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Spatial variability in scale transferring of vegetation LAI inversed from remotely sensed data

In inversing Leaf Area Index (LAI) from remotely sensed data, the transformation of the remotely sensed data from one kind of resolution to another has become a significant problem because of the heterogeneity in pixel. In this paper, based on an analysis of the reasons for error appearing in LAI inversion, the spatial heterogeneity in pixel was described by semivariance. The following conclusions were obtained from this study: In the study area, the spatial heterogeneity of reeds is caused by both the random element and the extent of spatial self-correlation. These factors can be described by the parameters of semivariogram, i.e., nugget and sill. In a pure pixel, little variation was found between the 30m and 60m scale, which means that the scaling problem for pure pixels may be ignored. However, while the degree of heterogeneity within a pixel increases, the spatial heterogeneity in the pixel with larger scale may be somewhat hided compared with the pixel with smaller scale. Results also showed that valid spatial self-correlation scale of reeds in the study area is within 360m.