Pub Date : 2018-01-01DOI: 10.1109/IGARSS.2018.8517339
X. Shen, Z. Qiu, M. Bilal
{"title":"Validation of Modis Aerosol Optical Depth Over South China Sea","authors":"X. Shen, Z. Qiu, M. Bilal","doi":"10.1109/IGARSS.2018.8517339","DOIUrl":"https://doi.org/10.1109/IGARSS.2018.8517339","url":null,"abstract":"","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"18 1","pages":"9130-9133"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75690145","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 : 2017-12-04DOI: 10.1109/IGARSS.2017.8127129
S. Skrunes, C. Brekke, M. M. Espeseth
Synthetic aperture radar data acquired by the Radar Imaging Satellite (RISAT-1) over experimental oil spills is here investigated. One quad-polarization scene in the Fine Resolution Alternate Polarization Stripmap (FRS-2) mode is analyzed to evaluate the potential of using this mode for oil spill observation. Oil slicks of varying type and age are clearly detected in the HH and VV channels, with relatively high signal-to-noise ratios. The cross-polarization channel is not found useful due to its proximity to the noise floor and some processing issues in the received product. Only intensity-based multipolarization parameters can be extracted due to the incoherent data acquisition. The Total Copolarization Power and the Polarization Difference are found to have good detection capabilities, whereas the Copolarization Power Ratio and the Normalized Polarization Difference only show small indications of the slicks. Comparison between SAR data and coincident observations from aircraft show a correlation between enhanced SAR signatures and locations of thicker oil layers.
{"title":"Assessment of the RISAT-1 FRS-2 mode for oil spill observation","authors":"S. Skrunes, C. Brekke, M. M. Espeseth","doi":"10.1109/IGARSS.2017.8127129","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127129","url":null,"abstract":"Synthetic aperture radar data acquired by the Radar Imaging Satellite (RISAT-1) over experimental oil spills is here investigated. One quad-polarization scene in the Fine Resolution Alternate Polarization Stripmap (FRS-2) mode is analyzed to evaluate the potential of using this mode for oil spill observation. Oil slicks of varying type and age are clearly detected in the HH and VV channels, with relatively high signal-to-noise ratios. The cross-polarization channel is not found useful due to its proximity to the noise floor and some processing issues in the received product. Only intensity-based multipolarization parameters can be extracted due to the incoherent data acquisition. The Total Copolarization Power and the Polarization Difference are found to have good detection capabilities, whereas the Copolarization Power Ratio and the Normalized Polarization Difference only show small indications of the slicks. Comparison between SAR data and coincident observations from aircraft show a correlation between enhanced SAR signatures and locations of thicker oil layers.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"44 1","pages":"1024-1027"},"PeriodicalIF":0.0,"publicationDate":"2017-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79299761","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 : 2017-12-01DOI: 10.1109/IGARSS.2017.8127862
P. O’neill, S. Chan, R. Bindlish, T. Jackson, A. Colliander, R. Dunbar, Fan Chen, J. Piepmeier, S. Yueh, D. Entekhabi, M. Cosh, T. Caldwell, J. Walker, Xiaoling Wu, A. Berg, T. Rowlandson, A. Pacheco, H. Mcnairn, M. Thibeault, J. Martínez-Fernández, Á. González-Zamora, E. López-Baeza, F. Uldall, M. Seyfried, D. Bosch, P. Starks, C. H. Collins, J. Prueger, Z. Su, R. Velde, J. Asanuma, M. Palecki, E. Small, M. Zreda, J. Calvet, W. Crow, Y. Kerr
NASA's Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am/6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2–3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAP's radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core cal/val sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.
