Pub Date : 2015-11-12DOI: 10.1109/IGARSS.2015.7325961
Haris Ahmad Khan, M. Khan, K. Khurshid, J. Chanussot
The problem with visualization of hyper-spectral images on tri-stimulus displays arises from the fact that they contain hundreds of spectral bands while generally used display devices support only three bands/channels namely blue, green and red. Therefore, for visualization a hyper-spectral (HS) image has to be reduced to three bands. The main challenge while performing this band reduction is to retain and display the maximum information available in a hyper-spectral image. Human visual system focuses attention on certain regions in images called “salient regions”. Therefore to provide a comprehensive representation of hyper-spectral data on tri-stimulus displays we propose to use a weighted fusion method of saliency maps and hyper-spectral bands. The efficacy of the proposed algorithm has been demonstrated by tests on both urban and countryside images of AVIRIS and ROSIS sensors.
{"title":"Saliency based visualization of hyper-spectral images","authors":"Haris Ahmad Khan, M. Khan, K. Khurshid, J. Chanussot","doi":"10.1109/IGARSS.2015.7325961","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7325961","url":null,"abstract":"The problem with visualization of hyper-spectral images on tri-stimulus displays arises from the fact that they contain hundreds of spectral bands while generally used display devices support only three bands/channels namely blue, green and red. Therefore, for visualization a hyper-spectral (HS) image has to be reduced to three bands. The main challenge while performing this band reduction is to retain and display the maximum information available in a hyper-spectral image. Human visual system focuses attention on certain regions in images called “salient regions”. Therefore to provide a comprehensive representation of hyper-spectral data on tri-stimulus displays we propose to use a weighted fusion method of saliency maps and hyper-spectral bands. The efficacy of the proposed algorithm has been demonstrated by tests on both urban and countryside images of AVIRIS and ROSIS sensors.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132997865","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 : 2015-11-12DOI: 10.1109/IGARSS.2015.7326299
Youming Wu, Ze Yu, Peng Xiao, Chunsheng Li
An innovative algorithm to suppress the strong azimuth ambiguity in single-look complex (SLC) synthetic aperture radar (SAR) images is presented. The basic idea is to construct a subspace with low ambiguous power and project the original image to the aforementioned subspace to suppress the azimuth ambiguity by the minimum mean square error estimation (MMSE). Compared with most traditional approaches, the proposed one is suitable for any distributed scene and any acquisition mode. Moreover, the proposed approach seems to keep the resolution in a reasonable level and not rely on the system parameters extremely. Raw data from the TerraSAR-X have been used to validate the effect of the azimuth ambiguity suppression by using the new approach.
{"title":"Azimuth ambiguity suppression based on minimum mean square error estimation","authors":"Youming Wu, Ze Yu, Peng Xiao, Chunsheng Li","doi":"10.1109/IGARSS.2015.7326299","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326299","url":null,"abstract":"An innovative algorithm to suppress the strong azimuth ambiguity in single-look complex (SLC) synthetic aperture radar (SAR) images is presented. The basic idea is to construct a subspace with low ambiguous power and project the original image to the aforementioned subspace to suppress the azimuth ambiguity by the minimum mean square error estimation (MMSE). Compared with most traditional approaches, the proposed one is suitable for any distributed scene and any acquisition mode. Moreover, the proposed approach seems to keep the resolution in a reasonable level and not rely on the system parameters extremely. Raw data from the TerraSAR-X have been used to validate the effect of the azimuth ambiguity suppression by using the new approach.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126997844","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 : 2015-11-12DOI: 10.1109/IGARSS.2015.7325730
Hao Liu, Di Zhu, Lijie Niu, Lin Wu, Caiyun Wang, Xue Chen, Xin Zhao, Cheng Zhang, Xiangkun Zhang, X. Yin, Ji Wu
Sea surface salinity (SSS) plays an important role in global water cycle. In recent years, satellite based remote sensing has proven to be a promising approach for global SSS observation. A new payload concept, named MICAP (microwave imager combined active and passive), has been introduced in this paper. MICAP is a suit of active/passive instrument package, which includes L/C/K band one-dimensional MIR (microwave interferometric radiometer) and L-band DBF (digital beamforming) scatterometer, sharing a parabolic cylinder reflector. MICAP has been selected to be a candidate payload for future Chinese ocean salinity mission. In this paper, the MICAP instrument concept, specification and preliminary system design will be introduced.
