The Experts below are selected from a list of 26433 Experts worldwide ranked by ideXlab platform
Tiancai Guo - One of the best experts on this subject based on the ideXlab platform.
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using multi angle hyperspectral data to monitor canopy leaf nitrogen content of wheat
Precision Agriculture, 2016Co-Authors: Xiao Song, Wei Feng, Yonghua Wang, Zhijie Wang, Craig A Coburn, Tiancai GuoAbstract:Nitrogen (N) content is an important factor that can affect wheat production. The non-destructive testing of wheat canopy leaf N content through multi-angle hyperspectral remote sensing is of great importance for wheat production and management. Based on a 2-year experiment for winter wheat in Lethbridge (Canada), Zhengzhou (China), and Kaifeng (China) growing under different cultivation practices, the authors studied the relationships between N content and wheat canopy spectral data in solar Principal Plane (SPP) and perpendicular Plane (PP) at different observation angles. Modeling was conducted according to the spectrum index with the highest correlation coefficient and the corresponding observation angle. The results showed that correlation coefficient between the spectral index and canopy leaf N content at each observation angle of the SPP was significantly higher than that of the PP. Significant differences in the correlation coefficient were also observed at different observation angles of the same observation Plane, and the correlation coefficients of angles of −30° and −40° were higher than others. A model fitted by a power function by using mND705 as independent variable at an angle of −40° in the SPP showed the highest accuracy.
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improved remote sensing of leaf nitrogen concentration in winter wheat using multi angular hyperspectral data
Remote Sensing of Environment, 2016Co-Authors: Xiao Song, Wei Feng, Binbin Guo, Yuanshuai Zhang, Yonghua Wang, Chenyang Wang, Tiancai GuoAbstract:Abstract Real-time, nondestructive monitoring of crop nitrogen (N) status is important for precise N management in winter wheat production. Nadir viewing passive multispectral sensors have limited utility for measuring the N status of winter wheat in middle and bottom layers, and multi-angular remote sensors may instead improve detection of whole canopy physiological and biochemical parameters. Our objective was to improve the predictive accuracy and angular stability of leaf nitrogen concentration (LNC) measurement by constructing a novel Angular Insensitivity Vegetation Index (AIVI). We quantified the relationship between LNC and ground-based multi-angular hyperspectral reflectance in winter wheat ( Triticum aestivum L.) across different growth stages, plant types, N rates, planting density, ecological sites and years. The optimum vegetation indices (VIs) obtained from 17 traditional indices reported in the literature were tested for their stability in estimating LNC at 13 view zenith angles (VZAs) in the solar Principal Plane (SPP). Overall the back-scatter direction gave improved index performance, relative to the nadir and forward-scattering direction. Red-edge VIs (e.g., mND705, GND [750,550], NDRE, RI-1dB) were highly correlated with LNC. However, the relationships strongly depended on experimental conditions, and these VIs tended to saturate at the highest LNC (4.5%). To further overcome the influence of different experimental conditions and VZAs on VIs, we developed a novel index, Angular Insensitivity Vegetation Index (AIVI), based on red-edge, blue and green bands. Our new model showed the highest association with LNC ( R 2 = 0.73–0.87) compared to traditional VIs. Investigating AIVI predictive accuracy in measuring LNC across view zenith angles (VZAs) revealed that performance was the highest at − 20° and was relatively homogenous between − 10° and − 40°. This provided a united, predictive model across this wide-angle range, which enhances the possibility of N monitoring by using portable monitors. Testing of the models with independent data gave R 2 of 0.84 at − 20°, and 0.83 across the range of − 10° to − 40°, respectively. These results suggest that the novel AIVI is more effective for monitoring LNC than previously reported VIs for predicting accuracy, monitoring model stability and view angle independency. More generally, our model indicates the importance of accounting for angular effects when analyzing VIs under different experimental conditions.
Xiao Song - One of the best experts on this subject based on the ideXlab platform.
