郑州邙山枣树沟黄土剖面常量元素含量的高光谱反演

Hyperspectral inversion of macro element content in loess based on the profile of Zaoshugou Village,Mangshan Mountain,Zhengzhou City

黄土自身的发生和发展过程记录了丰富的历史信息,其常量元素指标能够准确地反映出气候环境的演变。高光谱遥感技术具有波段多且连续、高分辨率的优点,可用于探测土壤属性信息的细微差异,为快速有效地获取黄土基础信息提供了技术支持。本研究以郑州邙山枣树沟村黄土剖面为研究对象,结合高光谱技术,通过对平滑处理后的原始光谱、一阶微分(FD)、二阶微分(SD)、去包络线(CR)和倒数对数(Log(1/R))与黄土剖面常量元素数开展相关性分析,选出相关系数R较大的波段作为特征波段建立基于PLSR(偏最小二乘回归)的模型进行分析。研究发现:Ga,Fe,Mg元素在郑州黄土剖面中变化指示了研究区全新世中期约5400 aBP至今经历了冷干-暖湿-冷干的的气候旋回;黄土不同地层单元的反射光谱特征虽在整体上曲线趋势相似,但其光谱反射率表现为黄土层L_(0-2)>黄土层L_(0-1)>过渡层L t>古土壤层S_(0-1)>表土层T_(S)的规律;基于偏最小二乘法的邙山黄土剖面常量元素反演模型中,Fe_(2)O_(3),CaO以及CaO/MgO的最佳反演模型为以FD光谱变换为自变量的PLSR模型,MgO的最佳反演模型为以CR光谱变换为自变量的PLSR模型;Fe_(2)O_(3),CaO和CaO/MgO的最佳反演模型能够较好地区分不同的气候区和所在区域古气候的旋回变化,MgO能较好指示所在区域的古气候演化规律,有一定的指示参考价值。

The occurrence and development themselves of loess have recorded abundant historical information,and the macro element content of loess can accurately reflect the environmental evolution.Hyperspectral remote sensing technology enjoys the advantages of being multi-band,continuous,and high-resolution.Therefore,it can be used to detect subtle differences in soil attributes and thus provide technical support for the fast and effective acquisition of basic loess information.In this paper,the loess profile of Zaoshugou Village,Zhengzhou City is studied.Combining the hyperspectral technology,the correlation between the spectral data and the macro elements of the loess was analyzed according to smoothed original spectra,first-order differential(FD),second-order differential(SD),de-envelope(CR),and reciprocal logarithm Log(1/R).A partial least square regression(PLSR)model was established using the wave band with a larger correlation coefficient R as the characteristic band.The main conclusions are as follows.The variations in Ga,Fe,and Mg elements in the loess profile indicate that the study area has experienced a cold dry-warm wet-cold dry climate cycle since the Middle Holocene about 5400 aBP.The reflectance spectra of the loess in different stratigraphic units show the characteristics with similar trends.However,their spectral reflectance is in the order of L_(0-2)>L_(0-1)>L t>S_(0-1)>T S.According to the method of partial least squares,the optimal inversion models of Fe_(2)O_(3),CaO,and CaO/MgO are the PLSR model with FD spectral transformation as the independent variable,while the best inversion model of MgO is the PLSR model with CR spectral transformation as the independent variable.The optimal inversion model of Fe_(2)O_(3),CaO,and CaO/MgO can effectively distinguish different climate zones and indicate palaeoclimate cycle changes in the region where the study area falls.The optimal inversion model of MgO can better indicate the palaeoclimate evolution law of the region where the study area falls and thus has a certain reference value.