Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576789
G. Prost
{"title":"Structural Geomorphology In Petroleum Exploration: Geologic Remote Sensing And The Search For The Subtle Trap","authors":"G. Prost","doi":"10.1109/IGARSS.1992.576789","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576789","url":null,"abstract":"","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133717281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576625
H.J.C. van Leeuwenl, G. Lemoine, D. Hoekman
A simple semi-empirical backscattering model for the crop-soil system is the CLOUD model. This model accounts for the backscattering of avegetation, modeled as a water cloud, and the backscattercontribution of the soil that is attenuated by one or more canopy layers. In our paper we will illustrate the use of the CLOUD model with scatterometer data from potato and sugar beet crops from the AGRISCATT 88 data set. We have extended the soil backscatter contribution in the CLOUD model to include appropriate soil models for these two types of crops. This extension is necessary to interpret the observed row-direction effect in the potato crop. The parameters derived from the AGRISCAlT data set are compared to results from literature. Using our results, we show the possibility to derive soil and crop parameters from the 1989 MAESTRO-1 data set over the Flevoland agricultural test site.
{"title":"Model-based Derivation Of Vegetation And Soil Parameters In Multi-frequency Radar Data Sets","authors":"H.J.C. van Leeuwenl, G. Lemoine, D. Hoekman","doi":"10.1109/IGARSS.1992.576625","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576625","url":null,"abstract":"A simple semi-empirical backscattering model for the crop-soil system is the CLOUD model. This model accounts for the backscattering of avegetation, modeled as a water cloud, and the backscattercontribution of the soil that is attenuated by one or more canopy layers. In our paper we will illustrate the use of the CLOUD model with scatterometer data from potato and sugar beet crops from the AGRISCATT 88 data set. We have extended the soil backscatter contribution in the CLOUD model to include appropriate soil models for these two types of crops. This extension is necessary to interpret the observed row-direction effect in the potato crop. The parameters derived from the AGRISCAlT data set are compared to results from literature. Using our results, we show the possibility to derive soil and crop parameters from the 1989 MAESTRO-1 data set over the Flevoland agricultural test site.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"65 Supplement 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133575149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578423
D.L. Williams, V. I. Kharuk, V.M. Jhirin, B. Rock, K. Ranson, C. Wessman, B. Curtiss
The field experiment described took place in the Sayani Mountains of Siberia. The purpose of the joint field campaign was to observe and exchange methodologies with Russian scientists with regard to the development of remote sensing techniques for the early detection and assessment of forest decline damage believed to be associated with atmospheric deposition and/or insect and disease infestations. Several types of passive and active remote sensing measurements were made in conjunction with biophysical measurements on vegetative samples collected from four study sites representing a strong elevational gradient. Relatively cloud-free SPOT data were also acquired over the study area. Moderate canopy damage was recorded at the mid-elevation site (3400 ft/1037 m). The lowest levels of damage were recorded at the lowest elevation site (2300 ft/701 m.) At all sites, east versus west flagging of the canopy was noted (i.e., full canopy on the west-facing side of the canopy, significantly less foliage on the east-facing side).