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using multi angle hyperspectral data to monitor canopy leaf nitrogen content of wheat
Precision Agriculture, 2016Co-Authors: Xiao Song, Wei Feng, Yonghua Wang, Zhijie Wang, Craig A Coburn, Tiancai GuoAbstract:Nitrogen (N) content is an important factor that can affect wheat production. The non-destructive testing of wheat canopy leaf N content through multi-angle hyperspectral remote sensing is of great importance for wheat production and management. Based on a 2-year experiment for winter wheat in Lethbridge (Canada), Zhengzhou (China), and Kaifeng (China) growing under different cultivation practices, the authors studied the relationships between N content and wheat canopy spectral data in solar Principal Plane (SPP) and perpendicular Plane (PP) at different observation angles. Modeling was conducted according to the spectrum index with the highest correlation coefficient and the corresponding observation angle. The results showed that correlation coefficient between the spectral index and canopy leaf N content at each observation angle of the SPP was significantly higher than that of the PP. Significant differences in the correlation coefficient were also observed at different observation angles of the same observation Plane, and the correlation coefficients of angles of −30° and −40° were higher than others. A model fitted by a power function by using mND705 as independent variable at an angle of −40° in the SPP showed the highest accuracy.
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improved remote sensing of leaf nitrogen concentration in winter wheat using multi angular hyperspectral data
Remote Sensing of Environment, 2016Co-Authors: Xiao Song, Wei Feng, Binbin Guo, Yuanshuai Zhang, Yonghua Wang, Chenyang Wang, Tiancai GuoAbstract:Abstract Real-time, nondestructive monitoring of crop nitrogen (N) status is important for precise N management in winter wheat production. Nadir viewing passive multispectral sensors have limited utility for measuring the N status of winter wheat in middle and bottom layers, and multi-angular remote sensors may instead improve detection of whole canopy physiological and biochemical parameters. Our objective was to improve the predictive accuracy and angular stability of leaf nitrogen concentration (LNC) measurement by constructing a novel Angular Insensitivity Vegetation Index (AIVI). We quantified the relationship between LNC and ground-based multi-angular hyperspectral reflectance in winter wheat ( Triticum aestivum L.) across different growth stages, plant types, N rates, planting density, ecological sites and years. The optimum vegetation indices (VIs) obtained from 17 traditional indices reported in the literature were tested for their stability in estimating LNC at 13 view zenith angles (VZAs) in the solar Principal Plane (SPP). Overall the back-scatter direction gave improved index performance, relative to the nadir and forward-scattering direction. Red-edge VIs (e.g., mND705, GND [750,550], NDRE, RI-1dB) were highly correlated with LNC. However, the relationships strongly depended on experimental conditions, and these VIs tended to saturate at the highest LNC (4.5%). To further overcome the influence of different experimental conditions and VZAs on VIs, we developed a novel index, Angular Insensitivity Vegetation Index (AIVI), based on red-edge, blue and green bands. Our new model showed the highest association with LNC ( R 2 = 0.73–0.87) compared to traditional VIs. Investigating AIVI predictive accuracy in measuring LNC across view zenith angles (VZAs) revealed that performance was the highest at − 20° and was relatively homogenous between − 10° and − 40°. This provided a united, predictive model across this wide-angle range, which enhances the possibility of N monitoring by using portable monitors. Testing of the models with independent data gave R 2 of 0.84 at − 20°, and 0.83 across the range of − 10° to − 40°, respectively. These results suggest that the novel AIVI is more effective for monitoring LNC than previously reported VIs for predicting accuracy, monitoring model stability and view angle independency. More generally, our model indicates the importance of accounting for angular effects when analyzing VIs under different experimental conditions.
R J Marhefka - One of the best experts on this subject based on the ideXlab platform.
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a caustic corrected utd solution for the fields radiated by a source on a flat plate with a curved edge
IEEE Transactions on Antennas and Propagation, 1997Co-Authors: J H Meloling, R J MarhefkaAbstract:Corrections to the uniform geometrical theory of diffraction (UTD) that account for the caustics caused by the coalescence of the diffraction points on a curved edge are derived. This creates a new curvature dependent diffraction coefficient that has not been previously accounted for in the UTD. The far-zone radiation by a short monopole mounted on an elliptic disk is analyzed using this caustic corrected UTD solution. Theoretical results are verified in the Principal Plane by comparison with a method of moments solution. The resulting solution for the radiated field is accurate and provides useful insight into the scattering phenomena. This insight is necessary in order to obtain more general solutions.
