关键词: 微生物群落多样性, 碱性磷酸酶, 磷细菌肥, Olsen-P, 复垦土壤

Abstract: Compared with dense vegetation area, arid and semi-arid areas show a lower accuracy in vegetation fractional coverage (VFC) calculation using remote sensing method, due to its poor and scattered vegetation coverage. To solve the above problems, restrictive and adaptation factors of three typical traditional VFC inversion methods, the regression model method, pixel dichotomy method and the spectral unmixing method in arid areas were analyzed in this paper. Then the traditional methods were improved based on groundmeasured spectrums through analysis of the sensitivity of NDVI_S to vegetation cover in arid areas. A VFC inversion experiment was carried out in a typical arid area in Xinjiang using the Landsat-8 OLI data. The measured VFC data were used to verify the experiment results. The results showed that the different methods showed certain difference for VFC inversion accuracy. The fully constrained least squares linear spectral unmixing method based on spectral unmixing showed the highest accuracy in the arid area, with highest consistency with the ground measured VFC (R²=0.989), followed by the pixel dichotomy method (R²=0.848) and the regression model method (R²=0.827).

Key words: Phosphorus bacteria fertilizer, reclaimed soil, microbial community diversity, alkaline phosphatase, Olsen-P