光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2013年
11期
3111-3115
,共5页
土壤%总氮%高光谱%多元线性回归
土壤%總氮%高光譜%多元線性迴歸
토양%총담%고광보%다원선성회귀
Soil%Total nitrogen%Hyperspectra%Multivariate linear regression
利用高光谱遥感技术反演土壤性质已经成为土壤学和遥感科学研究领域的新手段,特别对土壤化学元素含量的高光谱反演,已成为土壤元素快速监测方法的的研究热点。以往研究往往关注不同类型土壤的化学元素光谱响应特征模型,以试图找到普适性的元素-光谱反演模型。由于成土因素的复杂性,土壤类型及其化学元素分布具有明显的空间异质性特征,宏观尺度上的土壤-光谱统计反演模型客观上具有较大的不确定性。若范围缩小到同一个气候带,土壤生物地球化学反应过程较相似,土壤化学元素-光谱反演模型的不确定性相对较小。以福州市为研究区,采集福州市典型红壤样品135个,研究土壤全氮含量的高光谱响应特征,对土壤样品在350~2500 nm的光谱反射率分别进行倒数对数、微分等五种变换,分析变换后的光谱信息与土壤总氮含量的相关性,筛选出强相关敏感波段,通过设计不同的建模和验证样品比例,用逐步多元线性回归获得福州土壤的氮元素高光谱反演优化模型。结果表明:亚热带红壤全氮的敏感光谱波段为:可见光634~688 nm和红外872,873,1414和1415 nm ;亚热带沿海地区土壤全氮-高光谱反演的优化模型为:Y=5.384X664-1.039(决定系数 R2为0.616,均方根误差为0.422 mg · g -1,检验R2为0.608,均方根误差为0.546mg·g -1),该模型可以用于福州地区土壤全氮的光谱快速监测。
利用高光譜遙感技術反縯土壤性質已經成為土壤學和遙感科學研究領域的新手段,特彆對土壤化學元素含量的高光譜反縯,已成為土壤元素快速鑑測方法的的研究熱點。以往研究往往關註不同類型土壤的化學元素光譜響應特徵模型,以試圖找到普適性的元素-光譜反縯模型。由于成土因素的複雜性,土壤類型及其化學元素分佈具有明顯的空間異質性特徵,宏觀呎度上的土壤-光譜統計反縯模型客觀上具有較大的不確定性。若範圍縮小到同一箇氣候帶,土壤生物地毬化學反應過程較相似,土壤化學元素-光譜反縯模型的不確定性相對較小。以福州市為研究區,採集福州市典型紅壤樣品135箇,研究土壤全氮含量的高光譜響應特徵,對土壤樣品在350~2500 nm的光譜反射率分彆進行倒數對數、微分等五種變換,分析變換後的光譜信息與土壤總氮含量的相關性,篩選齣彊相關敏感波段,通過設計不同的建模和驗證樣品比例,用逐步多元線性迴歸穫得福州土壤的氮元素高光譜反縯優化模型。結果錶明:亞熱帶紅壤全氮的敏感光譜波段為:可見光634~688 nm和紅外872,873,1414和1415 nm ;亞熱帶沿海地區土壤全氮-高光譜反縯的優化模型為:Y=5.384X664-1.039(決定繫數 R2為0.616,均方根誤差為0.422 mg · g -1,檢驗R2為0.608,均方根誤差為0.546mg·g -1),該模型可以用于福州地區土壤全氮的光譜快速鑑測。
이용고광보요감기술반연토양성질이경성위토양학화요감과학연구영역적신수단,특별대토양화학원소함량적고광보반연,이성위토양원소쾌속감측방법적적연구열점。이왕연구왕왕관주불동류형토양적화학원소광보향응특정모형,이시도조도보괄성적원소-광보반연모형。유우성토인소적복잡성,토양류형급기화학원소분포구유명현적공간이질성특정,굉관척도상적토양-광보통계반연모형객관상구유교대적불학정성。약범위축소도동일개기후대,토양생물지구화학반응과정교상사,토양화학원소-광보반연모형적불학정성상대교소。이복주시위연구구,채집복주시전형홍양양품135개,연구토양전담함량적고광보향응특정,대토양양품재350~2500 nm적광보반사솔분별진행도수대수、미분등오충변환,분석변환후적광보신식여토양총담함량적상관성,사선출강상관민감파단,통과설계불동적건모화험증양품비례,용축보다원선성회귀획득복주토양적담원소고광보반연우화모형。결과표명:아열대홍양전담적민감광보파단위:가견광634~688 nm화홍외872,873,1414화1415 nm ;아열대연해지구토양전담-고광보반연적우화모형위:Y=5.384X664-1.039(결정계수 R2위0.616,균방근오차위0.422 mg · g -1,검험R2위0.608,균방근오차위0.546mg·g -1),해모형가이용우복주지구토양전담적광보쾌속감측。
The present paper studied the hyperspectral response characteristics of red soil ,with 135 soil samples in Fuzhou city . After monitoring the hypersectral reflection of soil samples with ASD (analytical spectral device) and total nitrogen contents with Vario MAX(for nitrogen and carbon analysis) ,the paper gained the spectral reflection data between 350~2 500 nm (resolution is 1 nm) and soil total nitrogen contents .Then the paper treated the hyperspectral reflection data with 5 mathematic conversions such as first derivative and second derivative conversions of original reflection ,reciprocal logarithmic conversion and its first de-rivative and second derivative conversion in advance .The next step was to calculate the correlation coefficient of soil nitrogen and the above spectral information ,and select the sensitive spectral bands according to the highest correlation coefficient .Finally ,by designing different proportions of modeling and validation sample data sets ,the paper established the quantitative linear models between soil total nitrogen contents and hyperspectral reflection and its 5 converted information ,the final optimal mathematic model between soil nitrogen and hyperspectral information was significantly determined .Results showed that 634~688 ,872 , 873 ,1 414 and 1 415 nm were the main sensitive bands for soil total nitrogen ,and Y=5.384X664 -1.039 (Y represents soil ni-trogen content ,X664 is the soil spectral absorbance value at 664 nm) was the optimal soil total nitrogen predicting model (in the model ,the determination coefficients R2 and the RMSE of total nitrogen were 0.616 and 0.422 mg · g -1 ,the inspection coeffi-cient R2 and the RMSE were 0.608 and 0.546 mg · g -1 respectively) .The model can be used to rapidly monitor soil total nitro-gen with hyperspectral reflection in Fuzhou area .