Using scattered hyperspectral imagery data to map the soil properties of a regionReportar como inadecuado

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1 LISAH - Laboratoire d-étude des interactions entre sols, agrosystèmes et hydrosystèmes 2 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale 3 BIOSP - Biostatistique et Processus Spatiaux

Abstract : Airborne hyperspectral imagery has been recently provedto bea successful technique for predicting soil properties of the bare soil surfaces that are usually scattered in the landscape. This new soil covariate could improve a lot the digital soil mapping DSM of soil properties over larger areas. To illustrate this, we experimented with digital soil mapping in a 24.6-km² area located in the vineyard plain of Languedoc. As input data, we used 200 points with clay content measurements and 192 bare soil fields representing 3.5% of the total area in which the clay contents of the soil surface were successfully mapped at 5-m resolution by hyperspectral remote sensing. The clay contents were estimated from CR2206, a spectrometric indicator that quantifies specific absorption features of clay at 2206 nm. We demonstrated by cross-validation that the co-kriging procedure based on our co-regionalisation model provided accurate error estimates at the clay measurement sites. Then, we applied a block co-kriging model to map the mean clay content at increasing resolutions 50 , 100, 250 and 500 m. The results showed the following:i using hyperspectral data significantly increased the accuracy of the mean clay content estimations; ii a block co-kriging procedure with reliable estimates of error variance can be used to estimate mean clay contents over larger areas and at coarser resolutions with acceptable and predictable errors and iii various maps can be produced that represent different compromises between prediction accuracy and spatial resolution


Autor: P. Lagacherie - Jean-Stéphane Bailly - P. Monestiez - C. Gomez -



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