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Using Remote Sensing for Agricultural Statistics
Author(s) -
Carfagna Elisabetta,
Gallego F. Javier
Publication year - 2005
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2005.tb00155.x
Subject(s) - estimator , mathematics , statistics , confusion , geography , forestry , cartography , remote sensing , psychology , psychoanalysis
Summary Remote sensing can be a valuable tool for agricultural statistics when area frames or multiple frames are used. At the design level, remote sensing typically helps in the definition of sampling units and the stratification, but can also be exploited to optimise the sample allocation and size of sampling units. At the estimator level, classified satellite images are generally used as auxiliary variables in a regression estimator or for estimators based on confusion matrixes. The most often used satellite images are LANDSAT‐TM and SPOT‐XS. In general, classified or photo‐interpreted images should not be directly used to estimate crop areas because the proportion of pixels classified into the specific crop is often strongly biased. Vegetation indexes computed from satellite images can give in some cases a good indication of the potential crop yield.