土壤发射率光谱与土壤元素含量的关系研究

发布时间：2018-03-07 16:02

本文选题：土壤发射率　切入点：中红外波段　出处：《光谱学与光谱分析》2017年02期 　论文类型：期刊论文

【摘要】：通过对全国十几个地区共26个土壤样品进行元素含量和红外光谱测定,分析了土壤中红外发射率光谱特征,研究了土壤发射率光谱与土壤的硝态氮(NO_3-N)、磷(P)、钾(K)、钙(Ca)、镁(Mg)、铜(Cu)、铁(Fe)、锰(Mn)、锌(Zn)等元素以及pH值和有机质(OM)含量的相关性,并利用偏最小二乘回归和多元逐步回归建立了利用发射率光谱估算土壤各种元素含量的回归模型。由此找到了土壤元素含量与土壤发射率相关性最大的特征波段,并遴选出了不同波段哪些土壤元素与发射率的相关性最紧密,为开展土壤发射率的影响因素研究和由土壤中红外光谱预测土壤元素含量奠定了理论基础。研究结果显示:(1)在8~10μm波段范围内,土壤发射率与土壤元素相关性从高到低依次为Ca,Mg,Mn和Fe,相关系数最高为0.85,最低为-0.5;另外K,Fe,NO_3-N和Zn与发射率的相关性在6~8μm波段范围内依次减小,相关系数最高为0.75,最低为0.48;而在10~14μm波段内,Mn和K与发射率有较强的相关性,相关系数约为0.5;(2)土壤发射率与土壤pH值之间大致呈抛物线关系,在土壤的pH值为7时,发射率最高,随着土壤越酸或越碱,发射率逐渐降低;(3)在建立土壤各元素含量的预测模型时发现,偏最小二乘回归估算土壤各元素含量的精度要高于多元逐步回归,尤其是Ca,Cu和Fe这些元素,建模和交叉验证的R~2分别能达到0.9、0.8以上;利用观测的土壤发射率光谱根据传感器波谱响应函数模拟得到的MODIS和ASTER传感器红外波段的发射率数据,通过多元逐步回归模型对土壤各元素含量进行估算发现,利用ASTER的热红外波段发射率估算土壤Ca含量时建模和验证的决定系数为0.774和0.892;用MODIS的红外波段发射率估算土壤Ca和Fe含量的建模和验证的决定系数都在0.85以上,估算Mg和K的建模和验证的决定系数都在0.5以上;并且ASTER的第10和11波段和MODIS的第28,29和30波段对土壤各元素有较高的敏感性,更适合用于土壤各元素的估算。
[Abstract]:The spectral characteristics of infrared emissivity in soil were analyzed by measuring the elemental content and infrared spectrum of 26 soil samples in more than a dozen regions of China. The correlation between soil emissivity spectra and elements such as no _ 3-N _ 2O _ 3-N, P _ 2O, K _ 2O, Ca ~ (2 +), mg ~ (2 +), Cu ~ (2 +), Fe ~ (2 +), mn ~ (2 +) ~ (2 +), Zn ~ (2 +), pH value and content of organic matter were studied. Based on partial least square regression and multivariate stepwise regression, a regression model for estimating the content of various elements in soil by emissivity spectrum was established. The characteristic band with the greatest correlation between soil element content and soil emissivity was found. And selected which soil elements in different bands are most closely related to emissivity, The results provide a theoretical basis for the study of the influencing factors of soil emissivity and the prediction of soil element content by infrared spectroscopy in soil. The results show that the content of elements in the soil is in the range of 810 渭 m. The correlation between soil emissivity and soil elements is Caomg mn and Fe from high to low, the correlation coefficient is 0.85, and the lowest is -0.5. In addition, the correlation between emissivity and soil emissivity decreases in turn in the range of 68 渭 m. The correlation coefficient was 0.75 and the lowest was 0.48.The correlation coefficient of mn and K with emissivity was about 0.5 ~ (2) in 10 ~ (14) 渭 m band.) there was a parabolic relationship between soil emissivity and soil pH value, and the emissivity was the highest in the soil pH value of 7:00. The emissivity decreased gradually with the increase of soil acidity or alkalinity. When the prediction model of soil elements content was established, it was found that the accuracy of partial least square regression was higher than that of multivariate stepwise regression, especially CaCU and Fe elements. The measured soil emissivity spectra were simulated according to the spectral response function of the MODIS and ASTER sensors, and the emissivity data of the infrared bands of the MODIS and ASTER sensors were obtained by using the observed soil emissivity spectra according to the spectral response function of the sensors. The multiple stepwise regression model was used to estimate the contents of various elements in soil. The determination coefficients of modeling and verification for estimating soil Ca content by using ASTER's thermal infrared emissivity are 0.774 and 0.892, and those for modeling and verifying soil Ca and Fe contents by MODIS infrared band emissivity are above 0.85, respectively. The determination coefficients for modeling and verification of mg and K are all above 0.5, and bands 10 and 11 of ASTER and 2829 and 30 of MODIS are more sensitive to soil elements, so they are more suitable for estimating soil elements.
【作者单位】：中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室;中国科学院大学;中国农业大学农业部设施农业工程重点开放实验室;
【基金】：国家自然科学基金项目(41271380) 国家重点基础研究发展计划(973)项目(2013CB733406)资助
【分类号】：S151.9

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