Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was eff...Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.展开更多
The objectives of the study were to select suitable wavebands for rice leaf area index （LAI） estimation using the data acquired over a whole growing season, and to test the efficiency of the selected wavebands by co...The objectives of the study were to select suitable wavebands for rice leaf area index （LAI） estimation using the data acquired over a whole growing season, and to test the efficiency of the selected wavebands by comparing them with feature positions of rice canopy spectra. In this study, the field experiment in 2002 growing season was conducted at the experimental farm of Zhejiang University, Hangzhou, China. Measurements of hyperspectral reflectance （350-2500 nm） and corresponding LAI were made for a paddy rice canopy throughout the growing season. And three methods were employed to identify the optimal wavebands for paddy rice LAI estimation： correlation coefficient-based method, vegetation index-based method, and stepwise regression method. This research selected 15 wavebands in the region of 350-2500 nm, which appeared to be the optimal wavebands for the paddy rice LAI estimation. Of the selected wavebands, the most frequently occurring wavebands were centered around 554, 675, 723, and 1633 rim. They were followed by 444, 524, 576, 594, 804, 849, 974, 1074, 1219, 1510, and 2194 rim. Most of them made physical sense and had their counterparts in spectral known feature positions, which indicates the promising potential of the 15 selected wavebands for the retrieval of paddy rice LAI.展开更多
Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojia...Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.展开更多
The level of chemical oxygen demand(COD)is an important index to evaluate whether sewage meets the discharge requirements,so corresponding tests should be carried out before discharge.Fourier transform infrared spectr...The level of chemical oxygen demand(COD)is an important index to evaluate whether sewage meets the discharge requirements,so corresponding tests should be carried out before discharge.Fourier transform infrared spectroscopy(FTIR)and attenuated total reflectance(ATR)can detect COD in sewage effectively,which has advantages over conventional chemical analysis methods.And the selection of characteristic bands was one of the key links in the application of FTIR/ATR spectroscopy.In this work,based on the moving window partial least-squares(MWPLS)regression to select a characteristic wavelength,a method of equivalent wavelength selection was proposed combining with paired t-test equivalent concept.The results showed that the prediction effect of the selected wavelength was very close to that of the MWPLS method,while the number of wavelength points was much smaller.SEPAve,RP,Ave,SEPStd,and RP,Std which characterized the modeling effect were 26.3 mg L^-1,0.969,3.49 mg L^-1,and 0.006,respectively.The validation effect V-SEP and V-RP were 28.64 mg L^-1 and 0.960,respectively.The selected waveband was between 1809 cm^-1 and 1568 cm^-1.The method was of more reference value for the design of FTIR/ATR spectral instrument for COD detection.展开更多
Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture.It helps the farmers in the optimal use of fertilizers.It reduces the cost of food production and also the n...Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture.It helps the farmers in the optimal use of fertilizers.It reduces the cost of food production and also the negative environmentalimpacts on atmosphere and water bodies due to indiscriminate dosageof fertilizers.The traditional chemical-based laboratory soil analysis methodsdo not serve the purpose as they are hardly suitable for site specific soil management.Moreover,the spectral range used in the chemical-based laboratory soil analysismay be of 350-2500 nm,which leads to redundancy and confusion.Developing sensors based on the discovery of spectral wavebands that respondto soil macronutrient concentrations,on the other hand,is an innovative and successfultechnology since the results are dependable and timely.The goal of thisarticle is to use a supervised neuro-fuzzy based dimensionality reduction approachin the sensor development process to determine sensitive wavebands of soilmacronutrients.Accordingly,the spectral signatures of the soil are collected inan outdoor environment and mapped with its macronutrient concentrations.In thisspectral analysis,the spectral reflectance of 424 wavelengths has been obtainedand these wavelengths are evaluated through combined and individual modesas well.Appropriate wavelengths are selected in each case by minimizing the fuzzy reflectance assessment index.The effectiveness of these selected wavelengthsin each mode is validated by modeling the relation between the reduced reflectancespace and each macronutrient concentration using Partial Least Squares Multi Variable Regression(PLS-MVR)method.Set of optimal wavebands areidentified and the results are compared with the existing systems.展开更多
针对2.0~25.0μm波段传输的限制损耗问题,文章采用数值模拟方法研究影响碲基硫系光子晶体光纤(photonic crystal fiber,PCF)限制损耗的主要因素。光纤纤芯和包层材料采用Ge 20 As 20 Se 15 Te 45玻璃,通过改变纤芯直径、空气孔直径和空...针对2.0~25.0μm波段传输的限制损耗问题,文章采用数值模拟方法研究影响碲基硫系光子晶体光纤(photonic crystal fiber,PCF)限制损耗的主要因素。光纤纤芯和包层材料采用Ge 20 As 20 Se 15 Te 45玻璃,通过改变纤芯直径、空气孔直径和空气孔层数等参数进行2.0~25.0μm波段限制损耗的计算,结果表明,影响限制损耗的最大因素是纤芯直径,限制损耗随着纤芯直径和空气孔直径的增大而显著降低,随着空气孔层数的增加而降低;优化设计出一种低限制损耗的PCF,结果表明,当纤芯直径和节距为8.0μm、空气孔直径为7.2μm、包层空气孔层数为4时,该PCF在2.0~25.0μm波长范围的限制损耗低于1.4×10^(-6) dB/m,满足低损耗传输要求。文章研究结果对2.0~25.0μm波段光信号的传输具有一定的意义。展开更多
基金Under the auspices of Fundamental Research Funds for Central Universities,China University of Geosciences(Wuhan)(No.CUGL150417)National Natural Science Foundation of China(No.41274036,41301026)
文摘Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.
