基于NPP/VIIRS夜光遥感影像的作业灯光围网渔船识别
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摘要
为对远洋灯光渔船作业信息进行实时动态监测,该研究基于可见光红外辐射仪(visible infrared imaging radiometer suite,VIIRS)夜光遥感影像,根据远洋灯光渔船作业时其集鱼灯灯光在VIIRS白天/夜晚波段(day/night band,DNB)影像上的辐射特征,采用峰值中值指数(spike median index,SMI)对灯光渔船与背景像元间的辐射差异进行拉伸,在此基础上设计了基于最大熵法(maximum entropy method,Max Ent)阈值分割以及局部峰值检测(local spike detection,LSD)的作业远洋灯光渔船识别算法,并采用2015年西北太平洋公海灯光围网渔场内作业渔船船位监控系统(vessel monitoring system,VMS)数据对该算法的识别精度进行检验。验证结果显示,该文提出的作业远洋灯光渔船自动识别算法对实际作业灯光渔船的识别精度在92%以上,可以满足远洋灯光渔船日常监测的需求,可为进一步评估远洋光诱渔业捕捞努力量、推进远洋光诱渔业信息化管理以及打击非法、未申报和无管制的(illegal,unregulated,unreported,IUU)捕捞活动提供技术支持。
Fishing data are the basement of fisheries science research,but currently the source of fishing data is extraordinarily scarce,and data quality is poor in some aspects.Satellite low light sensors can detect the light-fishing vessels at night,however,its application in pelagic fishery has been limited by the lack of an algorithm for extracting the location and brightness of operating pelagic light-fishing vessels.An examination of operating pelagic light-fishing vessels features in the day/night band(DNB)image,which was from the visible infrared imaging radiometer suite(VIIRS)on the Suomi National Polar-orbiting Partnership(NPP)satellite,indicated that the features were a list of nonadjacent bright spots.In order to identify the operating pelagic light-fishing vessels from VIIRS/DNB accurately,we designed a set of identification algorithm for operating pelagic light-fishing vessels according to the light radiation characteristics of its fishing gathering lamps in NPP/VIIRS low light image.Before applying the identification algorithm,a data pre-processing step was adopted through radiation stretch and noise reduction by adaptive Wiener filter to prepare the data for further analysis and use.A spike median index(SMI)was used to enlarge the radiation difference between operating pelagic light-fishing vessel pixels and background pixels.On the basis of this,an adaptive threshold segmentation method called the maximum entropy(Max Ent)method was used to extract the bright spot pixels,and generated a list of candidate operating pelagic light-fishing vessels detections.The candidate pixels were then filtered to remove the false identification bright spot pixels distributed near the operating pelagic light-fishing vessel pixels,and illuminated by the high-power fishing gathering lamps by a local spike detection(LSD)algorithm.A validation study was conducted at a night with weak lunar illuminance on May 24,2015 which was selected randomly,using the vessel monitoring system(VMS)data of Chinese operating light-seiners vessels on the high seas of Northwest Pacific Ocean light seine fishing ground and the result of VIIRS/DNB image visual interpretation.The validation result showed that the identification algorithm detected 27 operating pelagic light-fishing vessels on the high seas of Northwest Pacific Ocean light seine fishing ground,and the number of operating pelagic light-fishing boats and their distribution were entirely consistent with the result of VIIRS/DNB image visual interpretation;the VMS data had the record of 25 operating pelagic light-fishing vessels among the total 27vessels,and their distribution was nearly the same with the result of identification algorithm and VIIRS/DNB image visual interpretation.The identification algorithm worked well when lunar illuminance was weak and its identification accuracy was above 92%.The identification algorithm not only avoided the subjectivity and uncertainty of certain threshold segmentation,but also removed the false identification bright spot pixels near the operating pelagic light-fishing vessel pixels,which were illuminated by the high-power fishing gathering lamps.Detection of operating pelagic light-fishing vessels based on VIIRS/DNB imaging data can provide up-to-date activity and change information of operating pelagic light-fishing vessels for pelagic light-fishing industry,which meets the need of fishing boat’s daily monitoring,and has a wide application prospect in fishing effort estimation,research of central fishing ground spatial-temporal distribution and change,and fishery forecast and management.
