important because, to date, no geostatistical study has shown that the CCT is a spatially dependent random function.