Spectral index methodology has been widely used in Leaf Area Index(LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect ...Spectral index methodology has been widely used in Leaf Area Index(LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers(SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition(VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index(NDVI), Modified Simple Ratio Indices(MSRI) and Triangle Vegetation Index(TVI), although the coefficient of determination R^2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.展开更多
Based upon Fermi 1FGL and EGRET 3EG samples, a sample including 79 blazars （53 FSRQs, 26 BL Lacs） is presented. It is investigated that the correlations between the ratio of EGRET to Fermi blazars g-ray flux densiti...Based upon Fermi 1FGL and EGRET 3EG samples, a sample including 79 blazars （53 FSRQs, 26 BL Lacs） is presented. It is investigated that the correlations between the ratio of EGRET to Fermi blazars g-ray flux densities and the spectral index differ for EGRET to Fermi blazars for three subclasses of high-frequency peaked BL Lacertae objects-HBL, low-frequency peaked BL Lacertae objects-LBL, and flat spectrum radio quasars-FSRQs. There is a consistent relationship between the ratio of the two γ-ray flux densities and the spectral index difference for the three subclasses. It suggests that the spectrum changed with the source brightness in the gamma-ray band. Both the spectral index difference and the correlation slopes follow a continuous sequence from FSRQs to LBLs to HBLs, which is consistent with the noted blazar sequence.展开更多
Blazars are a special subclass of active galactic nuclei with extreme observation properties. This subclass can be divided into two further subclasses of flat spectrum radio quasars(FSRQs) and BL Lacertae objects(BL L...Blazars are a special subclass of active galactic nuclei with extreme observation properties. This subclass can be divided into two further subclasses of flat spectrum radio quasars(FSRQs) and BL Lacertae objects(BL Lacs) according to their emission line features. To compare the spectral properties of FSRQs and BL Lacs, the 1.4 GHz radio, optical R-band, 1 keV X-ray, and 1 GeVy-ray flux densities for 1108 Fermi blazars are calculated to discuss the properties of the six effective spectral indices of radio to optical(α_(RO)), radio to X-ray(α_(RX)), radio to y ray(α_(Ry)), optical to X-ray(α_(OX)), optical to y ray(α_(Oy)), and X-ray to y ray(α_(Xy)).The main results are as follows: For the averaged effective spectral indices, α_(OX_> α_(Oy)> α_(Xy)> α_(Ry)> α_(RX)> α_(RO) for samples of whole blazars and BL Lacs; α_(Xy)≈α_(Ry)≈α_(RX) for FSRQs and low-frequency-peaked BL Lacs(LBLs); and α_(OX)≈α_(Oy)≈α_(Xy) for high-synchrotron-frequency-peaked BL Lacs(HBLs). The distributions of the effective spectral indices involving optical emission(α_(RO), α_(OX), and α_(Oy)) for LBLs are different from those for FSRQs, but if the effective spectral index does not involve optical emission(α_(RX), α_(Ry), and α_(Xy)), the distributions for LBLs and FSRQs almost come from the same parent population. X-ray emissions from blazars include both synchrotron and inverse Compton (IC) components; the IC component for FSRQs and LBLs accounts for a larger proportion than that for HBLs; and the radiation mechanism for LBLs is similar to that for FSRQs, but the radiation mechanism for HBLs is different from that for both FSRQs and LBLs in X-ray bands. The tendency of α_(Ry) decreasing from LBLs to HBLs suggests that the synchrotron self-Compton model explains the main process for highly energetic y rays in BL Lacs.展开更多
