Pub Date : 2015-07-26DOI: 10.1109/IGARSS.2015.7326088
R. Guinvarc’h, L. Thirion-Lefevre
The double bounce mechanism is the main characteristic in urban areas. This paper describes two physical phenomena that can decrease it (and even suppress it) and thus alter the radar analysis of cities.
{"title":"Propagation in urban areas. Orientation, permittivity and entropy","authors":"R. Guinvarc’h, L. Thirion-Lefevre","doi":"10.1109/IGARSS.2015.7326088","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326088","url":null,"abstract":"The double bounce mechanism is the main characteristic in urban areas. This paper describes two physical phenomena that can decrease it (and even suppress it) and thus alter the radar analysis of cities.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"14 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":"124064365","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.2015.7325752
S. Bellez, C. Bourlier, G. Kubické
In this paper, an efficient hybrid approach to study the ElectroMagnetic (EM) scattering from a three-dimensional (3-D) Perfectly Electric Conducting (PEC) object buried under a two-dimensional (2-D) dielectric rough surface is developed. The electric and magnetic current densities on the rough surface are obtained through the current-based asymptotic Kirchhoff Approximation (KA) formulation whereas the electric current density on the buried object is rigorously determined by solving the Electric Field Integral Equation (EFIE) using the Galerkin's Method of Moments (MoM) with Rao-Wilton-Glisson (RWG) basis functions. The matrix equation arising from the MoM discretization of the hybrid KA-EFIE formulation is then efficiently solved by the iterative PILE (Propagation-Inside-Layer-Expansion) method combined with the algebraic Adaptive Cross Approximation (ACA). The current densities on the dielectric rough surface are thereafter used to handle the bistatic Normalized Radar Cross Section (NRCS) patterns.
本文提出了一种有效的混合方法来研究埋在二维介质粗糙表面下的三维完全导电物体的电磁散射。粗糙表面上的电流和磁场密度通过基于电流的渐近Kirchhoff近似(KA)公式获得，而埋藏物体上的电流密度则通过使用带有Rao-Wilton-Glisson (RWG)基函数的Galerkin矩量法(MoM)求解电场积分方程(EFIE)来严格确定。结合代数自适应交叉逼近(ACA)，采用迭代PILE (propagation - intra - layer - expand)方法对混合KA-EFIE公式的MoM离散化产生的矩阵方程进行了有效求解。然后利用介质粗糙表面上的电流密度来处理双基地归一化雷达截面(NRCS)图。
{"title":"3-D scattering from a PEC target buried beneath a dielectric rough surface using a hybrid formulation and a fast solver","authors":"S. Bellez, C. Bourlier, G. Kubické","doi":"10.1109/IGARSS.2015.7325752","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7325752","url":null,"abstract":"In this paper, an efficient hybrid approach to study the ElectroMagnetic (EM) scattering from a three-dimensional (3-D) Perfectly Electric Conducting (PEC) object buried under a two-dimensional (2-D) dielectric rough surface is developed. The electric and magnetic current densities on the rough surface are obtained through the current-based asymptotic Kirchhoff Approximation (KA) formulation whereas the electric current density on the buried object is rigorously determined by solving the Electric Field Integral Equation (EFIE) using the Galerkin's Method of Moments (MoM) with Rao-Wilton-Glisson (RWG) basis functions. The matrix equation arising from the MoM discretization of the hybrid KA-EFIE formulation is then efficiently solved by the iterative PILE (Propagation-Inside-Layer-Expansion) method combined with the algebraic Adaptive Cross Approximation (ACA). The current densities on the dielectric rough surface are thereafter used to handle the bistatic Normalized Radar Cross Section (NRCS) patterns.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"38 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":"124148047","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.2015.7326708
P. Pampaloni
Monitoring of terrestrial snow on both local and global scales is a topic of ever-increasing interest due to the crucial role that the snow plays in the climate dynamics, water resource management, energy production, and risk prevention. In this framework, microwave remote sensing is an important tool for observing snow cover and retrieving snow depth (SD) and water equivalent (SWE). This paper summarizes the most important aspects of the microwave remote sensing of snow by highlighting major results and problems.