{"title":"MICAP (Microwave imager combined active and passive): A new instrument for Chinese ocean salinity satellite","authors":"Hao Liu, Di Zhu, Lijie Niu, Lin Wu, Caiyun Wang, Xue Chen, Xin Zhao, Cheng Zhang, Xiangkun Zhang, X. Yin, Ji Wu","doi":"10.1109/IGARSS.2015.7325730","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7325730","url":null,"abstract":"Sea surface salinity (SSS) plays an important role in global water cycle. In recent years, satellite based remote sensing has proven to be a promising approach for global SSS observation. A new payload concept, named MICAP (microwave imager combined active and passive), has been introduced in this paper. MICAP is a suit of active/passive instrument package, which includes L/C/K band one-dimensional MIR (microwave interferometric radiometer) and L-band DBF (digital beamforming) scatterometer, sharing a parabolic cylinder reflector. MICAP has been selected to be a candidate payload for future Chinese ocean salinity mission. In this paper, the MICAP instrument concept, specification and preliminary system design will be introduced.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122582136","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 : 2015-11-12DOI: 10.1109/IGARSS.2015.7326542
Minyoung Jung, J. Yeom, Yongil Kim
In many agricultural applications, PolSAR data are widely used because they can be decomposed into various scattering components, which can be of help in observing the characteristics of agricultural areas. Recently, studies have been conducted to find suitable polarimetric parameters for specific applications. This paper tried to find appropriate polarimetric parameters for line extraction from agricultural areas as the line features are among the basic features of the surface. Towards this end, various polarimetric parameters were produced using polarimetric decomposition methods. LSD was used to extract lines from each polarimetric parameter image over agricultural areas, without any threshold value selection. The comparison of the line extraction result from each polarimetric parameter with the others was conducted through quantitative evaluation. Through this process, three parameters of the Pauli decomposition is found to be the suitable polarimetric parameters for line extraction from agricultural areas.
{"title":"Usefulness assessment of polarimetric parameters for line extraction from agricultural areas","authors":"Minyoung Jung, J. Yeom, Yongil Kim","doi":"10.1109/IGARSS.2015.7326542","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326542","url":null,"abstract":"In many agricultural applications, PolSAR data are widely used because they can be decomposed into various scattering components, which can be of help in observing the characteristics of agricultural areas. Recently, studies have been conducted to find suitable polarimetric parameters for specific applications. This paper tried to find appropriate polarimetric parameters for line extraction from agricultural areas as the line features are among the basic features of the surface. Towards this end, various polarimetric parameters were produced using polarimetric decomposition methods. LSD was used to extract lines from each polarimetric parameter image over agricultural areas, without any threshold value selection. The comparison of the line extraction result from each polarimetric parameter with the others was conducted through quantitative evaluation. Through this process, three parameters of the Pauli decomposition is found to be the suitable polarimetric parameters for line extraction from agricultural areas.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120960932","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 : 2015-11-12DOI: 10.1109/IGARSS.2015.7326736
S. Paloscia, S. Pettinato, E. Santi, C. Notarnicola, F. Greifeneder, G. Cuozzo, Irene Nicolini, B. Demir, L. Bruzzone
This research aims at analyzing the integration of C and X band data collected from Radarsat2 (RS2) and COSMO-SkyMed (CSK) systems on some test areas in Italy, in order to estimate the main geophysical parameters of soil and vegetation, such as soil moisture and vegetation biomass. A check of the sensitivity of SAR signal to the soil parameters was first carried out on both test sites. Over the South-Tyrol area a retrieval approach based on the Support Vector Regression methodology, which was already tested in this area using C-band data from ENVISAT/ASAR data, was carried out. From these preliminary results it can be concluded that X-band images combined with C-band images could provide valuable information for the retrieval of SMC, even though further investigations should be carried out on a larger time-series and larger set of samples.