Hyperspectral imaging,with many narrow bands of spectra,is strongly capable to detect or classify objects.It has been become one research hotspot in the field of near-ground remote sensing.However,the higher demands f...Hyperspectral imaging,with many narrow bands of spectra,is strongly capable to detect or classify objects.It has been become one research hotspot in the field of near-ground remote sensing.However,the higher demands for computing and complex operating of instrument are still the bottleneck for hyperspectral imaging technology applied in field.Band selection is a common way to reduce the dimensionality of hyperspectral imaging cube and simplify the design of spectral imaging instrument.In this research,hyperspectral images of blueberry fruit were collected both in the laboratory and in field.A set of spectral bands were selected by analyzing the differences among blueberry fruits at different growth stages and backgrounds.Furthermore,a normalized spectral index was set up using the bands selected to identify the three growth stages of blueberry fruits,aiming to eliminate the impact of background included leaf,branch,soil,illumination variation and so on.Two classifiers of spectral angle mapping(SAM),multinomial logistic regression(MLR)and classification tree were used to verify the results of identification of blueberry fruit.The detection accuracy was 82.1%for SAM classifier using all spectral bands,88.5%for MLR classifier using selected bands and 89.8%for decision tree using the spectral index.The results indicated that the normalization spectral index can both lower the complexity of computing and reduce the impact of noisy background in field.展开更多
Yellow rust(Puccinia striiformis f.sp.Tritici)is a frequently occurring fungal disease of winter wheat(Triticum aestivum L.).During yellow rust infestation,fungal spores appear on the surface of the leaves as yellow a...Yellow rust(Puccinia striiformis f.sp.Tritici)is a frequently occurring fungal disease of winter wheat(Triticum aestivum L.).During yellow rust infestation,fungal spores appear on the surface of the leaves as yellow and narrow stripes parallel to the leaf veins.We analyzed the effect of the fungal spores on the spectra of the diseased leaves to find a band sensitive to yellow rust and established a new vegetation index called the yellow rust spore index(YRSI).The estimation accuracy and stability were evaluated using two years of leaf spectral data,and the results were compared with eight indices commonly used for yellow rust detection.The results showed that the use of the YRSI ranked first for estimating the disease ratio for the 2017 spectral data(R^(2)=0.710,RMSE=0.097)and outperformed the published indices(R^(2)=0.587,RMSE=0.120)for the validation using the 2002 spectral data.The random forest(RF),k-nearest neighbor(KNN),and support vector machine(SVM)algorithms were used to test the discrimination ability of the YRSI and the eight commonly used indices using a mixed dataset of yellow-rust-infested,healthy,and aphid–infested wheat spectral data.The YRSI provided the best performance.展开更多
Accurate assessment of canopy carotenoid content(CC_(x+c)C)in crops is central to monitor physiological conditions in plants and vegetation stress,and consequently supporting agronomic decisions.However,due to the ove...Accurate assessment of canopy carotenoid content(CC_(x+c)C)in crops is central to monitor physiological conditions in plants and vegetation stress,and consequently supporting agronomic decisions.However,due to the overlap of absorption peaks of carotenoid(C_(x+c))and chlorophyll(C_(a+b)),accurate estimation of carotenoid using reflectance where carotenoid absorb is challenging.The objective of present study was to assess CC_(x+c)C in winter wheat(Triticum aestivum L.)with ground-and aircraft-based hyperspectral measurements in the visible and near-infrared spectrum.In-situ hyperspectral reflectance were measured and airborne hyperspectral data were acquired during major growth stages of winter wheat in five consecutive field experiments.At the canopy level,a remarkable linear relationship(R^(2)=0.95,p<0.001)existed between C_(x+c) and Ca+b,and correlation between CC_(x+c)C and wavelengths within 400 to 1000 nm range indicated that CC_(x+c)C could be estimated using