{"title":"Sayani '91: A Joint United States / Commonwealth of Independent States Field Campaign to Investigate Forest Decline Damage in the Krasnoyarsk Region of Southcentral Siberia","authors":"D.L. Williams, V. I. Kharuk, V.M. Jhirin, B. Rock, K. Ranson, C. Wessman, B. Curtiss","doi":"10.1109/IGARSS.1992.578423","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578423","url":null,"abstract":"The field experiment described took place in the Sayani Mountains of Siberia. The purpose of the joint field campaign was to observe and exchange methodologies with Russian scientists with regard to the development of remote sensing techniques for the early detection and assessment of forest decline damage believed to be associated with atmospheric deposition and/or insect and disease infestations. Several types of passive and active remote sensing measurements were made in conjunction with biophysical measurements on vegetative samples collected from four study sites representing a strong elevational gradient. Relatively cloud-free SPOT data were also acquired over the study area. Moderate canopy damage was recorded at the mid-elevation site (3400 ft/1037 m). The lowest levels of damage were recorded at the lowest elevation site (2300 ft/701 m.) At all sites, east versus west flagging of the canopy was noted (i.e., full canopy on the west-facing side of the canopy, significantly less foliage on the east-facing side).","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121080082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578869
P. Canuti, G. D'Auria, P. Pampaloni, D. Solimini
Remote sensing techniques can be a very useful method for monitoring hydrological parameters in large watersheds at a relatively low cost. However the operational capability of remote sensing is not yet fully exploited and much research is in progress especially on the use of new sensors and on the algorithms for the extraction of geophysical parameters. A research activity, which aims at a better understanding of the information that can be obtained from multifrequency polarimetric Synthetic Aperture Radar to be used in hydrology, has been started in the framework of SIR-C/X-SAR Project. The site of Montespertoli (Italy) was imaged three times during the Multisensor Airborne Campaign (MAC 91), carried out in summer 1991 on several sites in Europe, based on NASA/JPL AIRSAR. This paper presents an overview of the experiments which have been carried out during the campaign and a preliminary analysis of the obtained results
{"title":"Mac 91 on Montespertolk an Experiment for Agro-Hydrology","authors":"P. Canuti, G. D'Auria, P. Pampaloni, D. Solimini","doi":"10.1109/IGARSS.1992.578869","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578869","url":null,"abstract":"Remote sensing techniques can be a very useful method for monitoring hydrological parameters in large watersheds at a relatively low cost. However the operational capability of remote sensing is not yet fully exploited and much research is in progress especially on the use of new sensors and on the algorithms for the extraction of geophysical parameters. A research activity, which aims at a better understanding of the information that can be obtained from multifrequency polarimetric Synthetic Aperture Radar to be used in hydrology, has been started in the framework of SIR-C/X-SAR Project. The site of Montespertoli (Italy) was imaged three times during the Multisensor Airborne Campaign (MAC 91), carried out in summer 1991 on several sites in Europe, based on NASA/JPL AIRSAR. This paper presents an overview of the experiments which have been carried out during the campaign and a preliminary analysis of the obtained results","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114762337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576774
E. Rignot, M. Drinkwater
Quantitatively we investigate how multifrequency polarimetric radar imagery enhances our current ability to separate different Sea-ice types using single frequency, single polarization SAR data. Backscatter characteristics of six radiometrically and polarimetrically distinct sea-ice types are selected in an unsupervised range dependent analysis of mulfrom right to left. The incidence angle (6') varies between 22 and 52O, and pixel spacing is 6.7m in range, by 12.0m in azimuth. The entire scene is approximately 12km by 5km. 2. Range dependent segmentation of the SAR data tifrequency polarimetric SAR data using the MAP polarimetric classifier. Maximum ice discrimination is achieved with combined C- and L- band full polarimetry, and collocated passive microwave imagery suggest > 90% classification accuracy. C- band vv-pol alone achieves only 68% relative accuracy because it confuses multiyear and rough compressed first year ice. Relative accuracy is increased by 7% with one other channel and is 76% with C-band full polarimetry. L- band, relative classification accuracy is 75%, 83% and 85%, using hh-pol, hh- and vv- combined, or the full polarimetry, respectively. P- band is less accurate. Combinations of two frequencies at a single polarization show the greatest improvement over a single channel. With a relative accuracy of 89%, L-band hh and C-band vv together are almost equivalent to L-, and C-band fully polarimetric data. 1. AIRSAR data
