Pub Date : 2010-07-25DOI: 10.1109/IGARSS.2010.5650060
Reza Shirvany, M. Chabert, J. Tourneret
The degree of polarization (DoP) has long been recognized as one of the most important parameters characterizing partially polarized electromagnetic waves. This parameter can be effectively used to describe the information content of polarimetric images collected by synthetic aperture radar (SAR) systems. Estimation of DoP is standardly performed using four measurements. In SAR compact polarimetry (CP), however, only two measurements are available. In this paper, we develop maximum likelihood estimators of the DoP, in SAR CP modes, based on only two intensity images. We evaluate and compare the performance of these estimators for different CP modes on RADARSAT-2 polarimetric data, over various terrain types such as urban, vegetation, and ocean.
{"title":"Estimation of the degree of polarization in compact polarimetry","authors":"Reza Shirvany, M. Chabert, J. Tourneret","doi":"10.1109/IGARSS.2010.5650060","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5650060","url":null,"abstract":"The degree of polarization (DoP) has long been recognized as one of the most important parameters characterizing partially polarized electromagnetic waves. This parameter can be effectively used to describe the information content of polarimetric images collected by synthetic aperture radar (SAR) systems. Estimation of DoP is standardly performed using four measurements. In SAR compact polarimetry (CP), however, only two measurements are available. In this paper, we develop maximum likelihood estimators of the DoP, in SAR CP modes, based on only two intensity images. We evaluate and compare the performance of these estimators for different CP modes on RADARSAT-2 polarimetric data, over various terrain types such as urban, vegetation, and ocean.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116339066","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5652440
H. Wakabayashi, S. Sakai
The objective of this research is mainly in estimating sea ice concentration from Phased-Array L-band SAR (PALSAR) polarimetric data. This paper shows the results of estimating sea ice concentration from PALSAR data acquired from 2008 to 2010. The AMSR-E sea ice concentration data are also used to verify the result of sea ice concentration derived from PALSAR data. The difference in two sea ice concentrations was found especially in AMSR-E low concentration area. The high resolution backscattering and scattering entropy images give us an idea that there is some difficulty in AMSR-E to detect thin sea ice in the Sea of Okhotsk.
{"title":"Estimation of sea ice concentration in the Sea of Okhotsk using PALSAR polarimetric data","authors":"H. Wakabayashi, S. Sakai","doi":"10.1109/IGARSS.2010.5652440","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5652440","url":null,"abstract":"The objective of this research is mainly in estimating sea ice concentration from Phased-Array L-band SAR (PALSAR) polarimetric data. This paper shows the results of estimating sea ice concentration from PALSAR data acquired from 2008 to 2010. The AMSR-E sea ice concentration data are also used to verify the result of sea ice concentration derived from PALSAR data. The difference in two sea ice concentrations was found especially in AMSR-E low concentration area. The high resolution backscattering and scattering entropy images give us an idea that there is some difficulty in AMSR-E to detect thin sea ice in the Sea of Okhotsk.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114695000","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5649096
M. Even, A. Schunert, K. Schulz, U. Soergel
The PSInSAR technique, invented by Ferretti et. al. [1], [2], [3] ten years ago, meanwhile has proven it's capability for very precise measurement of surface deformations. To achieve this, the influence of the atmospheric phase screen (APS) has to be removed. We investigated the APS for two series of TerraSAR-X high resolution spotlight data of a scene in Bavaria. Our approach was to consider the APS as composed of a phase ramp, a part stratified with height and a turbulent component. We estimated the turbulent component via kriging. The variograms show for short distances a regime which is not visible for lower resolutions. In this paper we discuss the choice of appropriate variogram models with respect to our data.