reflectance ranging from visible to near-infrared wavebands.Results of Cx+c assessment based on chlorophyll and carotenoid indices showed that red edge chlorophyll index(CI red edge)performed with the highest accuracy(R^(2)=0.77,RMSE=22.27μg/cm^(2),MAE=4.97μg/cm^(2)).Applying partial least square regression(PLSR)in CC_(x+c)C retrieval emphasized the significance of reflectance within 700 to 750 nm range in CC_(x+c)C assessment.Based on CI red edge index,use of airborne hyperspectral imagery achieved satisfactory results in mapping the spatial distribution of CC_(x+c)C.This study demonstrates that it is feasible to accurately assess CC_(x+c)C in winter wheat with red edge chlorophyll index provided that C_(x+c) correlated well with C_(a+b) at the canopy scale.it is therefore a promising method for CC_(x+c)C retrieval at regional scale from aerial hyperspectral imagery.展开更多
Spectral reflectance in the near-infrared （NIR） shoulder （750-900 nm） region is affected by internal leaf structure, but it has rarely been investigated. In this study, a dehydration treatment and three paraquat h...Spectral reflectance in the near-infrared （NIR） shoulder （750-900 nm） region is affected by internal leaf structure, but it has rarely been investigated. In this study, a dehydration treatment and three paraquat herbicide applications were conducted to explore how spectral reflectance and shape in the NIR shoulder region responded to various stresses. A new spectral ratio index in the NIR shoulder region （NSRI）, defined by a simple ratio of reflectance at 890 nm to reflectance at 780 nm, was proposed for assessing leaf structure deterioration. Firstly, a wavelength-independent increase in spectral reflectance in the NIR shoulder region was observed from the mature leaves with slight dehydration. An increase in spectral slope in the NIR shoulder would be expected only when water stress developed sufficiently to cause severe leaf dehydration resulting in an alteration in cell structure. Secondly, the alteration of leaf cell structure caused by Paraquat herbicide applications resulted in a wavelength-dependent variation of spectral reflectance in the NIR shoulder region. The NSRI in the NIR shoulder region increased significantly under an herbicide application. Although the dehydration process also occurred with the herbicide injury, NSRI is more sensitive to herbicide injury than the water-related indices （water index and normalized difference water index） and normalized difference vegetation index. Finally, the sensitivity of NSRI to stripe rust in winter wheat was examined, yielding a determination coefficient of 0.61, which is more significant than normalized difference vegetation index （NDVI）, water index （WI） and normalized difference water index （NDWI）, with a determination coefficient of 0.45, 0.36 and 0.13, respectively. In this study, all experimental results demonstrated that NSRI will increase with internal leaf structure deterioration, and it is also a sensitive spectral index for herbicide injury or stripe rust in winter wheat.展开更多
Objective: To explore the correlation between the spectral computed tomography(CT) imaging parameters and the Ki-67 labeling index in lung adenocarcinoma.Methods: Spectral CT imaging parameters [iodine concentrations ...Objective: To explore the correlation between the spectral computed tomography(CT) imaging parameters and the Ki-67 labeling index in lung adenocarcinoma.Methods: Spectral CT imaging parameters [iodine concentrations of lesions(ICLs) in the arterial phase(ICLa)and venous phase(ICLv), normalized IC in the aorta(NICa/NICv), slope of the spectral HU curve(λHUa/λHUv)and monochromatic CT number enhancement on 40 keV and 70 keV images(CT40 keVa/v, CT70keVa/v)] in 34 lung adenocarcinomas were analyzed, and common molecular markers, including the Ki-67 labeling index, were detected with immunohistochemistry. Different Ki-67 labeling indexes were measured and grouped into four grades according