中文摘要：

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（NO3-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,NO3-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

英文摘要：

In this paper,based on the measurements of soil elements content and infrared spectra of 26 soil samples collected in more than 10 places,the relationship between soil emissivity in mid-infrared bands and the content of 11 soil elements including organic matters such as NO3-N,P,K,Ca,Mg,Cu,Fe,Mn,Zn and pH are analyzed.The bands where the soil elements content are significantly correlated with emissivity are given.And soil elements content estimation method is established based on the soil emissivity spectra with the partial least squares regression model and multiple stepwise regression model.The resultsshow that：（1）In 8-10μm,the correlation coefficient（R-2）between Ca and soil emissivity is the highest,followed by Mg,Mn and Fe,with the highest correlation coefficient of 0.85 and the lowest,0.52.In the range of 6-8μm,the correlations between the contents of K,Fe,NO3-N,Zn and emissivity decrease gradually,with the highest correlation coefficient of 0.75 and the lowest 0.48.In 10-14μm,the correlation between soil elements contents and emissivity is the highest for Mn,followed successively by P and K.（2）The scatter plot of soil emissivity and pH value has a parabola relation basically.The emissivity is the highest when pH value is 7,while the emissivity decreases gradually with the gradual decrease of pH value.（3）The accuracy of the estimated soil elements content from the partial least squares regression method is higher than that from the multiple stepwise regression method.It is noted that R-2 between the measurements and the estimates for the elements of Cu,Fe and Ca from the partial least squares regression method are very high（larger than 0.9）.Additionally,using the simulated emissivity spectrum in the ASTER thermal infrared bands,modeling R-2 and validation R-2 between the measurements and the estimates for the elements of Ca from the multiple stepwise regression method are high（0.774 and 0.892,respectively）.Using the simulated emissivity spectrum in the MODIS infrared bands,modelin