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| 1 | 中国主要土壤高光谱反射特性分类与有机质光谱预测模型显示文摘土壤可见-近红外漫反射光谱是当前对地遥感观察和土壤近地传感器研究的重要方向,同时也被认为是土壤数字制图、精确农业和土壤资源调查等方面最重要的数据获取技术. 从中国西藏、新疆、黑龙江、海南等地采集16种土类的1581个土壤样本,经干燥过筛后统一采用 ASD光谱仪测量了其室内可见-近红外反射光谱(350-2500 nm). 对所有的土壤光谱数据采用Savitzky-Golay平滑加一阶微分进行转换,来减少大样本数据受到实验室光学测试环境条件差异的影响,然后对数据进行主成分变换降维处理. 引入模糊k-means方法进行大样本光谱数据的最佳分类数目计算,并将中国土壤光谱数据分成五类,各自代表了不同的土壤矿物和有机组分,主要类型与国际同行类似成果有可比性. 最后提出了采用土壤光谱分类方法结合偏最小二乘回归法(PLSR)方法建立土壤有机质的光谱分类-局部预测模型,结果比未分类直接采用PLSR方法的一阶微分-全局预测模型的精度有了显著提高,其预测模型的R2和RPD两个指数分别从0.697和1.817提高到0.899和3.158. | 史舟 王乾龙 彭杰 纪文君 刘焕军 李曦 Raphael A VISCARRA ROSSEL | 2014 | 中国科学:地球科学2014，44，5： | 100 |
| 2 | Development of a national VNIR soil-spectral library for soil classification and prediction of organic matter concentrations显示文摘Soil visible-near infrared diffuse reflectance spectroscopy(vis-NIR DRS)has become an important area of research in the fields of remote and proximal soil sensing.The technique is considered to be particularly useful for acquiring data for soil digital mapping,precision agriculture and soil survey.In this study,1581 soil samples were collected from 14 provinces in China,including Tibet,Xinjiang,Heilongjiang,and Hainan.The samples represent 16 soil groups of the Genetic Soil Classification of China.After air-drying and sieving,the diffuse reflectance spectra of the samples were measured under laboratory conditions in the range between 350 and 2500 nm using a portable vis-NIR spectrometer.All the soil spectra were smoothed using the Savitzky-Golay method with first derivatives before performing multivariate data analyses.The spectra were compressed using principal components analysis and the fuzzy k-means method was used to calculate the optimal soil spectral classification.The scores of the principal component analyses were classified into five clusters that describe the mineral and organic composition of the soils.The results on the classification of the spectra are comparable to the results of other similar research.Spectroscopic predictions of soil organic matter concentrations used a combination of the soil spectral classification with multivariate calibration using partial least squares regression(PLSR).This combination significantly improved the predictions of soil organic matter(R2=0.899;RPD=3.158)compared with using PLSR alone(R2=0.697;RPD=1.817). | SHI Zhou WANG QianLong PENG Jie JI WenJun LIU HuanJun LI Xi Raphael A VISCARRA ROSSEL | 2014 | Science China Earth Sciences2014，57，7： | 32 |
| 3 | 黄土的红外反射光谱与红外光声光谱特征及其差异研究显示文摘红外光谱法作为一种新的研究手段已经广泛应用于土壤分析,由其检测区域和手段的不同又可分为多种光谱类型。本研究以第四纪黄土为例,系统地比较了近红外区和中红外区反射光谱和光声光谱的吸收特征及其差异。结果表明,中红外光谱比近红外光谱的信息更为丰富,且中红外光谱与样品中物质的特征吸收关系更加密切,从而更有利于=L壤定性与定量分析。土壤的反射光谱和光声光谱表现出了明显不同的特征,在近红外区,反射光谱和光声光谱吸收明显不同,而在中红外区,反射光谱和光声光谱具有相对应的吸收,但相对吸收强度明显不同,且吸收峰的位置也发生改变,尤其在1000—2000cm。谱区,反射光谱相互干扰很强,而光声光谱的吸收特征更为明显。在黄土的分类鉴别上,反射光谱优于光声光谱。红外反射光谱和光声光谱在不同波段下具有不同的吸收灵敏度,在土壤定性与定量分析中各自都将具有其明显的优势。 | 马赵扬 杜昌文 周健民 周桂勤 Viscarra Rossel RA | 2012 | 土壤2012，44，5： | 4 |
