松嫩平原典型土壤高光谱定量遥感研究
Study on Quantitatively Remote Sensing Typical Soils in Songnen Plain,Northeast China
- 2008年第4期 页码:647-654
纸质出版日期: 2008
DOI: 10.11834/jrs.20080485
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纸质出版日期: 2008 ,
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[1]刘焕军,张柏,刘殿伟,王宗明,宋开山,杨飞.松嫩平原典型土壤高光谱定量遥感研究[J].遥感学报,2008(04):647-654.
LIU Huan-jun1, ZHANG Bai1, LIU Dian-wei1, et al. Study on Quantitatively Remote Sensing Typical Soils in Songnen Plain,Northeast China[J]. Journal of Remote Sensing, 2008,(4):647-654.
为实现松嫩平原典型土壤理化参数时空信息的快速获取
为定量遥感、精准农业等相关研究服务
以松嫩平原典型土壤的高光谱反射率为研究对象
分析土壤反射光谱特征及其与土壤理化参数的关系
建立基于反射光谱指数的土壤理化参数遥感估算模型;提取黑土光谱特征点
建立黑土反射光谱曲线模拟函数。结果表明:松嫩平原不同土壤光谱特征差异主要在450—600
600—800 nm两个吸收谷部分
土壤有机质是黑土反射光谱特征的决定因素;不同于南方土壤
铁对松嫩平原典型土壤反射光谱特征的影响较小;随着含水量的增加
土壤水分对土壤光谱反射率的作用过程可以用三次方程定量描述;基于土壤反射率及反射光谱特征的土壤理化参数光谱预测模型可以用于土壤相关理化参数的快速测定;基于光谱特征点的黑土反射光谱曲线模拟函数可以准确描述黑土的反射光谱特征
这一方法可以用于高光谱数据压缩和基于多光谱数据的高光谱反射率重建。
Songnen Plain which lies in northeast China
is the important grain production base for China
precision agriculture
serious soil erosion and quantitatively remote sensing thirst for soil spatiotemporal variation
but traditional chemical analysis method can not satisfy the need
because of little points
slow test rate and limited measuring area.Soil spectral reflectance is the compositive reflection of soil physical and chemical properties
and many studies have predicted soil properties with soil hyperspectral reflectance.Soil reflectance and its models are different for places
while the physical models
such as soil BRDF models
have been used to describe the spectral changes caused by soil surface physical variation
can not depict the spectral characteristics with different soil chemical compositions quantitatively.To quickly acquire the physical and chemical properties of typical soils in Songnen Plain
and provide the spatiotemporal soil information for quantitative remote sensing
precision agriculture and other related studies
Nongan county
which is the typical area in Songnen Plain
was selected to study the spectral characteristics of different soils.It is black soil Zone in Heilongjiang province to be selected to study the effect of physical and chemical properties on single soil spectral characteristics.Soil organic matter
including total N
total Fe and water content were measured with traditional chemical methods.Laboratory spectral reflectance between 400—2500 nm was measured with ASD FieldSpec 3 pectroradiometers.Soil hyperspectral reflectance was continuum removed
and its derivate was calculated.Spectral indices relating to soil parameters were extracted with spectral analysis methods.Then the spectral characteristics of typical soils in Songnen Plain
and their relationship with soil physical and chemical properties were analyzed.Soil properties predicting models based on spectral indices were built
and the Black soil reflectance simulating models were built with the extracted spectral controlling points.The results show that: the spectral differences among soils in Songnen Plain are mainly at the two absorption vales
the wavelength domains are 450—600 nm and 600—800 nm.Organic matter is the determining factor of Black soil reflecting spectral characteristics.Fe is not important to the spectral characteristics of soils in Songnen Plain
which is different from the case in south China.With growing soil moisture
soil reflectance decreases and increases
because of water specular effect
and the process of moisture effect on soil reflectance
the inflection point can be described quantitatively with cubic functions.The soil parameter predicting models basing on soil reflectance and its spectral characteristics can be used for soil parameter quickly measuring.As the correlation between organic matter and total N in Songnen Plain is significant
total N content of soils can be characterized with the result of organic matter spectral prediction.The Black soil reflectance simulating model(linear
quadratic)
which is based on the extracted spectral controlling points at 450
500
590
660
930 nm
describes the spectral characteristics of Black soil precisely
and can be used for hyperspectral data compression
hyperspectral reflectance reconstruction with multispectral data.
土壤高光谱反射率有机质水分铁
soilhyperspectralreflectanceorganic mattermoistureFe
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