Fishing data are the basement of fisheries science research,but currently the source of fishing data is extraordinarily scarce,and data quality is poor in some aspects.Satellite low light sensors can detect the light-fishing vessels at night,however,its application in pelagic fishery has been limited by the lack of an algorithm for extracting the location and brightness of operating pelagic light-fishing vessels.An examination of operating pelagic light-fishing vessels features in the day/night band(DNB)image,which was from the visible infrared imaging radiometer suite(VIIRS)on the Suomi National Polar-orbiting Partnership(NPP)satellite,indicated that the features were a list of nonadjacent bright spots.In order to identify the operating pelagic light-fishing vessels from VIIRS/DNB accurately,we designed a set of identification algorithm for operating pelagic light-fishing vessels according to the light radiation characteristics of its fishing gathering lamps in NPP/VIIRS low light image.Before applying the identification algorithm,a data pre-processing step was adopted through radiation stretch and noise reduction by adaptive Wiener filter to prepare the data for further analysis and use.A spike median index(SMI)was used to enlarge the radiation difference between operating pelagic light-fishing vessel pixels and background pixels.On the basis of this,an adaptive threshold segmentation method called the maximum entropy(Max Ent)method was used to extract the bright spot pixels,and generated a list of candidate operating pelagic light-fishing vessels detections.The candidate pixels were then filtered to remove the false identification bright spot pixels distributed near the operating pelagic light-fishing vessel pixels,and illuminated by the high-power fishing gathering lamps by a local spike detection(LSD)algorithm.A validation study was conducted at a night with weak lunar illuminance on May 24,2015 which was selected randomly,using the vessel monitoring system(VMS)data of Chinese operating light-seiners vessels on the high seas of Northwest Pacific Ocean light seine fishing ground and the result of VIIRS/DNB image visual interpretation.The validation result showed that the identification algorithm detected 27 operating pelagic light-fishing vessels on the high seas of Northwest Pacific Ocean light seine fishing ground,and the number of operating pelagic light-fishing boats and their distribution were entirely consistent with the result of VIIRS/DNB image visual interpretation;the VMS data had the record of 25 operating pelagic light-fishing vessels among the total 27vessels,and their distribution was nearly the same with the result of identification algorithm and VIIRS/DNB image visual interpretation.The identification algorithm worked well when lunar illuminance was weak and its identification accuracy was above 92%.The identification algorithm not only avoided the subjectivity and uncertainty of certain threshold segmentation,but also removed the false identification bright spot pixels near the operating pelagic light-fishing vessel pixels,which were illuminated by the high-power fishing gathering lamps.Detection of operating pelagic light-fishing vessels based on VIIRS/DNB imaging data can provide up-to-date activity and change information of operating pelagic light-fishing vessels for pelagic light-fishing industry,which meets the need of fishing boat’s daily monitoring,and has a wide application prospect in fishing effort estimation,research of central fishing ground spatial-temporal distribution and change,and fishery forecast and management.
引文
[1]侍炯,钱卫国,杨卢明.鲐鱼灯光围网渔船合适作业间距的理论研究[J].南方水产科学,2013,9(4):82-86.Shi Jiong,Qian Weiguo,Yang Luming.The theoretical study on suitable spacing between of light purse seine vessels for chub mackerel(Scomber japonicus)[J].South China Fisheries Science,2013,9(4):82-86.(in Chinese with English abstract)
[2]Croft T A.Nighttime Images of the Earth from Space[J].Scientific American,1978,239(1):86-98.
[3]Cho K,Ito R,Shimoda H,et al.Fishing fleet lights and sea surface temperature distribution observed by DMSP/OLSsensor[J].International Journal of Remote Sensing,1999,20(1):3-9.