{"title":"On The Application Of Multifrequency Polarimetric Radar Observations To Sea-ice Classification","authors":"E. Rignot, M. Drinkwater","doi":"10.1109/IGARSS.1992.576774","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576774","url":null,"abstract":"Quantitatively we investigate how multifrequency polarimetric radar imagery enhances our current ability to separate different Sea-ice types using single frequency, single polarization SAR data. Backscatter characteristics of six radiometrically and polarimetrically distinct sea-ice types are selected in an unsupervised range dependent analysis of mulfrom right to left. The incidence angle (6') varies between 22 and 52O, and pixel spacing is 6.7m in range, by 12.0m in azimuth. The entire scene is approximately 12km by 5km. 2. Range dependent segmentation of the SAR data tifrequency polarimetric SAR data using the MAP polarimetric classifier. Maximum ice discrimination is achieved with combined C- and L- band full polarimetry, and collocated passive microwave imagery suggest > 90% classification accuracy. C- band vv-pol alone achieves only 68% relative accuracy because it confuses multiyear and rough compressed first year ice. Relative accuracy is increased by 7% with one other channel and is 76% with C-band full polarimetry. L- band, relative classification accuracy is 75%, 83% and 85%, using hh-pol, hh- and vv- combined, or the full polarimetry, respectively. P- band is less accurate. Combinations of two frequencies at a single polarization show the greatest improvement over a single channel. With a relative accuracy of 89%, L-band hh and C-band vv together are almost equivalent to L-, and C-band fully polarimetric data. 1. AIRSAR data","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115958789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576720
K. S. Kierein-Young, F. Kruse, A. B. Lefkoff
The Jet Propulsion Laboratory Airborne Synthetic Aperture Radar (JPL-AIRSAR) is used to collect full polarimetric measurements at P-, L-, and C-bands. These data are analyzed using the radar analysis and visualization environment (RAVEN). The AIRSAR data are calibrated using in-scene corner reflectors to allow for quantitative analysis of the radar backscatter. RAVEN is used to extract surface characteristics. Inversion models are used to calculate quantitative surface roughness values and fractal dimensions. These values are used to generate synthetic surface plots that represent the small-scale surface structure of areas in Death Valley. These procedures are applied to a playa, smooth salt-pan, and alluvial fan surfaces in Death Valley. Field measurements of surface roughness are used to verify the accuracy.
{"title":"Quantitative Analysis Of Surface Characteristics And Morphology In Death Valley, California Using Airsar Data","authors":"K. S. Kierein-Young, F. Kruse, A. B. Lefkoff","doi":"10.1109/IGARSS.1992.576720","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576720","url":null,"abstract":"The Jet Propulsion Laboratory Airborne Synthetic Aperture Radar (JPL-AIRSAR) is used to collect full polarimetric measurements at P-, L-, and C-bands. These data are analyzed using the radar analysis and visualization environment (RAVEN). The AIRSAR data are calibrated using in-scene corner reflectors to allow for quantitative analysis of the radar backscatter. RAVEN is used to extract surface characteristics. Inversion models are used to calculate quantitative surface roughness values and fractal dimensions. These values are used to generate synthetic surface plots that represent the small-scale surface structure of areas in Death Valley. These procedures are applied to a playa, smooth salt-pan, and alluvial fan surfaces in Death Valley. Field measurements of surface roughness are used to verify the accuracy.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116774392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576651
V. Etkin, A.V. Srnirnov
{"title":"Observations Of Internal Waves In Ocean By Radar Methods.","authors":"V. Etkin, A.V. Srnirnov","doi":"10.1109/IGARSS.1992.576651","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576651","url":null,"abstract":"","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116886784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578874
S. Saatchi, D. Lin, J. V. Van Zyl
' Retrieval of soil moisture from microwave remote sensing data has become the corner stone of many land surfacelatmospheric interaction and global hydrology studies and scientific plans. Recently, a number of microwave multisensor aircraft experiments has been devised in order to develop and evaluate techniques for soil moisture retrieval. During the MACHYDRO-90 experiment held in Mahantango watershed in central Pennsylvania, JPL AIRSAR multi-frequency and multi-polarization data were collected over an eleven day period. The main objective of this experiment was to map the spatial distribution of soil moisture and its changes with time within a basin. The research basin is a 7 sq km instrumented watershed. The area is confined by mountains with rolling terrain of elevations between 200 and 300 m and intensively cultivated. JPL AIRSAR was flown over the area four times during the experiment in order to acquire multiple incident angle (20°, 30°, 45') at P, L, and C band over a range of soil moisture conditions from 8% to 25% in volumetric unit. The radar returns from corner reflectors deployed in the watershed have been used to calibrate the system for channel imbalance, cross talk and absolute radiometric calibration. The overflight data acquisition was supported by in situ measurements of soil and vegetation parameters.
