滨海盐土土壤水分的高光谱参数及估测模型

应用生态学报

滨海盐土土壤水分的高光谱参数及估测模型

李晨¹,张国伟²,周治国¹,赵文青¹,孟亚利¹,陈兵林¹,王友华^1*

(¹南京农业大学/农业部作物生理生态与生产管理重点实验室/江苏省现代作物生产协同创新中心，南京 210095； ²江苏省农业科学院经济作物研究所，南京 210014)

出版日期:2016-02-18 发布日期:2016-02-18

Hyperspectral parameters and prediction model of soil moisture in coastal saline.

LI Chen¹, ZHANG Guo-wei², ZHOU Zhi-guo¹, ZHAO Wen-qing¹, MENG Ya-li¹, CHEN Bing-lin¹, WANG You-hua^1

(¹Ministry of Agriculture Key Laboratory of Crop Physiology, Ecology and Management/ Jiangsu Province Modern Crop Production Collaborative Innovation Center, Nanjing Agricultural University, Nanjing 210095, China; ²Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China)

Online:2016-02-18 Published:2016-02-18

摘要/Abstract

摘要： 基于滨海盐土5个试验点的土壤含水量和室内土壤表面高光谱反射率，综合分析了350～2500 nm波段范围内土壤含水量与土壤光谱之间的关系，并基于比值光谱指数(RSI)、归一化光谱指数(NDSI)和差值光谱指数(DI)确定了光谱参数，进而构建土壤含水量估测定量模型.结果表明：滨海盐土原始光谱反射率与土壤含水量呈显著负相关关系，且最大负相关出现在1930 nm(r=0.86)附近.对RSI、NDSI和DI的直线回归方程、幂函数回归方程进行对比，以RSI(R₁₄₀₇，R₁₄₅₉)为自变量构建的土壤含水量指数函数线性回归方程决定系数最大(0.780)，标准误较小(0.016)，拟合方程为y=0.00001e^9.72053x.估测模型能够更好地监测滨海盐土土壤水分状况.基于RSI(R₁₄₀₇，R₁₄₅₉)构建的模型可实现对江苏省滨海盐土土壤水分的精确监测.

Abstract: Based on the data of soil moisture content and indoor soil surface spectral reflectance from five sampling sites of coastal saline soil, this paper analyzed the relationship between soil moisture content and soil spectrum in wavelength 350-2500 nm. We determined spectral parameters under ratio spectral index (RSI), normalized difference spectral index (NDSI) and difference spectral index (DI), and established the quantitative model of soil moisture content. The results showed significant negative correlation between spectral reflectance and soil moisture content, and the maximum negative correlation was near 1930 nm (r=0.86). By comparison of the regression equation of RSI, NDSI and DI, it was found that the regression equation of exponential function (y=0.00001e^9.72053x) built by soil moisture content based on RSI (R₁₄₀₇,R₁₄₅₉) presented the maximum R₂(0.780) and the minimum SE (0.016). The established model based on RSI (R₁₄₀₇, R₁₄₅₉) could be used to monitor soil moisture content accurately in Jiangsu coastal saline soils.

李晨1,张国伟2,周治国1,赵文青1,孟亚利1,陈兵林1,王友华1*. 滨海盐土土壤水分的高光谱参数及估测模型[J]. 应用生态学报.

LI Chen1, ZHANG Guo-wei2, ZHOU Zhi-guo1, ZHAO Wen-qing1, MENG Ya-li1, CHEN Bing-lin1, WANG You-hua1. Hyperspectral parameters and prediction model of soil moisture in coastal saline.[J]. Chinese Journal of Applied Ecology.