Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian prod...Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian product based on local statistics. Increasing the number of samples in the local window can improve the estimation bias, but cause the loss of the estimated images spatial resolution. The limitations of these estimators lead to unclear contour of the disturbed region, and even the omission of fine change targets. In this paper, a CCD approach is proposed to detect fine scene changes from multi-temporal and multi-angle SAR image pairs. Multi-angle CCD estimator can improve the contrast between the change target and the background clutter by jointly accumulating singleangle alternative estimator results without further loss of image resolution. The sensitivity of detection performance to image quantity and angle interval is analyzed. Theoretical analysis and experimental results verify the performance of the proposed algorithm.展开更多
为研究减蛋综合征病毒亚单位疫苗,构建了表达减蛋综合征病毒(Egg drop syndrome virus,EDSV)Knob-S蛋白的大肠杆菌重组菌株,成功表达出可溶性的Knob-S蛋白,血凝(Hemagglutination,HA)和交叉血凝抑制(Hemagglutination inhibition,HI)试...为研究减蛋综合征病毒亚单位疫苗,构建了表达减蛋综合征病毒(Egg drop syndrome virus,EDSV)Knob-S蛋白的大肠杆菌重组菌株,成功表达出可溶性的Knob-S蛋白,血凝(Hemagglutination,HA)和交叉血凝抑制(Hemagglutination inhibition,HI)试验结果表明,该蛋白具有良好的生物学活性。分别以HA效价为1:32、1:64、1:128的Knob-S蛋白制备油乳剂灭活疫苗,免疫147日龄SPF鸡21 d后的HI抗体检测结果显示,HA效价为1:64和1:128制备疫苗免疫组可产生良好的HI抗体(≥7.1log2),攻毒结果显示,当HI抗体效价≥6log2时可提供有效的攻毒保护。结果表明,表达的Knob-S蛋白具有良好免疫原性,可作为减蛋综合征病毒亚单位疫苗制备的候选毒株。展开更多
Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have i...Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have investigated automated rice panicle counting. This paper describes a novel method for automatically and nonintrusively determining rice panicle numbers during the full heading stage by analyzing color images of rice plants taken from multiple angles. Pot-grown rice plants were transferred via an industrial conveyer to an imaging chamber. Color images from different angles were automatically acquired as a turntable rotated the plant. The images were then analyzed and the panicle number of each plant was determined. The image analysis pipeline consisted of extracting the i2 plane from the original color image, segmenting the image, discriminating the panicles from the rest of the plant using an artificial neural network, and calculating the panicle number in the current image. The panicle number of the plant was taken as the maximum of the panicle numbers extracted from all 12 multi-angle images. A total of 105 rice plants during the full heading stage were examined to test the performance of the method. The mean absolute error of the manual and automatic count was 0.5, with 95.3% of the plants yielding absolute errors within ± 1. The method will be useful for evaluating rice panicles and will serve as an important supplementary method for high-throughput rice phenotyping.展开更多
The traditional remote sensing mainly detects the ground vertically to obtain the 2D information but it is hard to get adequate parameters for the quantitative remote sensing to invert land features. The multi-angle o...The traditional remote sensing mainly detects the ground vertically to obtain the 2D information but it is hard to get adequate parameters for the quantitative remote sensing to invert land features. The multi-angle observation can get more detailed and reliable 3D structural parameters of targets, so it makes the quantitative remote sensing applicable. During the process of reflecting, scattering and transmitting the electromagnetic wave, minerals and rocks could reveal the polarized features related to the nature of themselves. Therefore, it has become a new approach of quantitative remote sensing to detect multi-angle polarized information of minerals and rocks. In respect that the polarized reflectance always goes with the bidirectional one, we can obtain the 3D spatial distribution of targets by a polarized means together with detecting its bi-directional reflectance. From the perspective of multi-angle polarized remote sensing mechanism, the quantitative relationship between multi-angle polarized reflectance and the BRDF is studied in this paper. And it is testified that the bi-directional reflectance, polarized reflectance of 45° and the mean value of polarized reflectance are equal to that of the corresponding azimuth angle, zenith angle, detection angle and detection channels in 27t space by experiment.展开更多
Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. Th...Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. The practical applications drive us to make improvements on the conventional linear rail GB-SAR system in order to achieve larger field imaging. First, a turntable is utilized to support the rotational movement of the radar.Next, a series of high-squint scanning is performed with multiple squint angles. Further, the high squint modulation phase of the echo data is eliminated. Then, a new multi-angle imaging method is performed in the wave number domain to expand the field of view. Simulation and real experiments verify the effectiveness of this method.展开更多
This study clarifies the seepage characteristics of complex fractured pressure-sensitive reservoirs,and addresses a common technological problem,that is the alteration of the permeability degree of the reservoir bed(k...This study clarifies the seepage characteristics of complex fractured pressure-sensitive reservoirs,and addresses a common technological problem,that is the alteration of the permeability degree of the reservoir bed(known to be responsible for changes in the direction and velocity of fluid flows between wells).On the basis of a new pressuresensitive equation that considers the fracture directional pressure-sensitive effect,an oil-gas-water three-phase seepage mathematical model is introduced,which can be applied to pressure-sensitive,full-tensor permeability,ultralow-permeability reservoirs with fracture-induced anisotropy.Accordingly,numerical simulations are conducted to explore the seepage laws for ultralow-permeability reservoirs.The results show that element patterns have the highest recovery percentage under a fracture angle of 45°.Accounting for the pressure-sensitive effect produces a decrease in the recovery percentage.Several patterns are considered:inverted five-seven-and nine-spot patterns and a cross-row well pattern.Finally,two strategies are introduced to counteract the rotation of the direction of the principal permeability due to the fracture directional pressure-sensitive effect.展开更多
Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)t...Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.展开更多
文摘Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian product based on local statistics. Increasing the number of samples in the local window can improve the estimation bias, but cause the loss of the estimated images spatial resolution. The limitations of these estimators lead to unclear contour of the disturbed region, and even the omission of fine change targets. In this paper, a CCD approach is proposed to detect fine scene changes from multi-temporal and multi-angle SAR image pairs. Multi-angle CCD estimator can improve the contrast between the change target and the background clutter by jointly accumulating singleangle alternative estimator results without further loss of image resolution. The sensitivity of detection performance to image quantity and angle interval is analyzed. Theoretical analysis and experimental results verify the performance of the proposed algorithm.