{"title":"Reading snow: A note on microwave remote sensing of snow cover","authors":"P. Pampaloni","doi":"10.1109/IGARSS.2015.7326708","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326708","url":null,"abstract":"Monitoring of terrestrial snow on both local and global scales is a topic of ever-increasing interest due to the crucial role that the snow plays in the climate dynamics, water resource management, energy production, and risk prevention. In this framework, microwave remote sensing is an important tool for observing snow cover and retrieving snow depth (SD) and water equivalent (SWE). This paper summarizes the most important aspects of the microwave remote sensing of snow by highlighting major results and problems.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"92 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":"124161782","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.2015.7326281
Pedram Ghamisi, Dan Wu, Gabriele Cavallaro, J. Benediktsson, S. Phinn, N. Falco
With respect to the exponential increase in the number of available remote sensors in recent years, the possibility of having different types of data captured over the same scene, has resulted in many research works related to the joint use of passive and active sensors for the accurate classification of different materials. However, until now, there is a small number of research works related to the integration of highly valuable information obtained from the joint use of LiDAR and hyperspectral data. This paper proposes an efficient classification approach in terms of accuracies and demanded CPU processing time for integrating big data sets (e.g., LiDAR and hyperspectral) to provide land cover mapping capabilities at a range of spatial scales. In addition, the proposed approach is fully automatic and is able to efficiently handle big data containing a huge number of features with very limited number of training samples in few seconds.
{"title":"An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia","authors":"Pedram Ghamisi, Dan Wu, Gabriele Cavallaro, J. Benediktsson, S. Phinn, N. Falco","doi":"10.1109/IGARSS.2015.7326281","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326281","url":null,"abstract":"With respect to the exponential increase in the number of available remote sensors in recent years, the possibility of having different types of data captured over the same scene, has resulted in many research works related to the joint use of passive and active sensors for the accurate classification of different materials. However, until now, there is a small number of research works related to the integration of highly valuable information obtained from the joint use of LiDAR and hyperspectral data. This paper proposes an efficient classification approach in terms of accuracies and demanded CPU processing time for integrating big data sets (e.g., LiDAR and hyperspectral) to provide land cover mapping capabilities at a range of spatial scales. In addition, the proposed approach is fully automatic and is able to efficiently handle big data containing a huge number of features with very limited number of training samples in few seconds.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"56 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":"127876925","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.2015.7326269
J. Marcello, F. Eugenio, F. Marqués, Javier Martín Abasolo
The analysis of the seafloor in shallow waters using remote sensing imagery at very high spatial resolution is a very challenging topic due to the minimum signal level received; the presence of noisy contributions from the atmosphere, solar reflection, foam, turbidity and water column; and the limited spectral information available for the classification at such depths that impedes, for example, the extraction of vegetation indices. In this complex scenario we have developed a mapping methodology that involves the precise application of pre-processing techniques and the use of efficient classification algorithms. In particular, after a detailed assessment, support vector machines achieved the best performance using the appropriate kernel and parameters. Two natural areas located at the Canary Islands (Spain) have been selected for their benthic habitats richness and specially for their preservation of highly protected seagrass regions.
{"title":"Precise classification of coastal benthic habitats using high resolution Worldview-2 imagery","authors":"J. Marcello, F. Eugenio, F. Marqués, Javier Martín Abasolo","doi":"10.1109/IGARSS.2015.7326269","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326269","url":null,"abstract":"The analysis of the seafloor in shallow waters using remote sensing imagery at very high spatial resolution is a very challenging topic due to the minimum signal level received; the presence of noisy contributions from the atmosphere, solar reflection, foam, turbidity and water column; and the limited spectral information available for the classification at such depths that impedes, for example, the extraction of vegetation indices. In this complex scenario we have developed a mapping methodology that involves the precise application of pre-processing techniques and the use of efficient classification algorithms. In particular, after a detailed assessment, support vector machines achieved the best performance using the appropriate kernel and parameters. Two natural areas located at the Canary Islands (Spain) have been selected for their benthic habitats richness and specially for their preservation of highly protected seagrass regions.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"18 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":"126481850","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.2015.7326316
A. Alyaari, J. Wigneron, A. Ducharne, Y. Kerr, R. Fernandez-Moran, M. Parrens, A. Al Bitar, A. Mialon, P. Richaume
Soil Moisture and Ocean Salinity (SMOS) satellite has been providing surface soil moisture (SSM) and ocean salinity (OS) retrievals at L-band for five years (2010-2014). During these five years, the SSM retrieval algorithm i.e. the L-MEB (L-Band Microwave Emission of the Biosphere [1] model has been progressively improved and hence results in different versions of the SMOS SSM products. This study aims at evaluating the last improvement in the SSM products of the most recent SMOS level 3 (SMOSL3) reprocessing (SMOSL3_2.72) vs. an earlier version (SMOSL3_246). Correlation, bias, Root Mean Square Difference (RMSD) and unbiased RMSD (unbRMSD) were used as performance criteria in this study using the ECMWF SM-DAS-2 product as a reference. Results show that the SMOS SSM estimates have been improved: (i) SMOSL3_272 was closer to SM-DAS-2 over most of the globe-with the exception of arid regions-in terms of unbRMSD (ii) SMOSL3_272 was closer to SM-DAS-2 over Spain, Brazil, parts of Sahel, high latitude and equator regions but comparable with SMOSL3_246 over most of the rest of the globe in terms of correlations.