{"title":"Atmospheric phase screen-estimation for PSInSAR applied to TerraSAR-X high resolution spotlight-data","authors":"M. Even, A. Schunert, K. Schulz, U. Soergel","doi":"10.1109/IGARSS.2010.5649096","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5649096","url":null,"abstract":"The PSInSAR technique, invented by Ferretti et. al. [1], [2], [3] ten years ago, meanwhile has proven it's capability for very precise measurement of surface deformations. To achieve this, the influence of the atmospheric phase screen (APS) has to be removed. We investigated the APS for two series of TerraSAR-X high resolution spotlight data of a scene in Bavaria. Our approach was to consider the APS as composed of a phase ramp, a part stratified with height and a turbulent component. We estimated the turbulent component via kriging. The variograms show for short distances a regime which is not visible for lower resolutions. In this paper we discuss the choice of appropriate variogram models with respect to our data.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124445621","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5651878
M. Lyons, S. Phinn, C. Roelfsema
Seagrass ecosystems are well studied and seagrass is recognised as a vital contributor to overall ecosystem health and productivity. However, a significant gap in knowledge exists in terms of the large scale temporal and spatial dynamics of cover level and distribution of seagrass communities. Remotely sensed satellite imagery offers a means to map seagrass cover and distribution over large temporal and spatial scales. At present, no operational methods have been produced to map seagrass on large spatio-temporal scales (> 100km2). This study presents a combined per-pixel/object-based method to rapidly map seagrass cover and distribution from a full Landsat archive, from 1972–2010 (MSS, TM and ETM+), with no in-situ data and at accuracies as good or better than existing mapping methods. The products provide management agencies with a baseline assessment as well as the capacity to continue to map seagrass distribution and predict changes in the future.
{"title":"Long term monitoring of seagrass distribution in Moreton Bay, Australia, from 1972–2010 using Landsat MSS, TM, ETM+","authors":"M. Lyons, S. Phinn, C. Roelfsema","doi":"10.1109/IGARSS.2010.5651878","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5651878","url":null,"abstract":"Seagrass ecosystems are well studied and seagrass is recognised as a vital contributor to overall ecosystem health and productivity. However, a significant gap in knowledge exists in terms of the large scale temporal and spatial dynamics of cover level and distribution of seagrass communities. Remotely sensed satellite imagery offers a means to map seagrass cover and distribution over large temporal and spatial scales. At present, no operational methods have been produced to map seagrass on large spatio-temporal scales (> 100km2). This study presents a combined per-pixel/object-based method to rapidly map seagrass cover and distribution from a full Landsat archive, from 1972–2010 (MSS, TM and ETM+), with no in-situ data and at accuracies as good or better than existing mapping methods. The products provide management agencies with a baseline assessment as well as the capacity to continue to map seagrass distribution and predict changes in the future.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124474096","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5650550
M. Matsuoka, S. Koshimura, N. Nojima
In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper introduces a likelihood function to estimate severe damage ratio by earthquakes on the basis of dataset from JERS-1/SAR (L-band SAR) images observed the 1995 Kobe earthquake and its detailed ground truth data. The model is applied to JERS-1/SAR images taken over the tsunami affected areas by the 1993 Hokkaido Nansei-oki, Japan earthquake.
{"title":"Estimation of building damage ratio due to earthquakes and tsunamis using satellite SAR imagery","authors":"M. Matsuoka, S. Koshimura, N. Nojima","doi":"10.1109/IGARSS.2010.5650550","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5650550","url":null,"abstract":"In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper introduces a likelihood function to estimate severe damage ratio by earthquakes on the basis of dataset from JERS-1/SAR (L-band SAR) images observed the 1995 Kobe earthquake and its detailed ground truth data. The model is applied to JERS-1/SAR images taken over the tsunami affected areas by the 1993 Hokkaido Nansei-oki, Japan earthquake.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127878912","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5650687
C. Walker, M. Liemohn, C. Parkinson
Due to the nature of observations taken by planetary spacecraft, many surface and atmospheric studies have been performed at the icy moons of the outer planets, which have left the many seemingly complex interior processes in these bodies left unexplored and unexplained. It is notably difficult to access the interior regions in which planetary formation and dynamics take place. This paper presents the possibility that radar measurements could contribute to the understanding of interior structure, particularly that of Enceladus, the small but notably dynamic icy moon of Saturn. The application of such radar may lead to discoveries concerning formation mechanisms and surface processes. Additionally, radar sounding will contribute measurements that aid in diagnosing the dynamics system at work in the subsurface - perhaps most notably, the source reservoir and/or dynamics of the observed water plume at the moon's south pole, in addition the moon's role as a whole in the Saturnian system.
