Crop area estimates through remote sensing: stability of the regression correction

1 December 1993

journal article
research article
Published by Taylor & Francis in International Journal of Remote Sensing

Vol. 14 (18) , 3433-3445
https://doi.org/10.1080/01431169308904456

Abstract

Inventories of the MARS Project of the IRSA that is briefly described. Some aspects concerning stability are discussed. Regression results seem to be more reliable if training pixels are chosen at random in a random subset of segments (elements of the area sampling frame). Some risk of bias is observed if segments with training pixels are included to compute the regression parameters.

Keywords

This publication has 8 references indexed in Scilit:

Use of error probabilities to improve area estimates based on maximum likelihood classifications
Remote Sensing of Environment, 1990
Global estimates from confusion matrices A reply to Jupp
International Journal of Remote Sensing, 1989
The stability of global estimates from confusion matrices
International Journal of Remote Sensing, 1989
The derivation of global estimates from a confusion matrix
International Journal of Remote Sensing, 1988
Crop Acreage Estimation Using a Landsat-Based Estimator as an Auxiliary Variable
IEEE Transactions on Geoscience and Remote Sensing, 1986
Regression Diagnostics
Published by Wiley ,1980
Sampling schemes providing unbaised regression estimators
Biometrika, 1980
A Structural Analysis of Complex Aerial Photographs
Published by Springer Nature ,1980