紫色土土壤全氮和全磷含量的高光谱遥感预测

高光谱遥感技术是土壤养分预测的有效手段之一。以三峡库区王家沟小流域为研究区，在对土壤样本的理化性质和实验室反射光谱数据分析和测量的基础上，用偏最小二乘回归方法建立了紫色土土壤全氮和全磷含量的预测模型，并用33个水稻土土壤样本对紫色土土壤养分预测模型进行了验证。结果显示，紫色土土壤全氮预测模型得到的土壤样本预测值和实测值之间的总相关系数达到了0.672，而紫色土土壤全磷预测模型得到的相关系数只有0.498; 用紫色土土壤养分预测模型对水稻土土壤养分进行预测得到的相关系数分别为0.550和0.124。因此，用高光谱来预测紫色土土壤全氮含量具有一定的可行性，但高光谱对于紫色土全磷含量的预测效果相对较差;土壤养分预测模型在不同类型土壤之间并不具有很好的通用性。

Prediction of Total Nitrogen and Total Phosphorus Concentrations in Purple Soil Using Hyperspectral Data

Hyper-spectral remote sensing is one of the effective means for prediction of soil nutrients. Taking Wangjiagou small watershed of Three Gorges Reservoir Area as researching zone, based on the soil physicochemical properties, reflective spectrum analysis and measurement, were built predictive models for total phosphorous and total phosphorus concentrations in purple soil. Meanwhile, 33 soil samples from paddy soil were used to validate the prediction models for soil nutrients in purple soil. Results show that the total correlation coefficients between their predicted values and measured values of total nitrogen and total phosphorus concentration in purple soil are 0.672 and 0.498, respectively. Correlation coefficients obtained from predictive model of purple soil nutrients validated by paddy soil samples are 0.550 and 0.124. Therefore, it is reasonable to use hyper-spectrum method to prediction total nitrogen concentration. But prediction accuracy for total phosphorus concentration in purple soil is relatively poor. The prediction model of soil nutrients in purple soil is not suitable for paddy soil.