to the number of positive-stained cells(grade 0, ≤1%;1%<grade 1≤10%;10%<grade 2≤30%;and grade 3, >30%). One-way analysis of variance(ANOVA) was used to compare the four different grades, and the Bonferroni method was used to correct the P value for multiple comparisons. A Spearman correlation analysis was performed to further research a quantitative correlation between the Ki-67 labeling index and spectral CT imaging parameters.Results: CT40keVa, CT40 keVv, CT70keVa and CT70keVv increased as the grade increased, and CT70keVa and CT70keVv were statistically significant(P<0.05). These four parameters and the Ki-67 labeling index showed a moderate positive correlation with lung adenocarcinoma nodules. ICL, NIC and λHU in the arterial and venous phases were not significantly different among the four grades.Conclusions: The spectral CT imaging parameters CT40keVa, CT40keVv, CT70keVa and CT70keVv gradually increased with Ki-67 expression and showed a moderate positive correlation with lung adenocarcinomas.Therefore, spectral CT imaging parameter-enhanced monochromatic CT numbers at 70 keV may indicate the extent of proliferation of lung adenocarcinomas.展开更多
In this study, strong ground motion record （SGMR） selection based on Eta （~/） as a spectral shape indicator has been investigated as applied to steel braced flame structures. A probabilistic seismic hazard disaggr...In this study, strong ground motion record （SGMR） selection based on Eta （~/） as a spectral shape indicator has been investigated as applied to steel braced flame structures. A probabilistic seismic hazard disaggregation analysis for the definition of the target Epsilon （ε） and the target Eta （η） values at different hazard levels is presented, taking into account appropriately selected SGMR＇s. Fragility curves are developed for different limit states corresponding to three representative models of typical steel braced frames having significant irregularities in plan, by means of a weighted damage index. The results show that spectral shape indicators have an important effect on the predicted median structural capacities, and also that the parameter r/is a more robust predictor of damage than searching for records with appropriate c values.展开更多
【目的】叶面积指数(leaf area index,LAI)是表征作物长势、光合、蒸腾的重要指标。论文旨在研究不同生育期、多生育期无人机多光谱数据棉花LAI估测模型,明确不同生育期间棉花LAI估测模型变化规律,为实时掌握棉花长势并因地制宜进行田...【目的】叶面积指数(leaf area index,LAI)是表征作物长势、光合、蒸腾的重要指标。论文旨在研究不同生育期、多生育期无人机多光谱数据棉花LAI估测模型,明确不同生育期间棉花LAI估测模型变化规律,为实时掌握棉花长势并因地制宜进行田间科学管理提供依据。【方法】利用大疆精灵4多光谱无人机获取棉花现蕾期、初花期、结铃期、吐絮期多光谱图像和RGB图像。选用归一化差植被指数(NDVI)、绿度归一化差植被指数(GNDVI)、归一化差红边指数(NDRE)、叶片叶绿素指数(LCI)、优化的土壤调节植被指数(OSAVI)5种多光谱指数和修正红绿植被指数(MGRVI)、红绿植被指数(GRVI)、绿叶指数(GLA)、超红指数(EXR)、大气阻抗植被指数(VARI)5种颜色指数分别建立棉花各生育期及棉花生长多生育期数据集合,结合打孔法获取地面LAI实测数据,使用机器学习算法中偏最小二乘(PLSR)、岭回归(RR)、随机森林(RF)、支持向量机(SVM)、神经网络(BP)构建棉花LAI预测模型。【结果】覆膜棉花LAI随着生育期的变化呈现先增长后下降的趋势,现蕾期、初花期、结铃期内侧棉花叶面积指数均值均显著大于外侧(P<0.05);选择的指数在各时期彼此间均呈显著相关(P<0.05),总体而言,多光谱指数与颜色指数间的相关性随着生育期的进行而呈现下降趋势,选择的指数在各时期均与棉花LAI相关性显著(P<0.05),多光谱指数相关系数介于0.35—0.85,颜色指数相关系数介于0.49—0.71,相关系数绝对值较大的指数多为多光谱指数,颜色指数与棉花LAI的相关系数绝对值较小;估测模型性能结果显示棉花各生育期模型中多光谱指数优于颜色指数,且各指数模型预测性能随着生育期的变化呈现一定规律性,NDVI是预测棉花LAI的最优指数。从模型结果上看,RF模型和BP模型在各生育期下获得了较高的估计精度。初花期LAI反演模型精度最高,最优模型验证集R2为0.809,MAE为0.288,NRMSE为0.120。多生育期最优模型验证集R2为0.386,MAE为0.700,NRMSE为0.198。【结论】棉花内外侧LAI在现蕾期、初花期、结铃期存在显著差异。在各生育期中,RF和BP模型是预测棉花LAI较优模型。NDVI在各指数中表现最好,是预测棉花LAI的最优指数。多生育期模型效果较单生育期明显下降,最优指数为GNDVI,最优模型为BP。本研究中预测棉花LAI的最优窗口期是初花期。研究结果可为无人机遥感监测棉花LAI提供理论依据和技术支持。展开更多
基金National Natural Science Foundation of China(No.41401002)Jilin Province Science Foundation for Youths(No.20160520077JH)
文摘Spectral index methodology has been widely used in Leaf Area Index(LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers(SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition(VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index(NDVI), Modified Simple Ratio Indices(MSRI) and Triangle Vegetation Index(TVI), although the coefficient of determination R^2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.