{"title":"On radar sounding applications for Enceladean ice","authors":"C. Walker, M. Liemohn, C. Parkinson","doi":"10.1109/IGARSS.2010.5650687","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5650687","url":null,"abstract":"Due to the nature of observations taken by planetary spacecraft, many surface and atmospheric studies have been performed at the icy moons of the outer planets, which have left the many seemingly complex interior processes in these bodies left unexplored and unexplained. It is notably difficult to access the interior regions in which planetary formation and dynamics take place. This paper presents the possibility that radar measurements could contribute to the understanding of interior structure, particularly that of Enceladus, the small but notably dynamic icy moon of Saturn. The application of such radar may lead to discoveries concerning formation mechanisms and surface processes. Additionally, radar sounding will contribute measurements that aid in diagnosing the dynamics system at work in the subsurface - perhaps most notably, the source reservoir and/or dynamics of the observed water plume at the moon's south pole, in addition the moon's role as a whole in the Saturnian system.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126247685","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5650966
Wenbin Yi, Yunhao Chen, Hong Tang, L. Deng
We introduce a semi-automated algorithm to extract urban road from high-resolution RS image using the Probabilistic Topic Models. First of all, an image collection is generated from a high-resolution image by partitioning it into densely overlapped sub-images. The image collection is divided into two subsets, i.e., training images and testing images. The training images are used to estimate the number of topics, and to learn topic models. The training images are densely overlapped and are folded in using the learned topics to make sure that every pixel in each document is allocated to a topic label. Therefore, every pixel in the initial large image might be allocated multiple topic labels since it might belong to multiple sub-images. By selecting the road segments samples, several cluster centers will be assumed as labels of road objects. The semantic information can improve the extraction accuracy of road segments. The central lines of the road segments will be extracted basing on some image filter algorithms and Hough transform. Experimental results over EROS-B images show that road segments can be effectively detected by the proposed algorithm and an initial road network can be formed
{"title":"Experimental research on urban road extraction from high-resolution RS images using Probabilistic Topic Models","authors":"Wenbin Yi, Yunhao Chen, Hong Tang, L. Deng","doi":"10.1109/IGARSS.2010.5650966","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5650966","url":null,"abstract":"We introduce a semi-automated algorithm to extract urban road from high-resolution RS image using the Probabilistic Topic Models. First of all, an image collection is generated from a high-resolution image by partitioning it into densely overlapped sub-images. The image collection is divided into two subsets, i.e., training images and testing images. The training images are used to estimate the number of topics, and to learn topic models. The training images are densely overlapped and are folded in using the learned topics to make sure that every pixel in each document is allocated to a topic label. Therefore, every pixel in the initial large image might be allocated multiple topic labels since it might belong to multiple sub-images. By selecting the road segments samples, several cluster centers will be assumed as labels of road objects. The semantic information can improve the extraction accuracy of road segments. The central lines of the road segments will be extracted basing on some image filter algorithms and Hough transform. Experimental results over EROS-B images show that road segments can be effectively detected by the proposed algorithm and an initial road network can be formed","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126462363","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5653924
W. Blake, Lei Shi, J. Meisel, C. Allen, S. Gogineni
During NASA's Operation Ice Bridge a gridded survey was flown over Pine Island Glacier (PIG). This survey was a finer grid than previously flown over this area. The data collected confirm that the majority of the ice at the bottom of PIG is below sea level which could be a major cause in the speed-up of the ice flow in that area. These data can be used in flow rate calculations and to the mass balance in that area.
