基于Landsat 8 OLI影像的延河流域土壤线提取及其应用研究

目的]以延河流域为研究区,利用自动提取算法建立典型黄土的土壤线方程,为土壤调节植被指数的计算提供基本参数。方法]基于Landsat 8OLI遥感影像,采用自动提取算法获取土壤线参数;分析归一化植被指数NDVI,土壤调节植被指数PVI,TSAVI,ATSAVI与实测盖度的相关性,探讨所构建的土壤线方程在黄土高原地区植被指数提取中的适用性。结果]通过自动算法与常规方法对比发现两者偏差较小,且自动提取算法具有较高的精度和稳定性;各植被指数与实测盖度的相关性大小为:PVINDVITSAVIATSAVI,PVI为延河流域植被盖度反演的最优植被指数,NDVI次之,TSAVI与ATSAVI较差;与NDVI指数相比,PVI指数能够较好地抵抗土壤噪声的影响,对不同植被类型的敏感性较高,更适用于植被覆盖度较低的黄土高原。结论]自动提取算法对延河流域土壤线的提取较为适用,所得参数适合于计算土壤调节植被指数。

Extraction and Application of Soil Line in Yanhe River Basin Based on Landsat 8 OLI

Objective] Taking Yanhe River basin as a study area, typical loess soil line equation was established by automatic algorithm to provide basic parameters for the calculation of the soil adjusted vegetation index. Methods] Based on Landsat 8 OLI images, soil line was extracted by automatic algorithm, then the correlation coefficients between normalized difference vegetation index(NDVI), perpendicular vegetation index(PVI), transformed soil-adjusted vegetation index(TSAVI), adjusted transformed soil-adjusted vegetation index(ATSAVI) and test coverage were calculated; and the applicability of soil line equation in vegetation index extraction was also discussed in the Loess Plateau. Results] (1) Compared with conventional method, the difference was small, and the automatic algorithm had high accuracy and stability; (2) The sequence of the correlation between vegetation index and test coverage was: PVI> NDVI> TSAVI> ATSAVI, which showed that PVI was the optimal vegetation index, NDVI was the next, TSAVI and ATSAVI were the worst to the extraction of vegetation coverage in Yanhe river basin; (3) Compared with NDVI, PVI index could reduce the influence of soil noise, and its sensitivity to different vegetation types was higher. PVI was more suitable for the Loess Plateau with low vegetation coverage. Conclusion] It is suitable to extract the soil line by automatic extraction algorithm in Yanhe river basin, and the parameters can be used to calculate the soil-adjusted vegetation index.