摘要
利用Landsat 8 OLI影像反演三江源区玉树、称多及玛多县的表层土壤全氮含量空间分布格局,选取光谱反射率（R）、光谱反射率的倒数（1/R）、光谱反射率倒数的对数〔lg（1/R）〕3个光谱指标,与表层土壤（0-30 cm）全氮实测数据进行相关性分析,筛选相关性最高的光谱指标,以达到显著性相关水平波段的主成分分量建立回归模型。结果表明：OLI影像的B1-B4和B7的R、1/R、lg（1/R）均与实测全氮数据达到显著性相关水平,以lg（1/R）变换最为明显;利用这5个波段lg（1/R）的第一、第二主成分建立负二次多项式回归模型,其中建模样本的R2为0.621,RMSE为2.075,验证样本的R2为0.730,RMSE为1.493,RPD为1.849,反演模型精度较高,稳定性较好。利用OLI影像可较好的估算表层土壤全氮含量的空间分布格局。
In this paper,taking Yushu county,Chengduo county and Maduo county in Sanjiangyuan Regions as a case,the Landsat 8 OLI image was used to predict the spatial distribution pattern of topsoil total nitrogen contents.The spectrum reflectance（ R） and its two kinds of transformation forms,including the spectrum reflectance reciprocal（ 1 / R） and the logarithm of spectrum reflectance reciprocal [lg（ 1 / R） ],selected to relate to soil total nitrogrn measured in laboratory. Firstly,correlation analysis between above three spectral index and the measured topsoil（ 0-30 cm） total nitrogen was conducted. Secondly,according correlation analysis results,the spectral index with the highest correlation was selected. In the end,the regression models were established using principal component with significant levels of correlated bands. The results show that the spectral reflectance and its two transformation forms from B1-B4,B7 were significantly correlated levels with the measured data,in which the lg（ 1 / R） was the most obvious. The negative quadratic polynomial model was set up through the first and second principal components of lg（ 1 / R） of these five bands,in which the R2 of calibration model R2 was 0. 621,RMSE was 2. 075,validation samples R2 was 0. 730,RMSE was 1. 493 and RPD was 1. 849,suggesting the predicting model having a high precision,good stability. Therefore the OLI images could be used to estimate the spatial distribution pattern of topsoil total nitrogen better.
出处
《干旱区研究》
CSCD
北大核心
2015年第5期890-896,共7页
Arid Zone Research
基金
国家自然科学基金项目(40861022)
国家科技支撑计划课题(2012BAC08B04)
青海省科技厅自然科学基金项目(2011-Z-903)
青海师范大学创新基金项目(QS2012-08)