{"title":"An analysis of the capabilities of COSMO-SKYMED and RADARSAT systems for agricultural area monitoring","authors":"S. Paloscia, S. Pettinato, E. Santi, C. Notarnicola, F. Greifeneder, G. Cuozzo, Irene Nicolini, B. Demir, L. Bruzzone","doi":"10.1109/IGARSS.2015.7326736","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326736","url":null,"abstract":"This research aims at analyzing the integration of C and X band data collected from Radarsat2 (RS2) and COSMO-SkyMed (CSK) systems on some test areas in Italy, in order to estimate the main geophysical parameters of soil and vegetation, such as soil moisture and vegetation biomass. A check of the sensitivity of SAR signal to the soil parameters was first carried out on both test sites. Over the South-Tyrol area a retrieval approach based on the Support Vector Regression methodology, which was already tested in this area using C-band data from ENVISAT/ASAR data, was carried out. From these preliminary results it can be concluded that X-band images combined with C-band images could provide valuable information for the retrieval of SMC, even though further investigations should be carried out on a larger time-series and larger set of samples.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129020301","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 : 2015-07-26DOI: 10.1109/IGARSS.2015.7325944
Giuseppe Masi, R. Gaetano, G. Poggi, G. Scarpa
In this paper a new object-oriented segmentation method for high-resolution remote sensing images is proposed. To limit computational complexity, a preliminary superpixel representation of the image is obtained by means of a suitable watershed transform. Then, a region adjacency graph is associated with the superpixels, with edge weights accounting for region similarity/dissimilarity. The final segmentation is then obtained by means of a graph-cutting approach, following a correlation clustering formulation. The optimal cut can be obtained by solving a Integer Linear Programming (ILP) problem, whose complexity, however, grows rapidly with the image size. Much faster near-optimal solutions are obtained, here, with a greedy solution. Experiments on a real-world high-resolution remote sensing image prove the potential of the approach.
{"title":"Superpixel-based segmentation of remote sensing images through correlation clustering","authors":"Giuseppe Masi, R. Gaetano, G. Poggi, G. Scarpa","doi":"10.1109/IGARSS.2015.7325944","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7325944","url":null,"abstract":"In this paper a new object-oriented segmentation method for high-resolution remote sensing images is proposed. To limit computational complexity, a preliminary superpixel representation of the image is obtained by means of a suitable watershed transform. Then, a region adjacency graph is associated with the superpixels, with edge weights accounting for region similarity/dissimilarity. The final segmentation is then obtained by means of a graph-cutting approach, following a correlation clustering formulation. The optimal cut can be obtained by solving a Integer Linear Programming (ILP) problem, whose complexity, however, grows rapidly with the image size. Much faster near-optimal solutions are obtained, here, with a greedy solution. Experiments on a real-world high-resolution remote sensing image prove the potential of the approach.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115011312","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 : 2015-07-26DOI: 10.1109/IGARSS.2015.7326678
S. Błoński, C. Cao
Radiometric calibration coefficients for the VIIRS reflective solar bands have been reprocessed from the beginning of the Suomi NPP mission until present. An automated calibration procedure, implemented in the JPSS operational data production system, was applied to reprocess onboard solar calibration data and solar diffuser degradation measurements. The latest processing parameters from the operational system were used to include corrected solar vectors, optimized directional dependence of attenuation screens transmittance and solar diffuser reflectance, updated pre-launch calibration coefficients without an offset term, and optimized Robust Holt-Winters filter parameters. The parameters were consistently used to generate a complete set of the radiometric calibration coefficients for the entire duration of the Suomi NPP mission. The reprocessing has also demonstrated that the automated calibration procedure can be successfully applied to all solar measurements acquired from the beginning of the mission until the full deployment of the automated procedure in the operational processing system.
{"title":"Viirs reflective solar bands calibration reprocessing","authors":"S. Błoński, C. Cao","doi":"10.1109/IGARSS.2015.7326678","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326678","url":null,"abstract":"Radiometric calibration coefficients for the VIIRS reflective solar bands have been reprocessed from the beginning of the Suomi NPP mission until present. An automated calibration procedure, implemented in the JPSS operational data production system, was applied to reprocess onboard solar calibration data and solar diffuser degradation measurements. The latest processing parameters from the operational system were used to include corrected solar vectors, optimized directional dependence of attenuation screens transmittance and solar diffuser reflectance, updated pre-launch calibration coefficients without an offset term, and optimized Robust Holt-Winters filter parameters. The parameters were consistently used to generate a complete set of the radiometric calibration coefficients for the entire duration of the Suomi NPP mission. The reprocessing has also demonstrated that the automated calibration procedure can be successfully applied to all solar measurements acquired from the beginning of the mission until the full deployment of the automated procedure in the operational processing system.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115126700","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 : 2015-07-26DOI: 10.1109/IGARSS.2015.7326911
Yang Li, Yunping Chen, Zhihang Xue, Yongxing Cao, Wenzhu He, L. Tong
Fine registration is a fundamental step for further application of remote sensing images. Focused on deficiencies in traditional manual registration, this paper presents a new method for automatic fine registration of multi-spectral images. To make the most of image information, the algorithm detects and matches feature points in the selected bands. Then pick up the common control points which contain more reliability relative to others after eliminating wrong matching points. The last registration model can be built based on common control points and the points selected by common ones. Experimental results with Landsat TM5 images demonstrate that the method is more accurate and suitable for automatic batch processing.