[4]Rodhouse P G,Elvidge C D,Trathan P N.Remote sensing of the global light-fishing fleet:an analysis of interactions with oceanography,other fisheries and predators[J].Advances in Marine Biology,2001,39(1):261-278.
[5]Waluda C M,Trathan P N,Elvidge C D,et al.Throwing light on straddling stocks of Illex argentinus:assessing fishing intensity with satellite imagery[J].Canadian Journal of Fisheries&Aquatic Sciences,2002,59(4):592-596.
[6]Maxwell M R,Henry A,Elvidge C D,et al.Fishery dynamics of the California market squid(Loligo opalescens),as measured by satellite remote sensing[J].Fishery Bulletin,2004,102(4):661-670.
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[8]Kiyofuji H,Saitoh S I.Use of nighttime visible images to detect Japanese common squid Todarodes pacificus fishing areas and potential migration routes in the Sea of Japan[J].Marine Ecology Progress,2004,276(1):173-186.
[9]Waluda C M,Griffiths H J,Rodhouse P G.Remotely sensed spatial dynamics of the Illex argentinus fishery,Southwest Atlantic[J].Fisheries Research,2008,91(3):196-202.
[10]程田飞.基于DMSP/OLS夜间灯光数据的西北太平洋鱿钓渔船只数量估算[D].上海:上海海洋大学,2013.Cheng Tianfei.An Estimation of the Number of Squid Jigging Vessels in the Northwest Pacific Ocean Using DMSP/OLS night-time emission data[D].Shanghai:Shanghai Ocean University,2013.(in Chinese with English abstract)
[11]Cheng T,Zhou W.Xu.,Fan W.Estimation of Fishing Vessel Numbers Close to the Terminator in the Pacific Northwest Using OLS/DMSP Data.Geo-Spatial Knowledge and Intelligence.GRMSE 2016[C].Singapore:Springer,2017:321-327
[12]杨眉,王世新,周艺,等.DMSP/OLS夜间灯光数据应用研究综述[J].遥感技术与应用,2011,26(1):45-51.Yang Mei,Wang Shixin,Zhou Yi,et al.Review on applications of DMSP/OLS night-time emissions data[J].Remote Sensing Technology and Application,2011,26(1):45-51.(in Chinese with English abstract)
[13]方荀.VIIRS白天/夜晚波段数据应用概况[J].科技创新导报,2015,12(12):42-43.
[14]李德仁,李熙.论夜光遥感数据挖掘[J].测绘学报,2015,44(6):591-601.Li Deren,Li Xi.An overview on data mining of nighttime light remote sensing[J].Acta Geodaetica et Cartographica Sinica,2015,44(6):591-601.(in Chinese with English abstract)
[15]Elvidge C D,Baugh K E,Zhizhin M,et al.Why VIIRS data are superior to DMSP for mapping nighttime lights[J].Proceedings of the Asia-Pacific Advanced Network,2013,35(7):62-69.
[16]Elvidge C D,Zhizhin M,Baugh K,et al.Automatic boat identification system for VIIRS low light imaging data[J].Remote Sensing,2015,7(3):3020-3036.
[17]郭刚刚,樊伟,张胜茂,等.船位监控系统数据挖掘与应用研究进展[J].海洋渔业,2016,38(2):217-224.Guo Ganggang,Fan Wei,Zhang Shengmao,et al.Advances in mining and application of vessel monitoring system data[J].Marine Fisheries,2016,38(2):217-224.(in Chinese with English abstract)
[18]夏浪,毛克彪,马莹,等.基于可见光红外成像辐射仪数据的地表温度反演[J].农业工程学报,2014,30(8):109-116.Xia Lang,Mao Kebiao,Ma Ying,et al.Retrieval land surface temperature from visible infrared imager radiometer suite data[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(8):109-116.(in Chinese with English abstract)
[19]Miller S D,Straka W,Mills S P,et al.Illuminating the capabilities of the suomi national polar-orbiting partnership(NPP)visible infrared imaging radiometer suite(VIIRS)day/night band[J].Remote Sensing,2013,5(12):6717-6766.
