Mixed-pixel clumping index calculation and scale analysis
混合像元聚集指数研究及尺度分析

A new algorithm for mixed-pixel clumping index (MPCI) calculation is proposed, which is based on the directional gap fraction and linear mixture model from the high-resolution remote sensing data. In this algorithm, the scale difference caused by the spatial heterogeneity of the fraction of vegetation cover (FVC), end-member clumping index (EMCI) and leaf inclination angle distribution (LAD) within the mixed pixel is well considered. The preliminary sensitivity analysis with the simulated data shows that the impact factors in a descending order are the special heterogeneity of EMCI, FVC and LAD (expressed as G function). The maximum values of the relative variation ratio caused by the heterogeneities are about 55%, 43% and 12%, correspondingly. The results also demonstrate that it is very necessary and signif icant to correct the scale difference in the mixed pixel with high special heterogeneity. It is potential to improve the accuracy of coarse leaf area index retrieval by employing the MPCI algorithm presented in this paper.