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遥感技术与应用
特约论文     
可见光—近红外光谱估算三江源区不同土壤全氮含量
高小红,杨扬,张威,贾伟,李金山,田成明,张艳娇,杨灵玉,何林华
(青海师范大学生命与地理科学学院,青海省自然地理与环境过程重点实验室,青藏高原环境与资源教育部重点实验室,青海 西宁 810008)
Using Visible and Near-infrared Reflectance Spectroscopy to Estimate Total Nitrogen Contents for Different Soil Types in the Sanjiangyuan Regions
Gao Xiaohong,Yang Yang,Zhang Wei,Jia Wei,Li Jinshan,Tian Chengming,Zhang Yanjiao,Yang Lingyu,He Linhua
(School of Life and Geographical Sciences, Key Laboratory of Physical Geography and Environment Process in Qinghai Province,Key Laboratory of Education Ministry on Environment and Resources in Qinghai-Tibet Plateau,Qinghai Normal University,Xining,810008,China)
 全文: PDF 
摘要:

近年来可见光—近红外反射光谱已被广泛应用于估算土壤全氮含量,为大范围区域土壤全氮含量获取提供了一种快速、有效的方法。基于实验室测定的三江源区146个表层土壤(0~30 cm)样品的反射光谱数据(350~2 500 nm)与全氮含量数据;利用偏最小二乘回归(PLSR)和反向传播神经网络(BPNN)两种模型方法与光谱反射率(REF)及其4种数学预处理变换相结合,分别建立分土壤类型样本和总体样本全氮估算模型;评估利用可见光—近红外光谱技术预测三江源区土壤全氮含量的能力。结果表明:BPNN模型的R 2cal R2val及验证RPD的平均值分别为0.87、0.81与2.28;而PLSR模型则相应为0.75、0.72和1.95;表明BPNN模型预测能力整体上要优于PLSR模型。BPNN与光谱各种形式的结合均具有良好、或接近良好预测全氮的能力;而PLSR与REF、倒数对数(Log(1/R))及波段深度(BD)的结合仅少部分具有良好估算能力、大部分则为粗略估算能力,一阶微分(FDR)和二阶微分(SDR)估算精度均较低,尤其是SDR(R2<0.5,RPD=1.10~1.27)均不具备估算能力。总体样本所建模型稳定性好于分土壤类型,分土壤类型建模差异性明显;此外,总体来看,BPNN模型比PLSR建模精度高、模型稳定性好,但PLSR模型可操作性强于BPNN模型。

关键词: 土壤全氮可见光&mdash近红外反射光谱偏最小二乘回归(PLSR)反向传播神经网络(BPNN)三江源区玉树县玛多县    
Abstract:

Visible and Near-Infrared Reflectance Spectroscopy (VNIRS) has extensively been used to estimate soil total nitrogen (TN) concentration,and can provide a rapid,convenient method for quantitatively obtaining soil TN content in a wide range of areas.In this study,we evaluated the prediction ability of Visible and Near-Infrared Reflectance Spectroscopy (VNIRS) for estimating soil TN in the Sanjiang Yuan regions of Qinghai province.Firstly,we collected about 146 surface soil samples (0~30 cm),including four soil types during the period from August 7 to 17 of 2012 in Yushu and Maduo counties;secondly,we respectively measured soil reflectance spectrum by ASD FieldSpec 4 portable spectrometer (Analytical Spectral Devices,Inc.,Boulder Colorado,2012) with the spectral range of 350~2 500 nm,and soil TN by using Vario EL Ⅲ element analyzer of ELEMENTAR Inc.in the laboratory;and then we respectively adopted PLSR and BPNN models to relate soil TN to raw spectral reflectance and its four pre-processing transformations for the overall soil samples and each soil types samples.The results showed that the average coefficients of determination(R2) of calibration and validation for BPNN are respectively 0.87 and 0.81 with the mean RPDval of 2.28,whereas those of PLSR model are 0.75,0.72 and 1.95 respectively,which suggest that BPNN has a better prediction ability than PLSR as a whole;The combination of BPNN and the raw reflectance spectrum (REF) and its all pre-processing transformations performed a good or closer good prediction ability for different and overall soil types;whereas the combination of PLSR model and REF,Log(1/R),BD produced a rough or good prediction ability for estimating TN,however,FDR and SDR with poor prediction ability,especially SDR (R2 cal<0.5,R2val<0.5,RPDval=1.10~1.27) hasnt the ability to predict soil TN;As a whole,TN estimating from the overall soil samples can produce more stability prediction accuracies than single soil types,whereas that from single soil type samples can reflect the difference among soil types;BPNN model accuracies are superior to those of PLSR model,but PLSR has stronger operability,and can show the difference among soil types,and different among transformation indicators as well as.

Key words: Soil total nitrogen(TN)    Visible-near infrared reflectance spectroscopy(VNIRS)    Partial least square regression(PLSR)    Back propagation neural network(BPNN)    Sanjiangyuan Regions    Yushu Counties    Maduo counties
收稿日期: 2014-04-17 出版日期: 2015-12-08
:  TP 79  
基金资助:

青海省科技厅自然科学基金项目(2011-Z-903)。

作者简介: 高小红(1963\|),女,陕西白水人,教授,主要从事遥感与地理信息系统应用方面的研究。Email:xiaohonggao226@163.com。
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引用本文:

高小红,杨扬,张威,贾伟,李金山,田成明,张艳娇,杨灵玉,何林华. 可见光—近红外光谱估算三江源区不同土壤全氮含量[J]. 遥感技术与应用, 10.11873/j.issn.1004-0323.2015.5.0849 .

Gao Xiaohong,Yang Yang,Zhang Wei,Jia Wei,Li Jinshan,Tian Chengming,Zhang Yanjiao,Yang Lingyu,He Linhua. Using Visible and Near-infrared Reflectance Spectroscopy to Estimate Total Nitrogen Contents for Different Soil Types in the Sanjiangyuan Regions. Remote Sensing Technology and Application, 10.11873/j.issn.1004-0323.2015.5.0849 .

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.5.0849        http://www.rsta.ac.cn/CN/Y2015/V30/I5/849

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