【摘要】 针对遥感影像在南方丘陵地区典型植被丰度信息提取中存在的大量混合像元问题,为进一步提高线性解混精度,通过计算像元EVI值,构建了Landsat 8时间序列影像南方典型植被(端元)和混合像元的EVI时间序列曲线,分析了不同生育期内各种地物类型的植被指数变化曲线,发现不同地物在植被指数时间序列中具有各自独立的波动规律。选取多个端元及其EVI时间序列曲线,利用光谱匹配方法对匹配EVI时间序列曲线和多个端元进行了匹配,达到利用不同端元组合进行光谱解混的目的。试验结果表明,与传统方法相比,阔叶林解混精度有明显提高,针叶林解混精度也有所提高。该研究成果可以为南方丘陵地区植被环境的研究提供有力支撑。更多还原

【Abstract】 Aiming at the problem of a large number of mixed pixels in the extraction of typical vegetation abundance in the southern hilly region of remote sensing images,in order to further improve the precision of linear unmixing,the EVI time series curves of typical vegetation( endmember) and mixed pixels in the south of Landsat 8 time series images are constructed by calculating the EVI value of pixels. The vegetation index change curves of various feature types in different growth periods are analyzed,and it is found that different features have their own independent fluctuation rules in the vegetation index time series. By selecting multiple endmembers and their EVI time series curves,the spectral matching method is used to match the EVI time series curve and multiple endmembers,and the purpose of spectral unmixing using different endmember combinations is achieved. The test results show that compared with the traditional method,the precision of broad-leaf forest unmixing is obviously improved,and the precision of coniferous forest unmixing is also improved. The research results can provide strong support for the study of vegetation environment in the southern hilly region.更多还原