{"title":"A new method for automatic fine registration of multi-spectral remote sensing images","authors":"Yang Li, Yunping Chen, Zhihang Xue, Yongxing Cao, Wenzhu He, L. Tong","doi":"10.1109/IGARSS.2015.7326911","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326911","url":null,"abstract":"Fine registration is a fundamental step for further application of remote sensing images. Focused on deficiencies in traditional manual registration, this paper presents a new method for automatic fine registration of multi-spectral images. To make the most of image information, the algorithm detects and matches feature points in the selected bands. Then pick up the common control points which contain more reliability relative to others after eliminating wrong matching points. The last registration model can be built based on common control points and the points selected by common ones. Experimental results with Landsat TM5 images demonstrate that the method is more accurate and suitable for automatic batch processing.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115233333","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 : 2015-07-26DOI: 10.1109/IGARSS.2015.7326036
E. Cristofori, S. Balbo, Walther Camaro, P. Pasquali, P. Boccardo, Alessandro Demarchi
This paper presents a methodology aimed at enabling local government personnel and decision makers to easily process satellite-derived precipitation data for the assessment of extreme precipitation hazard and to integrate them with geospatial reference datasets for the production of timely and meaningful flood risk information, considering also the assessment of exposed infrastructure, population or assets. The methodology relies on the use of the Malawi Spatial Data Platform (MASDAP), a GeoNode web platform for the management and publication of geospatial data, developed in the framework of the Shire River Basin Management Program (SRBMP). The proposed work-flow has been illustrated during a capacity building training held in Blantyre (Malawi) in December 2015 and constitutes a standardizable decision support approach, particularly useful for countries where meteo-hydrological observations are scarce or have a too coarse resolution.
{"title":"Flood risk web-mapping for decision makers: A service proposal based on satellite-derived precipitation analysis and geonode","authors":"E. Cristofori, S. Balbo, Walther Camaro, P. Pasquali, P. Boccardo, Alessandro Demarchi","doi":"10.1109/IGARSS.2015.7326036","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326036","url":null,"abstract":"This paper presents a methodology aimed at enabling local government personnel and decision makers to easily process satellite-derived precipitation data for the assessment of extreme precipitation hazard and to integrate them with geospatial reference datasets for the production of timely and meaningful flood risk information, considering also the assessment of exposed infrastructure, population or assets. The methodology relies on the use of the Malawi Spatial Data Platform (MASDAP), a GeoNode web platform for the management and publication of geospatial data, developed in the framework of the Shire River Basin Management Program (SRBMP). The proposed work-flow has been illustrated during a capacity building training held in Blantyre (Malawi) in December 2015 and constitutes a standardizable decision support approach, particularly useful for countries where meteo-hydrological observations are scarce or have a too coarse resolution.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115503559","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 : 2015-07-26DOI: 10.1109/IGARSS.2015.7326859
F. Huang, Jinrong Han
Based on Landsat ETM+ images in 2000, 2005 and 2010, land use/cover were extracted and carbon storage was estimated using InVEST model in the urban agglomeration of central and southern Liaoning province. Urban area increased by 6.12×104ha while carbon storage dropped by 25.69×104 tons during past ten years. The rapid urban expansion in central and southern Liaoning province causing dramatic land use/cover changes may affect carbon stocks of terrestrial ecosystems. The results will provide scientific basis for reasonable utilization of land resources and protection of ecological environment.
{"title":"Land use/cover and carbon storage changes in central and southern Liaoning urban agglomerations, China","authors":"F. Huang, Jinrong Han","doi":"10.1109/IGARSS.2015.7326859","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326859","url":null,"abstract":"Based on Landsat ETM+ images in 2000, 2005 and 2010, land use/cover were extracted and carbon storage was estimated using InVEST model in the urban agglomeration of central and southern Liaoning province. Urban area increased by 6.12×104ha while carbon storage dropped by 25.69×104 tons during past ten years. The rapid urban expansion in central and southern Liaoning province causing dramatic land use/cover changes may affect carbon stocks of terrestrial ecosystems. The results will provide scientific basis for reasonable utilization of land resources and protection of ecological environment.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115599685","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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