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The spatial structures displayed by remote sensing imagery are essential information characterizing the nature and the scale of spatial variation of Earth surface processes. This paper provides a new approach to characterize the spatial structures within remote sensing imagery using stochastic models and geostatistic metrics. Up to now, the second-order variogram has been widely used to describe the spatial variations within an image. In this paper, we demonstrate its limitation to discriminate distinct image spatial structures. We introduce a different geostatistic metric, the first-order variogram, which used in combination with the second-order variogram, will prove its efficiency to describe the image spatial structures. We then develop a method based on the simultaneous use of both first- and second-order variogram metrics to model the image spatial structures as the weighted linear combination of two stochastic models: a Poisson line mosaic model and a multi-Gaussian model. The image spatial structures are characterized by the variance weight and the variogram range related to each model. This method is applied to several SPOT-HRV Normalized Difference Vegetation Index (NDVI) images from the VALERI database in order to characterize the nature of the processes structuring different types of landscape. The mosaic model is an indicator of strong NDVI discontinuities within the image mainly generated by anthropogenic processes such as the mosaic pattern of crop sites. The multi-Gaussian model shows evidence of diffuse and continuous variation of NDVI generally engendered by ecological and environmental processes such as the fuzzy pattern observed over forest and natural vegetation sites. Index Terms--First-order variogram, landscape, multi-Gaussian model, normalized difference vegetation index (NDVI), Poisson line mosaic model, second-order variogram, spatial structure, stochastic simulation.

Initiated in 1984, the Committee Earth Observing Satellites' Working Group on Calibration and Validation (CEOS WGCV) pursues activities to coordinate, standardize and advance calibration and validation of civilian satellites and their data. One subgroup of CEOS WGCV, Land Product Validation (LPV), was established in 2000 to define standard validation guidelines and protocols and to foster data and information exchange relevant to the validation of land products. Since then, a number of leaf area index (LAI) products have become available to the science community at both global and regional extents. Having multiple global LAI products and multiple, disparate validation activities related to these products presents the opportunity to realize efficiency through international collaboration. So the LPV subgroup established an international LAI intercomparison validation activity. This paper describes the main components of this international validation effort. The paper documents the current participants, their ground LAI measurements and scaling techniques, and the metadata and infrastructure established to share data. The paper concludes by describing plans for sharing both field data and high-resolution LAI products from each site. Many considerations of this global LAI intercomparison can apply to other products, and this paper presents a framework for such collaboration. Index Terms--Committee on Earth Observing Satellites (CEOS) leaf area index (LAI), validation.

This study investigates the representativeness of land cover and leaf area index (LAI) sampled by a global network of sites to be used for the evaluation of land biophysical products, such as LAI or fAPAR, derived from current satellite systems. The networks of sites considered include 100 sites where ground measurements of LAI or fAPAR have been performed for the validation of medium resolution satellite land biophysical products, 188 FLUXNET sites and 52 AERONET sites. All the sites retained had less than 25% of water bodies within a 8 x 8 [km.sup.2] window, and were separated by more than 20 km. The ECOCLIMAP global classification was used to quantify the representativeness of the networks. It allowed describing the Earth's surface with seven main types and proposed a climatology for monthly LAI values at a spatial resolution around 1 km. The site distribution indicates a large over representation of the northern midlatitudes relative to other regions, and an under-representation of bare surfaces, grass, and evergreen broadleaf forests. These three networks represent all together 295 sites after elimination of sites that were too close. They were thus completed by 76 additional sites to improve the representativeness in latitude, longitude, and surface type. This constitutes the BELMANIP network proposed as a benchmark for intercomparison of land biophysical products. Suitable approaches to conducting intercomparison at the sites are recommended. Index Terms--Global land biophysical products, intercomparison, leaf area index (LAI), validation.