{"title":"Airborne 3D basal DEM and ice thickness map of Pine Island Glacier","authors":"W. Blake, Lei Shi, J. Meisel, C. Allen, S. Gogineni","doi":"10.1109/IGARSS.2010.5653924","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5653924","url":null,"abstract":"During NASA's Operation Ice Bridge a gridded survey was flown over Pine Island Glacier (PIG). This survey was a finer grid than previously flown over this area. The data collected confirm that the majority of the ice at the bottom of PIG is below sea level which could be a major cause in the speed-up of the ice flow in that area. These data can be used in flow rate calculations and to the mass balance in that area.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126478927","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5653086
T. Ikuma, M. Naraghi-Pour, T. Lewis
Raw data collected by synthetic aperture radar (SAR) is commonly assumed to be uncorrelated and with a zero-mean Gaussian distribution. In this paper, we show—both analytically and numerically—that the range-wise inverse Fourier transform of the dechirp-on-receive circular SAR data exhibits significant correlation in the azimuth direction. Moreover, we show that a block adaptive autoregressive model well represents the transformed SAR data.
{"title":"Autoregressive modeling of dechirped spotlight-mode sar rawdata in transform domain","authors":"T. Ikuma, M. Naraghi-Pour, T. Lewis","doi":"10.1109/IGARSS.2010.5653086","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5653086","url":null,"abstract":"Raw data collected by synthetic aperture radar (SAR) is commonly assumed to be uncorrelated and with a zero-mean Gaussian distribution. In this paper, we show—both analytically and numerically—that the range-wise inverse Fourier transform of the dechirp-on-receive circular SAR data exhibits significant correlation in the azimuth direction. Moreover, we show that a block adaptive autoregressive model well represents the transformed SAR data.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125461114","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 : 2010-07-25DOI: 10.1109/IGARSS.2010.5652092
Sung-Hyun Kim, Nam-Won Moon, Yong-Hoon Kim
For the last few decades, microwave radiometers have played an important role in various remote sensing applications of the earth environment such as atmosphere, ocean and soil. Especially, various polarimetric emission for more accurate estimation. In general, the electromagnetic wave is represented as full Stoke parameters. [1] The Stoke parameters can be defined as the horizontal and vertical polarization for the first and second parameters, and the 45 degree linear and circular polarization for the third and forth parameters, respectively. [2] In this study, we developed the fully polarimetric radiometer to measure full Stokes parameter at 94GHz. For stable and high sensible Stokes parameters measurement, we implemented a wideband analog correlator and a total power type receiver with periodic calibration. In order to measure full Stokes parameters, it needs the calibration by using the additional polarized references. The fully polarimetric calibration standard is composed of a polarizing grid, a retardation plate, and reference sources. The characteristic of calibration standards was measured and evaluated.
{"title":"System design of W-band fully polarimetric radiometer for target identification","authors":"Sung-Hyun Kim, Nam-Won Moon, Yong-Hoon Kim","doi":"10.1109/IGARSS.2010.5652092","DOIUrl":"https://doi.org/10.1109/IGARSS.2010.5652092","url":null,"abstract":"For the last few decades, microwave radiometers have played an important role in various remote sensing applications of the earth environment such as atmosphere, ocean and soil. Especially, various polarimetric emission for more accurate estimation. In general, the electromagnetic wave is represented as full Stoke parameters. [1] The Stoke parameters can be defined as the horizontal and vertical polarization for the first and second parameters, and the 45 degree linear and circular polarization for the third and forth parameters, respectively. [2] In this study, we developed the fully polarimetric radiometer to measure full Stokes parameter at 94GHz. For stable and high sensible Stokes parameters measurement, we implemented a wideband analog correlator and a total power type receiver with periodic calibration. In order to measure full Stokes parameters, it needs the calibration by using the additional polarized references. The fully polarimetric calibration standard is composed of a polarizing grid, a retardation plate, and reference sources. The characteristic of calibration standards was measured and evaluated.","PeriodicalId":406785,"journal":{"name":"2010 IEEE International Geoscience and Remote Sensing Symposium","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125662176","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：