{"title":"Evaluation of the most recent reprocessed SMOS soil moisture products: Comparison between SMOS level 3 V246 and V272","authors":"A. Alyaari, J. Wigneron, A. Ducharne, Y. Kerr, R. Fernandez-Moran, M. Parrens, A. Al Bitar, A. Mialon, P. Richaume","doi":"10.1109/IGARSS.2015.7326316","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326316","url":null,"abstract":"Soil Moisture and Ocean Salinity (SMOS) satellite has been providing surface soil moisture (SSM) and ocean salinity (OS) retrievals at L-band for five years (2010-2014). During these five years, the SSM retrieval algorithm i.e. the L-MEB (L-Band Microwave Emission of the Biosphere [1] model has been progressively improved and hence results in different versions of the SMOS SSM products. This study aims at evaluating the last improvement in the SSM products of the most recent SMOS level 3 (SMOSL3) reprocessing (SMOSL3_2.72) vs. an earlier version (SMOSL3_246). Correlation, bias, Root Mean Square Difference (RMSD) and unbiased RMSD (unbRMSD) were used as performance criteria in this study using the ECMWF SM-DAS-2 product as a reference. Results show that the SMOS SSM estimates have been improved: (i) SMOSL3_272 was closer to SM-DAS-2 over most of the globe-with the exception of arid regions-in terms of unbRMSD (ii) SMOSL3_272 was closer to SM-DAS-2 over Spain, Brazil, parts of Sahel, high latitude and equator regions but comparable with SMOSL3_246 over most of the rest of the globe in terms of correlations.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"76 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":"126202423","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.2015.7326887
Jun Li, Fei Hu, Feng He, Liang Wu, Xiaohui Peng, Yayun Cheng, D. Zhu, Ke Chen
An accurate geolocation of the radio frequency interference (RFI) sources is significant to effectively switch off illegal transmitters. In this study, utilizing the sparse property of RFI in the observed scene, a super-resolution RFI localization method based on compressive sensing is presented in synthetic aperture interferometric radiometer (SAIR). Numerical results show the presented method can achieve an super-resolution RFI localization even when there are some missing data due to correlator or receiver failure.
{"title":"Super-resolution RFI localization with compressive sensing in synthetic aperture interferometric radiometers","authors":"Jun Li, Fei Hu, Feng He, Liang Wu, Xiaohui Peng, Yayun Cheng, D. Zhu, Ke Chen","doi":"10.1109/IGARSS.2015.7326887","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326887","url":null,"abstract":"An accurate geolocation of the radio frequency interference (RFI) sources is significant to effectively switch off illegal transmitters. In this study, utilizing the sparse property of RFI in the observed scene, a super-resolution RFI localization method based on compressive sensing is presented in synthetic aperture interferometric radiometer (SAIR). Numerical results show the presented method can achieve an super-resolution RFI localization even when there are some missing data due to correlator or receiver failure.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"63 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":"126211454","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.2015.7326096
Xiaofeng Ai, Yongzhen Li, D. Feng, F. Zhao, S. Xiao
Feature extraction and recognition of wobbling targets are very important in spatial target surveillance. It has been shown that the scattering centers are slipping on the edge of the rotational symmetry target with the target micro-motion according to the electromagnetic scattering theory and electromagnetic computation analysis. Based on the slippery scattering center model, the micro-motion model and high-range resolution profile (HRRP) model of a wobbling rotational symmetry cone-shaped target are introduced, and the observed HRRP sequence is used to construct a time-range distribution matrix, then a estimation method of the wobbling period is proposed based on time-range distribution matrix correlation, which is validated by electromagnetic computation data and dynamic simulation.