基金supported by the National Natural Science Foundation of China(Grant Nos.10633010 and 11173009)the National Basic Research Program of China(Grant No.2007CB 815405)+5 种基金the Bureau of Education of Guangzhou Municipality(Grant No.11 Sui-Jiao-Ke[2009])Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (GDUPS)(2009)Yangcheng Scholar Funded Scheme(Grant No. 10A027S)Hunan Provincial Natural Science Foundation(Grant No. 10JJ3020)Fund of the 11th Five-year Plan for Key Construction Academic Subject(Optics) of Hunan Province,Research Funding from Hunan University of Arts and Science(Grant No.JJZD201101)the Guangzhou Education Bureau and Guangzhou Science and Technology Bureau
文摘Based upon Fermi 1FGL and EGRET 3EG samples, a sample including 79 blazars （53 FSRQs, 26 BL Lacs） is presented. It is investigated that the correlations between the ratio of EGRET to Fermi blazars g-ray flux densities and the spectral index differ for EGRET to Fermi blazars for three subclasses of high-frequency peaked BL Lacertae objects-HBL, low-frequency peaked BL Lacertae objects-LBL, and flat spectrum radio quasars-FSRQs. There is a consistent relationship between the ratio of the two γ-ray flux densities and the spectral index difference for the three subclasses. It suggests that the spectrum changed with the source brightness in the gamma-ray band. Both the spectral index difference and the correlation slopes follow a continuous sequence from FSRQs to LBLs to HBLs, which is consistent with the noted blazar sequence.
基金supported by the National Natural Science Foundation of China(Grant Nos.U1431112,U1531245,11733001,and 11403006)the Innovation Foundation of Guangzhou University(IFGZ)+3 种基金the Guangdong Innovation Team(Grant No.2014KCXTD014)Astrophysics Key Subjects of Guangdong Province and Guangzhou Citythe Hunan Provincial Natural Science Foundation of China(Grant No.2015JJ2104)the Research Foundation of the Education Bureau of Hunan Province,China(Grant No.16C1081)
文摘Blazars are a special subclass of active galactic nuclei with extreme observation properties. This subclass can be divided into two further subclasses of flat spectrum radio quasars(FSRQs) and BL Lacertae objects(BL Lacs) according to their emission line features. To compare the spectral properties of FSRQs and BL Lacs, the 1.4 GHz radio, optical R-band, 1 keV X-ray, and 1 GeVy-ray flux densities for 1108 Fermi blazars are calculated to discuss the properties of the six effective spectral indices of radio to optical(α_(RO)), radio to X-ray(α_(RX)), radio to y ray(α_(Ry)), optical to X-ray(α_(OX)), optical to y ray(α_(Oy)), and X-ray to y ray(α_(Xy)).The main results are as follows: For the averaged effective spectral indices, α_(OX_> α_(Oy)> α_(Xy)> α_(Ry)> α_(RX)> α_(RO) for samples of whole blazars and BL Lacs; α_(Xy)≈α_(Ry)≈α_(RX) for FSRQs and low-frequency-peaked BL Lacs(LBLs); and α_(OX)≈α_(Oy)≈α_(Xy) for high-synchrotron-frequency-peaked BL Lacs(HBLs). The distributions of the effective spectral indices involving optical emission(α_(RO), α_(OX), and α_(Oy)) for LBLs are different from those for FSRQs, but if the effective spectral index does not involve optical emission(α_(RX), α_(Ry), and α_(Xy)), the distributions for LBLs and FSRQs almost come from the same parent population. X-ray emissions from blazars include both synchrotron and inverse Compton (IC) components; the IC component for FSRQs and LBLs accounts for a larger proportion than that for HBLs; and the radiation mechanism for LBLs is similar to that for FSRQs, but the radiation mechanism for HBLs is different from that for both FSRQs and LBLs in X-ray bands. The tendency of α_(Ry) decreasing from LBLs to HBLs suggests that the synchrotron self-Compton model explains the main process for highly energetic y rays in BL Lacs.
基金The work was financially supported by the National Key Research and Development Program of China Sub-project(No.2016YFD0700103)the National Natural Science Foundation of China(No.61805073)+1 种基金Innovation Scientists and Technicians Talent Projects of Henan Provincial Department of Education(No.19HASTIT021)Henan provincial science and technology project(No.182102110201&No.192102110204).