{"title":"Assessment of version 4 of the SMAP passive soil moisture standard product","authors":"P. O’neill, S. Chan, R. Bindlish, T. Jackson, A. Colliander, R. Dunbar, Fan Chen, J. Piepmeier, S. Yueh, D. Entekhabi, M. Cosh, T. Caldwell, J. Walker, Xiaoling Wu, A. Berg, T. Rowlandson, A. Pacheco, H. Mcnairn, M. Thibeault, J. Martínez-Fernández, Á. González-Zamora, E. López-Baeza, F. Uldall, M. Seyfried, D. Bosch, P. Starks, C. H. Collins, J. Prueger, Z. Su, R. Velde, J. Asanuma, M. Palecki, E. Small, M. Zreda, J. Calvet, W. Crow, Y. Kerr","doi":"10.1109/IGARSS.2017.8127862","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127862","url":null,"abstract":"NASA's Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am/6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2–3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAP's radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core cal/val sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"6 1","pages":"3941-3944"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80847452","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 : 2017-12-01DOI: 10.1109/IGARSS.2017.8127617
Tung-Yao Hsu, Yi Chang
Skipjack tuna (Katsuwonus pelamis) is the major target species in Taiwan pelagic purse-seine in the western and central Pacific Ocean with approximate 90% of catch rate in all harvested species. This study attempts to identify the habitat suitability index (HSI) for skipjack tuna in the western and central Pacific Ocean. Fishery data was processed for comparing with satellite data included sea surface temperature (SST), chlorophyll-a concentration (Chl-a), sea surface height (SSH), and sea surface salinity (SSS). In addition, SST and Chl-a satellite images were applied to oceanic frontal band detection that front gradient magnitudes were used for the HSI estimation. Preliminary results in this study revealed that HSI of skipjack tuna greater than 0.6 was confirmed, where SST and Chl-a front gradient ranged between 0.065 to 0.216 (°C/10km) and 0.003 to 0.005 (ratio/10km), respectively and SSH changed from −0.107 to 0.016 (m), SSS changed from 34.5 to 35.19(psu).
{"title":"Modeling the habitat suitability index of skipjack tuna (katsuwonus pelamis) in the western and central pacific ocean","authors":"Tung-Yao Hsu, Yi Chang","doi":"10.1109/IGARSS.2017.8127617","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127617","url":null,"abstract":"Skipjack tuna (Katsuwonus pelamis) is the major target species in Taiwan pelagic purse-seine in the western and central Pacific Ocean with approximate 90% of catch rate in all harvested species. This study attempts to identify the habitat suitability index (HSI) for skipjack tuna in the western and central Pacific Ocean. Fishery data was processed for comparing with satellite data included sea surface temperature (SST), chlorophyll-a concentration (Chl-a), sea surface height (SSH), and sea surface salinity (SSS). In addition, SST and Chl-a satellite images were applied to oceanic frontal band detection that front gradient magnitudes were used for the HSI estimation. Preliminary results in this study revealed that HSI of skipjack tuna greater than 0.6 was confirmed, where SST and Chl-a front gradient ranged between 0.065 to 0.216 (°C/10km) and 0.003 to 0.005 (ratio/10km), respectively and SSH changed from −0.107 to 0.016 (m), SSS changed from 34.5 to 35.19(psu).","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"54 1","pages":"2950-2953"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84186397","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 : 2017-12-01DOI: 10.1109/IGARSS.2017.8127484
R. Natsuaki, M. Ohki, Hiroto Nagai, T. Motohka, T. Tadono, M. Shimada, S. Suzuki
In 2016, the Advanced Land Observing Satellite-2 (ALOS-2, “DAICHI-2”) observed various disaster affected areas. Japan Aerospace Exploration Agency (JAXA) operated the emergency observation more than hundred times in the year. The Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard ALOS-2 contributed for detecting the disaster affected area, ground deformation and flood affected area. Especially for the ground deformation and damaged area detection caused by the devastating earthquakes in 2016, e.g., Kumamoto earthquakes in Japan and Kaikoura earthquake in New Zealand, researchers provided variable analytical results from ALOS-2 observation data. In this paper, some examples of the emergency observation results are presented.
