Quadro de Recados - Divirtam-se com Responsabilidade!

Caros, Segue o link para acesso (GRATUITO) ao paper publicado HOJE na revista Remote Sensing
Martinez, B.; Cassiraga, E.; Camacho, F.; Garcia-Haro, J. Geostatistics for Mapping Leaf Area Index over a Cropland Landscape: Efficiency Sampling Assessment. Remote Sens. 2010, 2, 2584-2606.

Abstract: This paper evaluates the performance of spatial methods to estimate leaf area index (LAI) fields from ground-based measurements at high-spatial resolution over a cropland landscape. Three geostatistical model variants of the kriging technique, the ordinary kriging (OK), the collocated cokriging (CKC) and kriging with an external drift (KED) are used. The study focused on the influence of the spatial sampling protocol, auxiliary information, and spatial resolution in the estimates. The main advantage of these models lies in the possibility of considering the spatial dependence of the data and, in the case of the KED and CKC, the auxiliary information for each location used for prediction purposes. A high-resolution NDVI image computed from SPOT TOA reflectance data is used as an auxiliary variable in LAI predictions. The CKC and KED predictions have proven the relevance of the auxiliary information to reproduce the spatial pattern at local scales, proving the KED model to be the best estimator when a non-stationary trend is observed. Advantages and limitations of the methods in LAI field predictions for two systematic and two stratified spatial samplings are discussed for high (20 m), medium (300 m) and coarse (1 km) spatial scales. The KED has exhibited the best observed local accuracy for all the spatial samplings. Meanwhile, the OK model provides comparable results when a well stratified sampling scheme is considered by land cover.

Caros, Segue referencia a um paper recente, 2009, do Goovaerts sobre modelagem de incerteza por indicator kriging. Recomendo.
AUTO-IK: a 2D indicator kriging program for the automated non- parametric modeling of local uncertainty in earth sciences. P. Goovaerts. Comput Geosci. 2009 June ; 35(6): 1255–1270.

Deem uma olhada no link de Bibliografia. Vocês encontrarão links para

 dois materiais de muita ajuda. Um do Professor Paulo Justiniano (LEG-UFPR)
 e outro dos Professores Paulo Inácio de Knegt López de Prado (IB, Ecologia, USP)
 e Jão L.F. Batista (Depto. Ciencias Florestais, ESALQ-USP.
 Parafrasenado Pessoa, "Valem muito a pena quando a alma não é pequena"!!