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a caustic corrected utd solution for a short monopole near a curved edge on a flat plate
IEEE Antennas and Propagation Society International Symposium, 1994Co-Authors: J H Meloling, R J MarhefkaAbstract:Corrections to the uniform geometrical theory of diffraction (UTD) that account for the caustics caused by the coalescence of the diffraction points are derived. This creates a new curvature dependent diffraction coefficient that has not been previously accounted for in the UTD. The far-zone radiation by a short monopole mounted on an elliptic disk is analyzed using this caustic corrected UTD solution. Theoretical results are verified in the Principal Plane by comparison with a method of moments solution. The resulting solution for the radiated field is accurate and fast to compute. >
L Aladosarboledas - One of the best experts on this subject based on the ideXlab platform.
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analysis of the columnar radiative properties retrieved during african desert dust events over granada 2005 2010 using Principal Plane sky radiances and spheroids retrieval procedure
Atmospheric Research, 2012Co-Authors: A Valenzuela, F J Olmo, A Quirantes, H Lyamani, M Anton, L AladosarboledasAbstract:Abstract The southern Iberian Peninsula is an important area for studying the columnar radiative properties of African desert dust air masses reaching Europe. The Aerosol Optical Depth (AOD) and Angstrom coefficient, α (440–1020 nm), have been retrieved during the dust events reached at surface from 2005 to 2010 at Granada (37.18°N, 3.58°W, 680 m a.m.s.l), using extinction measurements by means of a CIMEL CE 318-1 sun-photometer. In addition, sky radiance measurements performed in Principal Plane in conjunction with solar irradiance measurements were used to retrieve columnar aerosol size distributions, single scattering albedo and asymmetry parameter. During these desert dust intrusions, high values of AOD at 440 nm (0.27 ± 0.17) and low values of α (0.4 ± 0.2) were found. These values indicate both high aerosol load and predominance of coarse particles during these events. The aerosol volume size distributions were bimodal, with the fine and coarse radius mode centered at 0.20 μm and 2.41 μm, respectively. The mean coarse to fine volume concentration ratio value was 11 ± 6, showing a predominance of coarse particles in good agreement with α analysis. During these events, columnar aerosol single scattering albedo (ω0) increased with wavelength in accordance with previous works. However, the obtained values of ω0 in all wavelengths were lower than those reported by other authors during desert dust intrusions. The mixing of desert dust with absorbing particles from anthropogenic origin could explain the low ω0 values measured in the study area.
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aerosol optical properties assessed by an inversion method using the solar Principal Plane for non spherical particles
Journal of Quantitative Spectroscopy & Radiative Transfer, 2008Co-Authors: F J Olmo, A Quirantes, V Lara, H Lyamani, L AladosarboledasAbstract:Adequate modeling of light scattering by non-spherical particles is one of the major difficulties in remote sensing of atmospheric aerosols, mainly in desert dust outbreaks. In this paper we test a parameterization of the particle shape in size distribution, single-scattering albedo, phase function and asymmetry parameter retrieval from beam and sky-radiance measurements, based on the model Skyrad.pack, taking into account the Principal Plane measurements configuration. The method is applied under different Saharan dust outbreaks. We compare the results with those obtained by the almucantar measurements configuration. The results obtained by both methodologies agree and make possible to extend the parameter retrieval to smaller zenith angles than that used in the retrieval from almucantar geometries.
Wei Feng - One of the best experts on this subject based on the ideXlab platform.
