TY - JOUR

T1 - Measurement error in reflectance data and its implcations for regularizing the variogram

AU - Atkinson, Peter M.

AU - Dunn, R.

AU - Harrison, A. R.

PY - 1996

Y1 - 1996

N2 - Measurement error is an important component of variation in most measured variables and also, therefore, in the sample variogram of field-based reflectance. The variogram of the underlying variation in reflectance is regularized and, therefore, must be continuous through the origin. The variogram of measurement error in reflectance, however, is unlikely to pass continuously through the origin. Therefore, the sample semivariance at a lag of just grealer than zeroy v(0++ ) is likely to be some positive value due solely to the error in measuring reflectance. We recommend that where possible y v(0++ ) should be computed by repeated measurement of reflectance al the same location, x, and over the same support, v. If repeated measurement is not possible then in certain circumstances the nugget variance of the variogram model may be used to estimate measurement error in the sample variogram denotedy v ME, IF y v is not estimated and measurement error is not separated from the underlying variation then geostatistical techniques that depend on yv( h) and which are currently being applied in remote sensing may be affected. We demonstrate these ideas with a simple example involving regularizing the variogram of the Normalized Difference Vegetation Index (NDVI) of a field of pasture measured with a field radiometer.

AB - Measurement error is an important component of variation in most measured variables and also, therefore, in the sample variogram of field-based reflectance. The variogram of the underlying variation in reflectance is regularized and, therefore, must be continuous through the origin. The variogram of measurement error in reflectance, however, is unlikely to pass continuously through the origin. Therefore, the sample semivariance at a lag of just grealer than zeroy v(0++ ) is likely to be some positive value due solely to the error in measuring reflectance. We recommend that where possible y v(0++ ) should be computed by repeated measurement of reflectance al the same location, x, and over the same support, v. If repeated measurement is not possible then in certain circumstances the nugget variance of the variogram model may be used to estimate measurement error in the sample variogram denotedy v ME, IF y v is not estimated and measurement error is not separated from the underlying variation then geostatistical techniques that depend on yv( h) and which are currently being applied in remote sensing may be affected. We demonstrate these ideas with a simple example involving regularizing the variogram of the Normalized Difference Vegetation Index (NDVI) of a field of pasture measured with a field radiometer.

U2 - 10.1080/01431169608949181

DO - 10.1080/01431169608949181

M3 - Journal article

VL - 17

SP - 3735

EP - 3750

JO - International Journal of Remote Sensing

JF - International Journal of Remote Sensing

SN - 0143-1161

IS - 18

ER -