{"title":"Performance of ALOS-2 PALSAR-2 for disaster response","authors":"R. Natsuaki, M. Ohki, Hiroto Nagai, T. Motohka, T. Tadono, M. Shimada, S. Suzuki","doi":"10.1109/IGARSS.2017.8127484","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127484","url":null,"abstract":"In 2016, the Advanced Land Observing Satellite-2 (ALOS-2, “DAICHI-2”) observed various disaster affected areas. Japan Aerospace Exploration Agency (JAXA) operated the emergency observation more than hundred times in the year. The Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard ALOS-2 contributed for detecting the disaster affected area, ground deformation and flood affected area. Especially for the ground deformation and damaged area detection caused by the devastating earthquakes in 2016, e.g., Kumamoto earthquakes in Japan and Kaikoura earthquake in New Zealand, researchers provided variable analytical results from ALOS-2 observation data. In this paper, some examples of the emergency observation results are presented.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"68 1","pages":"2434-2437"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77125812","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 : 2017-12-01DOI: 10.1109/IGARSS.2017.8127780
Jen-Han Yang, Yi Chang
Derelict fishing gear produced by oyster farming activities is being dispersed along the southwestern coast of Taiwan. The derelict gear fragments littering at the coastal areas and is responsible for ghost fishing being a type of marine pollution. To address this problem, the paper presents an experimental implementation of a method to localize radio-frequency identification tags in oyster farms for monitoring using drone technologies. The advantage of the proposed system is to provide a useful tool in analyzing identification of oyster rafts farming with less man power and time. The findings provide an initial feasibility study on combining radio-frequency identification system with drone technology to improve oyster farms management. In addition, this paper depicts the proposed system, shows the testing methodology and analyses some achieved performances in an experimental scenario.
{"title":"Feasibility study of RFID-Mounted drone application in management of oyster farms","authors":"Jen-Han Yang, Yi Chang","doi":"10.1109/IGARSS.2017.8127780","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127780","url":null,"abstract":"Derelict fishing gear produced by oyster farming activities is being dispersed along the southwestern coast of Taiwan. The derelict gear fragments littering at the coastal areas and is responsible for ghost fishing being a type of marine pollution. To address this problem, the paper presents an experimental implementation of a method to localize radio-frequency identification tags in oyster farms for monitoring using drone technologies. The advantage of the proposed system is to provide a useful tool in analyzing identification of oyster rafts farming with less man power and time. The findings provide an initial feasibility study on combining radio-frequency identification system with drone technology to improve oyster farms management. In addition, this paper depicts the proposed system, shows the testing methodology and analyses some achieved performances in an experimental scenario.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"1 1","pages":"3610-3613"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90612260","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 : 2017-10-01DOI: 10.1109/IGARSS.2017.8127518
W. Tang, A. Fore, S. Yueh, Tong Lee, A. Hayashi, A. Sanchez‐Franks, D. Baranowski
Sea surface salinity (SSS) retrieved from SMAP radiometer measurements is validated with in situ salinity measurements collected from Argo floats, tropical moored buoys and ship-based thermosalinograph (TSG) data. SMAP SSS achieved accuracy of 0.2 PSU on a monthly basis in comparison with Argo gridded data in the tropics and mid-latitudes. In tropical oceans, time series comparison of salinity measured at 1 m by moored buoys indicates that SMAP can track large salinity changes occurred within a month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and exclude erroneous jumps or drift in some real-time buoy data from assessment of satellite retrieval. The resulting SMAP-buoy matchup analysis leads to an average standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale; the average standard deviation reduced to 0.17 PSU and the correlation improved to 0.8 on monthly scale. SMAP L3 daily maps reveals salty water intrusion from the Arabian Sea into the Bay of Bengal during the Indian summer monsoon, consistent with the daily measurements collected from floats deployed during the Bay of Bengal Boundary Layer Experiment (BoBBLE) project field campaign. In the Mediterranean Sea, the spatial pattern of SSS from SMAP is confirmed by the ship-based TSG data.