{"title":"Feature extraction of wobbling rotational symmetry targets","authors":"Xiaofeng Ai, Yongzhen Li, D. Feng, F. Zhao, S. Xiao","doi":"10.1109/IGARSS.2015.7326096","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326096","url":null,"abstract":"Feature extraction and recognition of wobbling targets are very important in spatial target surveillance. It has been shown that the scattering centers are slipping on the edge of the rotational symmetry target with the target micro-motion according to the electromagnetic scattering theory and electromagnetic computation analysis. Based on the slippery scattering center model, the micro-motion model and high-range resolution profile (HRRP) model of a wobbling rotational symmetry cone-shaped target are introduced, and the observed HRRP sequence is used to construct a time-range distribution matrix, then a estimation method of the wobbling period is proposed based on time-range distribution matrix correlation, which is validated by electromagnetic computation data and dynamic simulation.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"1 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":"126219857","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.2015.7326768
A. Guerriero, V. W. Anelli, A. Pagliara, R. Nutricato, D. Nitti
Satellite remote sensing radar technologies provide powerful tools for geohazard monitoring and risk management at synoptic scale. In particular, advanced Multi-Temporal SAR Interferometric algorithms are capable to detect ground deformations and structural instabilities with millimetric precision, but impose strong requirements in terms of hardware re-sources. Recent advances in GPU computing and programming hold promise for time efficient implementation of imaging algorithms, thus enhancing the development of advanced Emergency Management Services based on Earth Observation technologies. In this study, a preliminary assessment of the potentials of GPU processing is carried out, by comparing CPU (single- and multi-thread) and GPU implementations of InSAR time-consuming algorithm kernels. In particular, it is focused on the fine coregistration of SAR interferometric pairs, a crucial step in the interferogram generation process. Experimental results are discussed.
{"title":"Efficient implementation of InSAR time-consuming algorithm kernels on GPU environment","authors":"A. Guerriero, V. W. Anelli, A. Pagliara, R. Nutricato, D. Nitti","doi":"10.1109/IGARSS.2015.7326768","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326768","url":null,"abstract":"Satellite remote sensing radar technologies provide powerful tools for geohazard monitoring and risk management at synoptic scale. In particular, advanced Multi-Temporal SAR Interferometric algorithms are capable to detect ground deformations and structural instabilities with millimetric precision, but impose strong requirements in terms of hardware re-sources. Recent advances in GPU computing and programming hold promise for time efficient implementation of imaging algorithms, thus enhancing the development of advanced Emergency Management Services based on Earth Observation technologies. In this study, a preliminary assessment of the potentials of GPU processing is carried out, by comparing CPU (single- and multi-thread) and GPU implementations of InSAR time-consuming algorithm kernels. In particular, it is focused on the fine coregistration of SAR interferometric pairs, a crucial step in the interferogram generation process. Experimental results are discussed.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"31 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":"126455025","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.2015.7326620
E. Haas, D. Moyer, G. Moy, F. D. Luccia, D. Kunkee
The Suomi National Polar-orbiting Partnership (SNPP) spacecraft's primary sensor is the Visible-Infrared Imaging Radiometer Suite (VIIRS) which launched on October 28, 2011. It has 22 total bands with 7 thermal emissive bands (TEBs), a high dynamic range monochromatic Day Night Band (DNB) and 14 reflective solar bands (RSBs). The TEB gain and noise performance is tracked on-orbit using an On-Board Calibrator BlackBody (OBCBB) as a thermal source. The TEBs view the OBCBB every scan allowing gain correction roughly every 1.7 seconds. Long term trending of the F factor (inversely proportional to gain) and Noise Equivalent delta Temperature (NEdT) allows the stability and uncertainty in the TEB thermal model to be evaluated. This paper will discuss the impacts of the thermal model uncertainties on the VIIRS calibration and how those impact the long term performance of VIIRS. It will also show the stability of the TEBs over 3 years on-orbit.
{"title":"SNPP VIIRS thermal emissive band performance after three years on-orbit","authors":"E. Haas, D. Moyer, G. Moy, F. D. Luccia, D. Kunkee","doi":"10.1109/IGARSS.2015.7326620","DOIUrl":"https://doi.org/10.1109/IGARSS.2015.7326620","url":null,"abstract":"The Suomi National Polar-orbiting Partnership (SNPP) spacecraft's primary sensor is the Visible-Infrared Imaging Radiometer Suite (VIIRS) which launched on October 28, 2011. It has 22 total bands with 7 thermal emissive bands (TEBs), a high dynamic range monochromatic Day Night Band (DNB) and 14 reflective solar bands (RSBs). The TEB gain and noise performance is tracked on-orbit using an On-Board Calibrator BlackBody (OBCBB) as a thermal source. The TEBs view the OBCBB every scan allowing gain correction roughly every 1.7 seconds. Long term trending of the F factor (inversely proportional to gain) and Noise Equivalent delta Temperature (NEdT) allows the stability and uncertainty in the TEB thermal model to be evaluated. This paper will discuss the impacts of the thermal model uncertainties on the VIIRS calibration and how those impact the long term performance of VIIRS. It will also show the stability of the TEBs over 3 years on-orbit.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"15 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":"126549912","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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