基金supported by grants from the National High Technology Research and Development Program of China(2013AA102403)the National Natural Science Foundation of China (30921091, 31200274)+1 种基金the Program for New Century Excellent Talents in University (NCET-10-0386)the Fundamental Research Funds for the Central Universities (2013PY034, 2014BQ010)
文摘Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have investigated automated rice panicle counting. This paper describes a novel method for automatically and nonintrusively determining rice panicle numbers during the full heading stage by analyzing color images of rice plants taken from multiple angles. Pot-grown rice plants were transferred via an industrial conveyer to an imaging chamber. Color images from different angles were automatically acquired as a turntable rotated the plant. The images were then analyzed and the panicle number of each plant was determined. The image analysis pipeline consisted of extracting the i2 plane from the original color image, segmenting the image, discriminating the panicles from the rest of the plant using an artificial neural network, and calculating the panicle number in the current image. The panicle number of the plant was taken as the maximum of the panicle numbers extracted from all 12 multi-angle images. A total of 105 rice plants during the full heading stage were examined to test the performance of the method. The mean absolute error of the manual and automatic count was 0.5, with 95.3% of the plants yielding absolute errors within ± 1. The method will be useful for evaluating rice panicles and will serve as an important supplementary method for high-throughput rice phenotyping.
基金Project KZCX3-S W-338-1 supported by Science and Technology Innovation Foundation of Chinese Academy of Science and 49771057 supported by theNational Natural Science Foundation of China
文摘The traditional remote sensing mainly detects the ground vertically to obtain the 2D information but it is hard to get adequate parameters for the quantitative remote sensing to invert land features. The multi-angle observation can get more detailed and reliable 3D structural parameters of targets, so it makes the quantitative remote sensing applicable. During the process of reflecting, scattering and transmitting the electromagnetic wave, minerals and rocks could reveal the polarized features related to the nature of themselves. Therefore, it has become a new approach of quantitative remote sensing to detect multi-angle polarized information of minerals and rocks. In respect that the polarized reflectance always goes with the bidirectional one, we can obtain the 3D spatial distribution of targets by a polarized means together with detecting its bi-directional reflectance. From the perspective of multi-angle polarized remote sensing mechanism, the quantitative relationship between multi-angle polarized reflectance and the BRDF is studied in this paper. And it is testified that the bi-directional reflectance, polarized reflectance of 45° and the mean value of polarized reflectance are equal to that of the corresponding azimuth angle, zenith angle, detection angle and detection channels in 27t space by experiment.
基金supported by the National Natural Science Foundation of China(61801007)the Beijing Natural Science Foundation(4194075)。
文摘Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. The practical applications drive us to make improvements on the conventional linear rail GB-SAR system in order to achieve larger field imaging. First, a turntable is utilized to support the rotational movement of the radar.Next, a series of high-squint scanning is performed with multiple squint angles. Further, the high squint modulation phase of the echo data is eliminated. Then, a new multi-angle imaging method is performed in the wave number domain to expand the field of view. Simulation and real experiments verify the effectiveness of this method.
基金This work is financially supported by the National Natural Science Foundation Project(No.51374222)National Major Project(No.2017ZX05032004-002)+2 种基金the National Key Basic Research&Development Program(No.2015CB250905)CNPC’s Major Scientific and Technological Project(No.2017E-0405)SINOPEC Major Scientific Research Project(No.P18049-1).
文摘This study clarifies the seepage characteristics of complex fractured pressure-sensitive reservoirs,and addresses a common technological problem,that is the alteration of the permeability degree of the reservoir bed(known to be responsible for changes in the direction and velocity of fluid flows between wells).On the basis of a new pressuresensitive equation that considers the fracture directional pressure-sensitive effect,an oil-gas-water three-phase seepage mathematical model is introduced,which can be applied to pressure-sensitive,full-tensor permeability,ultralow-permeability reservoirs with fracture-induced anisotropy.Accordingly,numerical simulations are conducted to explore the seepage laws for ultralow-permeability reservoirs.The results show that element patterns have the highest recovery percentage under a fracture angle of 45°.Accounting for the pressure-sensitive effect produces a decrease in the recovery percentage.Several patterns are considered:inverted five-seven-and nine-spot patterns and a cross-row well pattern.Finally,two strategies are introduced to counteract the rotation of the direction of the principal permeability due to the fracture directional pressure-sensitive effect.
基金the National Natural Science Foundation of China(Grant Nos.42025504,No.41905023)National Natural Science Youth Science Foundation(Grant No.41701406)Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.:2021122).
文摘Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.