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Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data
Frontiers Media S.A., 2018Co-Authors: Binbin Guo, Wei Feng, Yun-ji Zhu, Yi Zhou, Xing-xu RenAbstract:Remote sensing techniques can be efficient for non-destructive, rapid detection of wheat nitrogen (N) nutrient status. In the paper, we examined the relationships of canopy multi-angular data with aerial N uptake of winter wheat (Triticum aestivum L.) across different growing seasons, locations, years, wheat varieties, and N application rates. Seventeen vegetation indices (VIs) selected from the literature were measured for the stability in estimating aerial N uptake of wheat under 13 view zenith angles (VZAs) in the solar Principal Plane (SPP). In total, the back-scatter angles showed better VI behavior than the forward-scatter angles. The correlation coefficient of VIs with aerial N uptake increased with decreasing VZAs. The best linear relationship was integrated with the optimized common indices DIDA and DDn to examine dynamic changes in aerial N uptake; this led to coefficients of determination (R2) of 0.769 and 0.760 at the −10° viewing angle. Our novel area index, designed the modified right-side peak area index (mRPA), was developed in accordance with exploration of the spectral area calculation and red-edge feature using the equation: mRPA = (R760/R600)1/2 × (R760-R718). Investigating the predictive accuracy of mRPA for aerial N uptake across VZAs demonstrated that the best performance was at −10° [R2 = 0.804, p < 0.001, root mean square error (RMSE) = 3.615] and that the effect was relatively similar between −20° to +10° (R2 = 0.782, p < 0.001, RMSE = 3.805). This leads us to construct a simple model under wide-angle combinations so as to improve the field operation simplicity and applicability. Fitting independent datasets to the models resulted in relative error (RE, %) values of 12.6, 14.1, and 14.9% between estimated and measured aerial N uptake for mRPA, DIDA, and DDn across the range of −20° to +10°, respectively, further confirming the superior test performance of the mRPA index. These results illustrate that the novel index mRPA represents a more accurate assessment of plant N status, which is beneficial for guiding N management in winter wheat
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using multi angle hyperspectral data to monitor canopy leaf nitrogen content of wheat
Precision Agriculture, 2016Co-Authors: Xiao Song, Wei Feng, Yonghua Wang, Zhijie Wang, Craig A Coburn, Tiancai GuoAbstract:Nitrogen (N) content is an important factor that can affect wheat production. The non-destructive testing of wheat canopy leaf N content through multi-angle hyperspectral remote sensing is of great importance for wheat production and management. Based on a 2-year experiment for winter wheat in Lethbridge (Canada), Zhengzhou (China), and Kaifeng (China) growing under different cultivation practices, the authors studied the relationships between N content and wheat canopy spectral data in solar Principal Plane (SPP) and perpendicular Plane (PP) at different observation angles. Modeling was conducted according to the spectrum index with the highest correlation coefficient and the corresponding observation angle. The results showed that correlation coefficient between the spectral index and canopy leaf N content at each observation angle of the SPP was significantly higher than that of the PP. Significant differences in the correlation coefficient were also observed at different observation angles of the same observation Plane, and the correlation coefficients of angles of −30° and −40° were higher than others. A model fitted by a power function by using mND705 as independent variable at an angle of −40° in the SPP showed the highest accuracy.
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improved remote sensing of leaf nitrogen concentration in winter wheat using multi angular hyperspectral data
Remote Sensing of Environment, 2016Co-Authors: Xiao Song, Wei Feng, Binbin Guo, Yuanshuai Zhang, Yonghua Wang, Chenyang Wang, Tiancai GuoAbstract:Abstract Real-time, nondestructive monitoring of crop nitrogen (N) status is important for precise N management in winter wheat production. Nadir viewing passive multispectral sensors have limited utility for measuring the N status of winter wheat in middle and bottom layers, and multi-angular remote sensors may instead improve detection of whole canopy physiological and biochemical parameters. Our objective was to improve the predictive accuracy and angular stability of leaf nitrogen concentration (LNC) measurement by constructing a novel Angular Insensitivity Vegetation Index (AIVI). We quantified the relationship between LNC and ground-based multi-angular hyperspectral reflectance in winter wheat ( Triticum aestivum L.) across different growth stages, plant types, N rates, planting density, ecological sites and years. The optimum vegetation indices (VIs) obtained from 17 traditional indices reported in the literature were tested for their stability in estimating LNC at 13 view zenith angles (VZAs) in the solar Principal Plane (SPP). Overall the back-scatter direction gave improved index performance, relative to the nadir and forward-scattering direction. Red-edge VIs (e.g., mND705, GND [750,550], NDRE, RI-1dB) were highly correlated with LNC. However, the relationships strongly depended on experimental conditions, and these VIs tended to saturate at the highest LNC (4.5%). To further overcome the influence of different experimental conditions and VZAs on VIs, we developed a novel index, Angular Insensitivity Vegetation Index (AIVI), based on red-edge, blue and green bands. Our new model showed the highest association with LNC ( R 2 = 0.73–0.87) compared to traditional VIs. Investigating AIVI predictive accuracy in measuring LNC across view zenith angles (VZAs) revealed that performance was the highest at − 20° and was relatively homogenous between − 10° and − 40°. This provided a united, predictive model across this wide-angle range, which enhances the possibility of N monitoring by using portable monitors. Testing of the models with independent data gave R 2 of 0.84 at − 20°, and 0.83 across the range of − 10° to − 40°, respectively. These results suggest that the novel AIVI is more effective for monitoring LNC than previously reported VIs for predicting accuracy, monitoring model stability and view angle independency. More generally, our model indicates the importance of accounting for angular effects when analyzing VIs under different experimental conditions.