[20]Shi K,Yu B,Huang Y,et al.Evaluating the ability of NPP/VIIRS nighttime light data to estimate the gross domestic product and the electric power consumption of China at multiple scales:a comparison with DMSP-OLSdata[J].Remote Sensing,2014,6(2):1705-1724.
[21]Cao C,Xiong J,Blonski S,et al.Suomi NPP VIIRS sensor data record verification,validation,and long‐term performance monitoring[J].Journal of Geophysical Research Atmospheres,2013,118(11):664-678.
[22]Lim J S.Two-dimensional signal and image processing[M].Englewood Cliffs:Prentice Hall,1990.
[23]梅安新,彭望琭,秦其明,等.遥感导论[M].北京:高等教育出版社,2001.
[24]吴谨,李娟,刘成云,等.基于最大熵的灰度阈值选取方法[J].武汉科技大学学报:自然科学版,2004,27(1):58-60.Wu Jin,Li Juan,Liu Chengyun,et al.A method for gray-level threshold selection based on maximum entropy[J].Journal of Wuhan University of Science and Technology(Natural Science Edition),2004,27(1):58-60.(in Chinese with English abstract)
[25]田有文,程怡,王小奇,等.基于高光谱成像的苹果虫害检测特征向量的选取[J].农业工程学报,2014,30(12):132-139.Tian Youwen,Cheng Yi,Wang Xiaoqi,et al.Feature vectors determination for pest detection on apples based on hyperspectral imaging[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(12):132-139.(in Chinese with English abstract)
[26]张晓东,毛罕平,左志宇,等.基于多光谱视觉技术的油菜水分胁迫诊断[J].农业工程学报,2011,27(3):152-157.Zhang Xiaodong,Mao Hanping,Zuo Zhiyu,et al.Nondestructive testing method for rape water stress based on multi-spectral vision[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2011,27(3):152-157.(in Chinese with English abstract)
[27]伦向敏,侯一民.运用迭代最大熵算法选取最佳图像分割阈值[J].计算机工程与设计,2015,36(5):1265-1268.Lun Xiangming,Hou Yimin.Optimal threshold selection for image segmentation utilizing entropy-max algorithm[J].Computer Engineering and Design,2015,36(5):1265-1268.(in Chinese with English abstract)
[28]Kopp T J,Thomas W,Heidinger A K,et al.The VIIRS cloud mask:Progress in the first year of S‐NPP toward a common cloud detection scheme[J].Journal of Geophysical Research Atmospheres,2014,119(5):2441-2456.
[29]张胜茂,崔雪森,伍玉梅,等.基于北斗卫星船位数据分析象山拖网捕捞时空特征[J].农业工程学报,2015,31(7):151-156.Zhang Shengmao,Cui Xunsen,Wu Yumei,et al.Analyzing space-time characteristics of Xiangshan trawling based on Beidou vessel monitoring system data[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(7):151-156.(in Chinese with English abstract)
[30]Liu Y,Saitoh S I,Hirawake T,et al.Detection of Squid and Pacific Saury fishing vessels around Japan using VIIRSDay/Night Band image[J].Proceeding of the Asia-Pacific Advanced Network,2015,39(3):28-39.
[31]Straka W I,Seaman C,Baugh K,et al.Utilization of the suomi national polar-orbiting partnership(npp)visible infrared imaging radiometer suite(viirs)day/night band for arctic ship tracking and fisheries management[J].remote sensing,2015,7(12):971-989.
[2]Croft T A.Nighttime Images of the Earth from Space[J].Scientific American,1978,239(1):86-98.
[3]Cho K,Ito R,Shimoda H,et al.Fishing fleet lights and sea surface temperature distribution observed by DMSP/OLSsensor[J].International Journal of Remote Sensing,1999,20(1):3-9.