基金supported by the National Natural Science Foundation of China (No. 40571115)the Hi-Tech Research and Development Program (863) of China (No. 2006AA120101)the National Basic Research Program (973) of China (No. 2006BAD10A09)
文摘The objectives of the study were to select suitable wavebands for rice leaf area index （LAI） estimation using the data acquired over a whole growing season, and to test the efficiency of the selected wavebands by comparing them with feature positions of rice canopy spectra. In this study, the field experiment in 2002 growing season was conducted at the experimental farm of Zhejiang University, Hangzhou, China. Measurements of hyperspectral reflectance （350-2500 nm） and corresponding LAI were made for a paddy rice canopy throughout the growing season. And three methods were employed to identify the optimal wavebands for paddy rice LAI estimation： correlation coefficient-based method, vegetation index-based method, and stepwise regression method. This research selected 15 wavebands in the region of 350-2500 nm, which appeared to be the optimal wavebands for the paddy rice LAI estimation. Of the selected wavebands, the most frequently occurring wavebands were centered around 554, 675, 723, and 1633 rim. They were followed by 444, 524, 576, 594, 804, 849, 974, 1074, 1219, 1510, and 2194 rim. Most of them made physical sense and had their counterparts in spectral known feature positions, which indicates the promising potential of the 15 selected wavebands for the retrieval of paddy rice LAI.
文摘Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.
基金This work was financially supported by the Natural Science Foundation of Hainan Province(417087)the Key Research and Development Program of Hainan Province(ZDYF2018007)Research Fund for Advanced Talents of Hainan University(No.kyqd1577).
文摘The level of chemical oxygen demand(COD)is an important index to evaluate whether sewage meets the discharge requirements,so corresponding tests should be carried out before discharge.Fourier transform infrared spectroscopy(FTIR)and attenuated total reflectance(ATR)can detect COD in sewage effectively,which has advantages over conventional chemical analysis methods.And the selection of characteristic bands was one of the key links in the application of FTIR/ATR spectroscopy.In this work,based on the moving window partial least-squares(MWPLS)regression to select a characteristic wavelength,a method of equivalent wavelength selection was proposed combining with paired t-test equivalent concept.The results showed that the prediction effect of the selected wavelength was very close to that of the MWPLS method,while the number of wavelength points was much smaller.SEPAve,RP,Ave,SEPStd,and RP,Std which characterized the modeling effect were 26.3 mg L^-1,0.969,3.49 mg L^-1,and 0.006,respectively.The validation effect V-SEP and V-RP were 28.64 mg L^-1 and 0.960,respectively.The selected waveband was between 1809 cm^-1 and 1568 cm^-1.The method was of more reference value for the design of FTIR/ATR spectral instrument for COD detection.
文摘Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture.It helps the farmers in the optimal use of fertilizers.It reduces the cost of food production and also the negative environmentalimpacts on atmosphere and water bodies due to indiscriminate dosageof fertilizers.The traditional chemical-based laboratory soil analysis methodsdo not serve the purpose as they are hardly suitable for site specific soil management.Moreover,the spectral range used in the chemical-based laboratory soil analysismay be of 350-2500 nm,which leads to redundancy and confusion.Developing sensors based on the discovery of spectral wavebands that respondto soil macronutrient concentrations,on the other hand,is an innovative and successfultechnology since the results are dependable and timely.The goal of thisarticle is to use a supervised neuro-fuzzy based dimensionality reduction approachin the sensor development process to determine sensitive wavebands of soilmacronutrients.Accordingly,the spectral signatures of the soil are collected inan outdoor environment and mapped with its macronutrient concentrations.In thisspectral analysis,the spectral reflectance of 424 wavelengths has been obtainedand these wavelengths are evaluated through combined and individual modesas well.Appropriate wavelengths are selected in each case by minimizing the fuzzy reflectance assessment index.The effectiveness of these selected wavelengthsin each mode is validated by modeling the relation between the reduced reflectancespace and each macronutrient concentration using Partial Least Squares Multi Variable Regression(PLS-MVR)method.Set of optimal wavebands areidentified and the results are compared with the existing systems.
文摘针对2.0~25.0μm波段传输的限制损耗问题,文章采用数值模拟方法研究影响碲基硫系光子晶体光纤(photonic crystal fiber,PCF)限制损耗的主要因素。光纤纤芯和包层材料采用Ge 20 As 20 Se 15 Te 45玻璃,通过改变纤芯直径、空气孔直径和空气孔层数等参数进行2.0~25.0μm波段限制损耗的计算,结果表明,影响限制损耗的最大因素是纤芯直径,限制损耗随着纤芯直径和空气孔直径的增大而显著降低,随着空气孔层数的增加而降低;优化设计出一种低限制损耗的PCF,结果表明,当纤芯直径和节距为8.0μm、空气孔直径为7.2μm、包层空气孔层数为4时,该PCF在2.0~25.0μm波长范围的限制损耗低于1.4×10^(-6) dB/m,满足低损耗传输要求。文章研究结果对2.0~25.0μm波段光信号的传输具有一定的意义。