文摘Hyperspectral imaging,with many narrow bands of spectra,is strongly capable to detect or classify objects.It has been become one research hotspot in the field of near-ground remote sensing.However,the higher demands for computing and complex operating of instrument are still the bottleneck for hyperspectral imaging technology applied in field.Band selection is a common way to reduce the dimensionality of hyperspectral imaging cube and simplify the design of spectral imaging instrument.In this research,hyperspectral images of blueberry fruit were collected both in the laboratory and in field.A set of spectral bands were selected by analyzing the differences among blueberry fruits at different growth stages and backgrounds.Furthermore,a normalized spectral index was set up using the bands selected to identify the three growth stages of blueberry fruits,aiming to eliminate the impact of background included leaf,branch,soil,illumination variation and so on.Two classifiers of spectral angle mapping(SAM),multinomial logistic regression(MLR)and classification tree were used to verify the results of identification of blueberry fruit.The detection accuracy was 82.1%for SAM classifier using all spectral bands,88.5%for MLR classifier using selected bands and 89.8%for decision tree using the spectral index.The results indicated that the normalization spectral index can both lower the complexity of computing and reduce the impact of noisy background in field.
基金The research was funded by the Chinese Academy of Sciences[183611KYSB20200080]the National Natural Science Foundation of China[41871339,42071320,42071423,41801338]+2 种基金the National Special Support Program for High-level Personnel Recruitment(Wenjiang Huang)the Youth Innovation Promotion Association CAS(Huichun Ye)the Future Star Talent Program of Aerospace Information Research Institute,CAS(Huichun Ye).
文摘Yellow rust(Puccinia striiformis f.sp.Tritici)is a frequently occurring fungal disease of winter wheat(Triticum aestivum L.).During yellow rust infestation,fungal spores appear on the surface of the leaves as yellow and narrow stripes parallel to the leaf veins.We analyzed the effect of the fungal spores on the spectra of the diseased leaves to find a band sensitive to yellow rust and established a new vegetation index called the yellow rust spore index(YRSI).The estimation accuracy and stability were evaluated using two years of leaf spectral data,and the results were compared with eight indices commonly used for yellow rust detection.The results showed that the use of the YRSI ranked first for estimating the disease ratio for the 2017 spectral data(R^(2)=0.710,RMSE=0.097)and outperformed the published indices(R^(2)=0.587,RMSE=0.120)for the validation using the 2002 spectral data.The random forest(RF),k-nearest neighbor(KNN),and support vector machine(SVM)algorithms were used to test the discrimination ability of the YRSI and the eight commonly used indices using a mixed dataset of yellow-rust-infested,healthy,and aphid–infested wheat spectral data.The YRSI provided the best performance.
基金supported by the Fundamental Research Funds for the Provincial Universities of Zhejiang(Project No.GK229909299001-302)the National Natural Science Foundation of China(Project No.41901268)+1 种基金the Natural Science Foundation of Zhejiang Province(Project No.LQ19D010009)the Provincial Education Department General Scientific Research Items(Project No.Y202249845).
文摘Accurate assessment of canopy carotenoid content(CC_(x+c)C)in crops is central to monitor physiological conditions in plants and vegetation stress,and consequently supporting agronomic decisions.However,due to the overlap of absorption peaks of carotenoid(C_(x+c))and chlorophyll(C_(a+b)),accurate estimation of carotenoid using reflectance where carotenoid absorb is challenging.The objective of present study was to assess CC_(x+c)C in winter wheat(Triticum aestivum L.)with ground-and aircraft-based hyperspectral measurements in the visible and near-infrared spectrum.In-situ hyperspectral reflectance were measured and airborne hyperspectral data were acquired during major growth stages of winter wheat in five consecutive field experiments.At the canopy level,a remarkable linear relationship(R^(2)=0.95,p<0.001)existed between C_(x+c) and Ca+b,and correlation between CC_(x+c)C and wavelengths within 400 to 1000 nm range indicated that CC_(x+c)C could be estimated using reflectance ranging from visible to near-infrared wavebands.Results of Cx+c assessment based on chlorophyll and carotenoid indices showed that red edge chlorophyll index(CI red edge)performed with the highest accuracy(R^(2)=0.77,RMSE=22.27μg/cm^(2),MAE=4.97μg/cm^(2)).Applying partial least square regression(PLSR)in CC_(x+c)C retrieval emphasized the significance of reflectance within 700 to 750 nm range in CC_(x+c)C assessment.Based on CI red edge index,use of airborne hyperspectral imagery achieved satisfactory results in mapping the spatial distribution of CC_(x+c)C.This study demonstrates that it is feasible to accurately assess CC_(x+c)C in winter wheat with red edge chlorophyll index provided that C_(x+c) correlated well with C_(a+b) at the canopy scale.it is therefore a promising method for CC_(x+c)C retrieval at regional scale from aerial hyperspectral imagery.