{"title":"Validating SMAP SSS with in situ measurements","authors":"W. Tang, A. Fore, S. Yueh, Tong Lee, A. Hayashi, A. Sanchez‐Franks, D. Baranowski","doi":"10.1109/IGARSS.2017.8127518","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127518","url":null,"abstract":"Sea surface salinity (SSS) retrieved from SMAP radiometer measurements is validated with in situ salinity measurements collected from Argo floats, tropical moored buoys and ship-based thermosalinograph (TSG) data. SMAP SSS achieved accuracy of 0.2 PSU on a monthly basis in comparison with Argo gridded data in the tropics and mid-latitudes. In tropical oceans, time series comparison of salinity measured at 1 m by moored buoys indicates that SMAP can track large salinity changes occurred within a month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and exclude erroneous jumps or drift in some real-time buoy data from assessment of satellite retrieval. The resulting SMAP-buoy matchup analysis leads to an average standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale; the average standard deviation reduced to 0.17 PSU and the correlation improved to 0.8 on monthly scale. SMAP L3 daily maps reveals salty water intrusion from the Arabian Sea into the Bay of Bengal during the Indian summer monsoon, consistent with the daily measurements collected from floats deployed during the Bay of Bengal Boundary Layer Experiment (BoBBLE) project field campaign. In the Mediterranean Sea, the spatial pattern of SSS from SMAP is confirmed by the ship-based TSG data.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"190 1","pages":"2561-2564"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91537326","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 : 2017-07-28DOI: 10.1109/IGARSS.2017.8127090
B. Kellenberger, M. Volpi, D. Tuia
Illegal wildlife poaching poses one severe threat to the environment. Measures to stem poaching have only been with limited success, mainly due to efforts required to keep track of wildlife stock and animal tracking. Recent developments in remote sensing have led to low-cost Unmanned Aerial Vehicles (UAVs), facilitating quick and repeated image acquisitions over vast areas. In parallel, progress in object detection in computer vision yielded unprecedented performance improvements, partially attributable to algorithms like Convolutional Neural Networks (CNNs). We present an object detection method tailored to detect large animals in UAV images. We achieve a substantial increase in precision over a robust state-of-the-art model on a dataset acquired over the Kuzikus wildlife reserve park in Namibia. Furthermore, our model processes data at over 72 images per second, as opposed 3 for the baseline, allowing for real-time applications.
{"title":"Fast animal detection in UAV images using convolutional neural networks","authors":"B. Kellenberger, M. Volpi, D. Tuia","doi":"10.1109/IGARSS.2017.8127090","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127090","url":null,"abstract":"Illegal wildlife poaching poses one severe threat to the environment. Measures to stem poaching have only been with limited success, mainly due to efforts required to keep track of wildlife stock and animal tracking. Recent developments in remote sensing have led to low-cost Unmanned Aerial Vehicles (UAVs), facilitating quick and repeated image acquisitions over vast areas. In parallel, progress in object detection in computer vision yielded unprecedented performance improvements, partially attributable to algorithms like Convolutional Neural Networks (CNNs). We present an object detection method tailored to detect large animals in UAV images. We achieve a substantial increase in precision over a robust state-of-the-art model on a dataset acquired over the Kuzikus wildlife reserve park in Namibia. Furthermore, our model processes data at over 72 images per second, as opposed 3 for the baseline, allowing for real-time applications.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"7 1","pages":"866-869"},"PeriodicalIF":0.0,"publicationDate":"2017-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81856165","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 : 2017-07-28DOI: 10.1109/IGARSS.2017.8127384
Pasquale Iervolino, R. Guida, P. Lumsdon, J. Janoth, M. Clift, A. Minchella, P. Bianco
This paper presents a ship-detection study with Synthetic Aperture Radar (SAR) images acquired at two different frequencies: X- and C-band. The detection procedure relies on a novel algorithm based on the likelihood functions of both canonical ship target and sea clutter. Spaceborne images were acquired over the same area in the Solent Channel in UK at approximately the same time on the 7th June 2016. Here, datasets are compared in terms of probability of detection (PD), probability of false alarm (PFA) and Target-to-Clutter Ratio (TCR). Detection maps are validated with Automatic Identification System (AIS) data when available and preliminary results show a higher TCR for the X-band SAR image.
{"title":"Ship detection in SAR imagery: A comparison study","authors":"Pasquale Iervolino, R. Guida, P. Lumsdon, J. Janoth, M. Clift, A. Minchella, P. Bianco","doi":"10.1109/IGARSS.2017.8127384","DOIUrl":"https://doi.org/10.1109/IGARSS.2017.8127384","url":null,"abstract":"This paper presents a ship-detection study with Synthetic Aperture Radar (SAR) images acquired at two different frequencies: X- and C-band. The detection procedure relies on a novel algorithm based on the likelihood functions of both canonical ship target and sea clutter. Spaceborne images were acquired over the same area in the Solent Channel in UK at approximately the same time on the 7th June 2016. Here, datasets are compared in terms of probability of detection (PD), probability of false alarm (PFA) and Target-to-Clutter Ratio (TCR). Detection maps are validated with Automatic Identification System (AIS) data when available and preliminary results show a higher TCR for the X-band SAR image.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"107 1","pages":"2050-2053"},"PeriodicalIF":0.0,"publicationDate":"2017-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76530147","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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