{"title":"Soil Moisture Mapping Using Sar Imagery","authors":"S. Saatchi, D. Lin, J. V. Van Zyl","doi":"10.1109/IGARSS.1992.578874","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578874","url":null,"abstract":"' Retrieval of soil moisture from microwave remote sensing data has become the corner stone of many land surfacelatmospheric interaction and global hydrology studies and scientific plans. Recently, a number of microwave multisensor aircraft experiments has been devised in order to develop and evaluate techniques for soil moisture retrieval. During the MACHYDRO-90 experiment held in Mahantango watershed in central Pennsylvania, JPL AIRSAR multi-frequency and multi-polarization data were collected over an eleven day period. The main objective of this experiment was to map the spatial distribution of soil moisture and its changes with time within a basin. The research basin is a 7 sq km instrumented watershed. The area is confined by mountains with rolling terrain of elevations between 200 and 300 m and intensively cultivated. JPL AIRSAR was flown over the area four times during the experiment in order to acquire multiple incident angle (20°, 30°, 45') at P, L, and C band over a range of soil moisture conditions from 8% to 25% in volumetric unit. The radar returns from corner reflectors deployed in the watershed have been used to calibrate the system for channel imbalance, cross talk and absolute radiometric calibration. The overflight data acquisition was supported by in situ measurements of soil and vegetation parameters.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115365064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578356
H. Quelle, J. Boucher, W. Pieczynski
1. Abstract Our work deals with the unsupervised statistical segmentation of SAR images. However the method here developped is a general parameter estimation technique and can be used for most types of images. We adopt a contextual method in which each pixel is classified from the measurements taken in its neighborhood. In this approach the previous statistical problem is the estimation of components of a distribution mixture. We showed in some previous studies that the SEM is well adapted to the problem in this frame, when stationary random fields are considered. In this paper we present a new distribution mixture estimator in which priors can depend on the position of the considered pixel. This makes it valid in the non-stationary case. We describe some situations, based on synthetic images sampled by stationary or non stationary random fields, in which the contextual method based on parameters estimated by our algorithm is more efficient than the same method based on parameters estimated by the SEM algorithm.
{"title":"Local Parameter Estimation and Unsupervised Segmentation of Sar Images","authors":"H. Quelle, J. Boucher, W. Pieczynski","doi":"10.1109/IGARSS.1992.578356","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578356","url":null,"abstract":"1. Abstract Our work deals with the unsupervised statistical segmentation of SAR images. However the method here developped is a general parameter estimation technique and can be used for most types of images. We adopt a contextual method in which each pixel is classified from the measurements taken in its neighborhood. In this approach the previous statistical problem is the estimation of components of a distribution mixture. We showed in some previous studies that the SEM is well adapted to the problem in this frame, when stationary random fields are considered. In this paper we present a new distribution mixture estimator in which priors can depend on the position of the considered pixel. This makes it valid in the non-stationary case. We describe some situations, based on synthetic images sampled by stationary or non stationary random fields, in which the contextual method based on parameters estimated by our algorithm is more efficient than the same method based on parameters estimated by the SEM algorithm.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115396927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578284
J. Daba, M. Bell
Detection and identification of objects in SAR images is complicated by the presence of speckle. This is true for both human and machine detection. We formulate and analyze the performance of maximum likelihood tests for determining the orientation of an object and for discriminating among a set of known objects in a speckled image. We then generalize the tests into three classes of pattern recognition problems, corresponding to orthogonal, antipodal, and biorthogonal signal detection problems. Finally, we compare the performance of these tests to the results of Korwar and Pierce for human interpretation of objects in speckled images.
{"title":"Optimal Object Discrimination and Orientation Determination in Synthetic Aperture Radar Images","authors":"J. Daba, M. Bell","doi":"10.1109/IGARSS.1992.578284","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578284","url":null,"abstract":"Detection and identification of objects in SAR images is complicated by the presence of speckle. This is true for both human and machine detection. We formulate and analyze the performance of maximum likelihood tests for determining the orientation of an object and for discriminating among a set of known objects in a speckled image. We then generalize the tests into three classes of pattern recognition problems, corresponding to orthogonal, antipodal, and biorthogonal signal detection problems. Finally, we compare the performance of these tests to the results of Korwar and Pierce for human interpretation of objects in speckled images.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115519507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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