基金the National High-Tech R&D Program of China(2012AA12A30701)the National Natural Science Foundation of China(91125003,41222008)
文摘Spectral reflectance in the near-infrared （NIR） shoulder （750-900 nm） region is affected by internal leaf structure, but it has rarely been investigated. In this study, a dehydration treatment and three paraquat herbicide applications were conducted to explore how spectral reflectance and shape in the NIR shoulder region responded to various stresses. A new spectral ratio index in the NIR shoulder region （NSRI）, defined by a simple ratio of reflectance at 890 nm to reflectance at 780 nm, was proposed for assessing leaf structure deterioration. Firstly, a wavelength-independent increase in spectral reflectance in the NIR shoulder region was observed from the mature leaves with slight dehydration. An increase in spectral slope in the NIR shoulder would be expected only when water stress developed sufficiently to cause severe leaf dehydration resulting in an alteration in cell structure. Secondly, the alteration of leaf cell structure caused by Paraquat herbicide applications resulted in a wavelength-dependent variation of spectral reflectance in the NIR shoulder region. The NSRI in the NIR shoulder region increased significantly under an herbicide application. Although the dehydration process also occurred with the herbicide injury, NSRI is more sensitive to herbicide injury than the water-related indices （water index and normalized difference water index） and normalized difference vegetation index. Finally, the sensitivity of NSRI to stripe rust in winter wheat was examined, yielding a determination coefficient of 0.61, which is more significant than normalized difference vegetation index （NDVI）, water index （WI） and normalized difference water index （NDWI）, with a determination coefficient of 0.45, 0.36 and 0.13, respectively. In this study, all experimental results demonstrated that NSRI will increase with internal leaf structure deterioration, and it is also a sensitive spectral index for herbicide injury or stripe rust in winter wheat.
基金supported by National Natural Science Foundation of China (No. 91959116)Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support (No. ZYLX 201803)+1 种基金“Beijing Hospitals Authority” Ascent Plan (No. DFL20191103)National Key R&D Program of China (No. 2017YFC1309101, 2017YFC1309104).
文摘Objective: To explore the correlation between the spectral computed tomography(CT) imaging parameters and the Ki-67 labeling index in lung adenocarcinoma.Methods: Spectral CT imaging parameters [iodine concentrations of lesions(ICLs) in the arterial phase(ICLa)and venous phase(ICLv), normalized IC in the aorta(NICa/NICv), slope of the spectral HU curve(λHUa/λHUv)and monochromatic CT number enhancement on 40 keV and 70 keV images(CT40 keVa/v, CT70keVa/v)] in 34 lung adenocarcinomas were analyzed, and common molecular markers, including the Ki-67 labeling index, were detected with immunohistochemistry. Different Ki-67 labeling indexes were measured and grouped into four grades according to the number of positive-stained cells(grade 0, ≤1%;1%<grade 1≤10%;10%<grade 2≤30%;and grade 3, >30%). One-way analysis of variance(ANOVA) was used to compare the four different grades, and the Bonferroni method was used to correct the P value for multiple comparisons. A Spearman correlation analysis was performed to further research a quantitative correlation between the Ki-67 labeling index and spectral CT imaging parameters.Results: CT40keVa, CT40 keVv, CT70keVa and CT70keVv increased as the grade increased, and CT70keVa and CT70keVv were statistically significant(P<0.05). These four parameters and the Ki-67 labeling index showed a moderate positive correlation with lung adenocarcinoma nodules. ICL, NIC and λHU in the arterial and venous phases were not significantly different among the four grades.Conclusions: The spectral CT imaging parameters CT40keVa, CT40keVv, CT70keVa and CT70keVv gradually increased with Ki-67 expression and showed a moderate positive correlation with lung adenocarcinomas.Therefore, spectral CT imaging parameter-enhanced monochromatic CT numbers at 70 keV may indicate the extent of proliferation of lung adenocarcinomas.