| 4 | Using data mining to model and interpret soil diffuse reflectance spectra显示文摘 | R.A. Viscarra Rossel T. Behrens | 2010 | Geoderma2010，，1： | 1 |
| 5 | Discrimination of Australian soil horizons and classes from their visible-near infrared spectra显示文摘 | Rossel Viscarra R A Webster R | 2011 | European Journal of Soil Science2011，62，4： | 1 |
| 6 | Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: An Australian case study显示文摘 | Gomez C Viscarra Rossel R A McBratney A B | 2008 | Geoderma2008，146，4： | 1 |
| 7 | Soil organiccarbon prediction by hyperspectral remote sensing and field vis-NIR spec-troscopy:An Australian case study显示文摘 | GOMEZ C VISCARRA ROSSEL R A MCBRATNEY A B | 2008 | Geoderma2008，146，34： | 1 |
| 8 | Transcriptional regulation of hepatic lipogenesis显示文摘 | WANG Y VISCARRA J KIM S J | 2015 | Nat Rev Mol Cell Biol2015，16，11： | 1 |
| 9 | Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties显示文摘 | Viscarra Rossel R A Walvoort D J J McBratney A B | 2006 | Geoderma2006，131，12： | 1 |
| 10 | Using data mining to model and interpret soil diffuse reflvctance spectra显示文摘 | Viscarra Rossel R A Behrens T | 2010 | Geodcrma2010，158，12： | 1 |
| 11 | Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties 显示文摘 | Viscarra Rossel R A Walvoort D J J McBratney A B | 2006 | Geoderma2006，131，： | 1 |
| 12 | Visible and near infrared spectroscopy in soil science显示文摘 | Stenberg B Viscarra Rossel R A Mouazen A M | 2010 | Advances in Agronomy2010，，107： | 1 |
| 13 | Robust modelling of soil diffuse reflectance spectra by bagging-partial least squares regression显示文摘 | VISCARRA R R A | 2007 | Journal of Near Infrared Spectroscopy2007，15，1： | 1 |
| 14 | Visible, near infrared, mid infrared or combineddiffuse reflectance spectroscopy for simultaneous assessmentof various soil properties显示文摘 | Viscarra Rossel R A Walvoort D J J McBratney A B etal | 2006 | Geoderma2006，131，12： | 1 |
| 15 | Determining the composition of mineral-organic mixes using UV-Vis-NIR diffuse reflectance spectroscopy显示文摘 | Viscarra Rossel R V McGlyn R N McBratney A B | 2006 | Geoderma2006，137，12： | 1 |
| 16 | Determining the composition of mineral-organic mixes using UV–vis–NIR diffuse reflectance spectroscopy显示文摘 | R.A. Viscarra Rossel R.N. McGlynn A.B. McBratney | 2006 | Geoderma2006，，1： | 1 |
| 17 | Visible,near infrared,mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties显示文摘 | VISCARRA ROSSEL RA WALVOORT DJJ MCBRATNEYAB | 2006 | Geoderma2006，131，： | 1 |
| 18 | Visible and Near Infrared Spectroscopy in Soil Science显示文摘 | STENBERG B VISCARRA ROSSEL RA MOUAZEN AM | 2010 | Advances in Agronomy2010，107，： | 1 |
| 19 | Using data mining to model and interpret soil diffuse reflectance spectra显示文摘 | Viscarra Rossel R A Behrens T | 2010 | Geoderma2010，158，12： | 1 |
| 20 | Prediction of soil organic matter using a spatially constrained local partial least squares regression and the Chinese vis-NIR spectral library显示文摘 | SHI Z JI WJ VISCARRA ROSSEL RA | 2015 | European Journal of Soil Science2015，66，： | 1 |
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