[4]Rodhouse P G,Elvidge C D,Trathan P N.Remote sensing of the global light-fishing fleet:an analysis of interactions with oceanography,other fisheries and predators[J].Advances in Marine Biology,2001,39(1):261-278.
[5]Waluda C M,Trathan P N,Elvidge C D,et al.Throwing light on straddling stocks of Illex argentinus:assessing fishing intensity with satellite imagery[J].Canadian Journal of Fisheries&Aquatic Sciences,2002,59(4):592-596.
[6]Maxwell M R,Henry A,Elvidge C D,et al.Fishery dynamics of the California market squid(Loligo opalescens),as measured by satellite remote sensing[J].Fishery Bulletin,2004,102(4):661-670.
[7]Waluda C M,Yamashiro C,Elvidge C D,et al.Quantifying light-fishing for Dosidicus gigas,in the eastern Pacific using satellite remote sensing[J].Remote Sensing of Environment,2004,91(2):129-133.
[8]Kiyofuji H,Saitoh S I.Use of nighttime visible images to detect Japanese common squid Todarodes pacificus fishing areas and potential migration routes in the Sea of Japan[J].Marine Ecology Progress,2004,276(1):173-186.
[9]Waluda C M,Griffiths H J,Rodhouse P G.Remotely sensed spatial dynamics of the Illex argentinus fishery,Southwest Atlantic[J].Fisheries Research,2008,91(3):196-202.
[10]程田飞.基于DMSP/OLS夜间灯光数据的西北太平洋鱿钓渔船只数量估算[D].上海:上海海洋大学,2013.Cheng Tianfei.An Estimation of the Number of Squid Jigging Vessels in the Northwest Pacific Ocean Using DMSP/OLS night-time emission data[D].Shanghai:Shanghai Ocean University,2013.(in Chinese with English abstract)
[11]Cheng T,Zhou W.Xu.,Fan W.Estimation of Fishing Vessel Numbers Close to the Terminator in the Pacific Northwest Using OLS/DMSP Data.Geo-Spatial Knowledge and Intelligence.GRMSE 2016[C].Singapore:Springer,2017:321-327
[12]杨眉,王世新,周艺,等.DMSP/OLS夜间灯光数据应用研究综述[J].遥感技术与应用,2011,26(1):45-51.Yang Mei,Wang Shixin,Zhou Yi,et al.Review on applications of DMSP/OLS night-time emissions data[J].Remote Sensing Technology and Application,2011,26(1):45-51.(in Chinese with English abstract)
[13]方荀.VIIRS白天/夜晚波段数据应用概况[J].科技创新导报,2015,12(12):42-43.
[14]李德仁,李熙.论夜光遥感数据挖掘[J].测绘学报,2015,44(6):591-601.Li Deren,Li Xi.An overview on data mining of nighttime light remote sensing[J].Acta Geodaetica et Cartographica Sinica,2015,44(6):591-601.(in Chinese with English abstract)
[15]Elvidge C D,Baugh K E,Zhizhin M,et al.Why VIIRS data are superior to DMSP for mapping nighttime lights[J].Proceedings of the Asia-Pacific Advanced Network,2013,35(7):62-69.
[16]Elvidge C D,Zhizhin M,Baugh K,et al.Automatic boat identification system for VIIRS low light imaging data[J].Remote Sensing,2015,7(3):3020-3036.
[17]郭刚刚,樊伟,张胜茂,等.船位监控系统数据挖掘与应用研究进展[J].海洋渔业,2016,38(2):217-224.Guo Ganggang,Fan Wei,Zhang Shengmao,et al.Advances in mining and application of vessel monitoring system data[J].Marine Fisheries,2016,38(2):217-224.(in Chinese with English abstract)
[18]夏浪,毛克彪,马莹,等.基于可见光红外成像辐射仪数据的地表温度反演[J].农业工程学报,2014,30(8):109-116.Xia Lang,Mao Kebiao,Ma Ying,et al.Retrieval land surface temperature from visible infrared imager radiometer suite data[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(8):109-116.(in Chinese with English abstract)
[19]Miller S D,Straka W,Mills S P,et al.Illuminating the capabilities of the suomi national polar-orbiting partnership(NPP)visible infrared imaging radiometer suite(VIIRS)day/night band[J].Remote Sensing,2013,5(12):6717-6766.