文摘In this study, strong ground motion record （SGMR） selection based on Eta （~/） as a spectral shape indicator has been investigated as applied to steel braced flame structures. A probabilistic seismic hazard disaggregation analysis for the definition of the target Epsilon （ε） and the target Eta （η） values at different hazard levels is presented, taking into account appropriately selected SGMR＇s. Fragility curves are developed for different limit states corresponding to three representative models of typical steel braced frames having significant irregularities in plan, by means of a weighted damage index. The results show that spectral shape indicators have an important effect on the predicted median structural capacities, and also that the parameter r/is a more robust predictor of damage than searching for records with appropriate c values.
文摘【目的】叶面积指数(leaf area index,LAI)是表征作物长势、光合、蒸腾的重要指标。论文旨在研究不同生育期、多生育期无人机多光谱数据棉花LAI估测模型,明确不同生育期间棉花LAI估测模型变化规律,为实时掌握棉花长势并因地制宜进行田间科学管理提供依据。【方法】利用大疆精灵4多光谱无人机获取棉花现蕾期、初花期、结铃期、吐絮期多光谱图像和RGB图像。选用归一化差植被指数(NDVI)、绿度归一化差植被指数(GNDVI)、归一化差红边指数(NDRE)、叶片叶绿素指数(LCI)、优化的土壤调节植被指数(OSAVI)5种多光谱指数和修正红绿植被指数(MGRVI)、红绿植被指数(GRVI)、绿叶指数(GLA)、超红指数(EXR)、大气阻抗植被指数(VARI)5种颜色指数分别建立棉花各生育期及棉花生长多生育期数据集合,结合打孔法获取地面LAI实测数据,使用机器学习算法中偏最小二乘(PLSR)、岭回归(RR)、随机森林(RF)、支持向量机(SVM)、神经网络(BP)构建棉花LAI预测模型。【结果】覆膜棉花LAI随着生育期的变化呈现先增长后下降的趋势,现蕾期、初花期、结铃期内侧棉花叶面积指数均值均显著大于外侧(P<0.05);选择的指数在各时期彼此间均呈显著相关(P<0.05),总体而言,多光谱指数与颜色指数间的相关性随着生育期的进行而呈现下降趋势,选择的指数在各时期均与棉花LAI相关性显著(P<0.05),多光谱指数相关系数介于0.35—0.85,颜色指数相关系数介于0.49—0.71,相关系数绝对值较大的指数多为多光谱指数,颜色指数与棉花LAI的相关系数绝对值较小;估测模型性能结果显示棉花各生育期模型中多光谱指数优于颜色指数,且各指数模型预测性能随着生育期的变化呈现一定规律性,NDVI是预测棉花LAI的最优指数。从模型结果上看,RF模型和BP模型在各生育期下获得了较高的估计精度。初花期LAI反演模型精度最高,最优模型验证集R2为0.809,MAE为0.288,NRMSE为0.120。多生育期最优模型验证集R2为0.386,MAE为0.700,NRMSE为0.198。【结论】棉花内外侧LAI在现蕾期、初花期、结铃期存在显著差异。在各生育期中,RF和BP模型是预测棉花LAI较优模型。NDVI在各指数中表现最好,是预测棉花LAI的最优指数。多生育期模型效果较单生育期明显下降,最优指数为GNDVI,最优模型为BP。本研究中预测棉花LAI的最优窗口期是初花期。研究结果可为无人机遥感监测棉花LAI提供理论依据和技术支持。