[20]Shi K,Yu B,Huang Y,et al.Evaluating the ability of NPP/VIIRS nighttime light data to estimate the gross domestic product and the electric power consumption of China at multiple scales:a comparison with DMSP-OLSdata[J].Remote Sensing,2014,6(2):1705-1724.
[21]Cao C,Xiong J,Blonski S,et al.Suomi NPP VIIRS sensor data record verification,validation,and long‐term performance monitoring[J].Journal of Geophysical Research Atmospheres,2013,118(11):664-678.
[22]Lim J S.Two-dimensional signal and image processing[M].Englewood Cliffs:Prentice Hall,1990.
[23]梅安新,彭望琭,秦其明,等.遥感导论[M].北京:高等教育出版社,2001.
[24]吴谨,李娟,刘成云,等.基于最大熵的灰度阈值选取方法[J].武汉科技大学学报:自然科学版,2004,27(1):58-60.Wu Jin,Li Juan,Liu Chengyun,et al.A method for gray-level threshold selection based on maximum entropy[J].Journal of Wuhan University of Science and Technology(Natural Science Edition),2004,27(1):58-60.(in Chinese with English abstract)
[25]田有文,程怡,王小奇,等.基于高光谱成像的苹果虫害检测特征向量的选取[J].农业工程学报,2014,30(12):132-139.Tian Youwen,Cheng Yi,Wang Xiaoqi,et al.Feature vectors determination for pest detection on apples based on hyperspectral imaging[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(12):132-139.(in Chinese with English abstract)
[26]张晓东,毛罕平,左志宇,等.基于多光谱视觉技术的油菜水分胁迫诊断[J].农业工程学报,2011,27(3):152-157.Zhang Xiaodong,Mao Hanping,Zuo Zhiyu,et al.Nondestructive testing method for rape water stress based on multi-spectral vision[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2011,27(3):152-157.(in Chinese with English abstract)
[27]伦向敏,侯一民.运用迭代最大熵算法选取最佳图像分割阈值[J].计算机工程与设计,2015,36(5):1265-1268.Lun Xiangming,Hou Yimin.Optimal threshold selection for image segmentation utilizing entropy-max algorithm[J].Computer Engineering and Design,2015,36(5):1265-1268.(in Chinese with English abstract)
[28]Kopp T J,Thomas W,Heidinger A K,et al.The VIIRS cloud mask:Progress in the first year of S‐NPP toward a common cloud detection scheme[J].Journal of Geophysical Research Atmospheres,2014,119(5):2441-2456.
[29]张胜茂,崔雪森,伍玉梅,等.基于北斗卫星船位数据分析象山拖网捕捞时空特征[J].农业工程学报,2015,31(7):151-156.Zhang Shengmao,Cui Xunsen,Wu Yumei,et al.Analyzing space-time characteristics of Xiangshan trawling based on Beidou vessel monitoring system data[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(7):151-156.(in Chinese with English abstract)
[30]Liu Y,Saitoh S I,Hirawake T,et al.Detection of Squid and Pacific Saury fishing vessels around Japan using VIIRSDay/Night Band image[J].Proceeding of the Asia-Pacific Advanced Network,2015,39(3):28-39.
[31]Straka W I,Seaman C,Baugh K,et al.Utilization of the suomi national polar-orbiting partnership(npp)visible infrared imaging radiometer suite(viirs)day/night band for arctic ship tracking and fisheries management[J].remote sensing,2015,7(12):971-989.