地球科学进展 ›› 2023, Vol. 38 ›› Issue (5): 533 -550. doi: 10.11867/j.issn.1001-8166.2023.019

新学科·新技术·新发现 上一篇    

夜间星载微光成像仪在大气、海洋和环境领域的应用研究进展
农子琪 1( ), 黄鹏宇 1, 徐寒列 2, 胡秀清 2, 闵敏 1( )   
  1. 1.中山大学大气科学学院 南方海洋科学与工程广东省实验室(珠海)和广东省气候变化与自然灾害 重点实验室,广东 珠海 519082
    2.中国气象局中国遥感卫星辐射测量和定标重点开放实验室/ 国家卫星气象中心(国家空间天气监测预警中心),许健民气象卫星创新中心,北京 100081
  • 收稿日期:2022-11-24 修回日期:2023-03-27 出版日期:2023-05-10
  • 通讯作者: 闵敏 E-mail:nongzq@mail2.sysu.edu.cn;minm5@mail.sysu.edu.cn
  • 基金资助:
    国家自然科学基金项目“夜间微光大气辐射传输理论和建模研究”(42175086);“强对流初生特征的静止红外和极轨微波星座联合观测研究”(41975031)

Application and Research Progress on Satellite-based Low Light Imager Data in the Atmospheric, Marine, and Environmental Sciences at Night

Ziqi NONG 1( ), Pengyu HUANG 1, Hanlie XU 2, Xiuqing HU 2, Min MIN 1( )   

  1. 1.School of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University (Zhuhai), Zhuhai Guangdong 519082, China
    2.Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites and Innovation Center for FengYun Meteorological Satellite (FYSIC), National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China
  • Received:2022-11-24 Revised:2023-03-27 Online:2023-05-10 Published:2023-05-10
  • Contact: Min MIN E-mail:nongzq@mail2.sysu.edu.cn;minm5@mail.sysu.edu.cn
  • About author:NONG Ziqi (1997-), male, Baise City, Guangxi Zhuang Autonomous Region, Master student. Research areas include remote sensing and satellite meteorology. E-mail: nongzq@mail2.sysu.edu.cn
  • Supported by:
    the National Natural Science Foundation of China “Research on the theory and modeling of nighttime low light atmospheric radiation transmission”(42175086);“Study on the joint observation of geostationary infrared and polar-orbiting microwave constellations for the characteristics of severe convective initiation”(41975031)

随着星载微光成像仪器的出现,人类可以探测到夜间低照度条件下的可见光辐射,尤其是进行了高精度辐射定标后,这些微光辐射资料的定量应用成为最近的研究热点。系统总结了夜间星载微光成像仪在大气、海洋和环境领域的应用研究进展,首先,介绍了星载微光成像仪载荷的发展历程。然后,详细总结微光数据在大气、海洋和环境3个地球科学领域典型应用和带来的科学上的新发现。最后,围绕新的科学目标展望了未来星载微光成像仪的设计思路和应用前景。

With the development of spaceborne low-light imagers, extremely low-magnitude nocturnal visible radiance can accurately be detected. After accurate radiometric calibration, quantitative applications of satellite-based low-light imager observation data attract particularly increased scientific interest. This investigation systematically summarizes the advances in applications and research of satellite-based low-light imager data in the atmospheric, marine, and environmental sciences at night. First, the development history of satellite-based low-light imager payload is briefly introduced. Subsequently, the typical applications of low-light imager data in the atmospheric, marine, and environmental fields and the corresponding new scientific discoveries are summarized. Finally, considering new scientific objectives, advanced design concepts and application prospects for future satellite-based low-light imagers are proposed and discussed.

中图分类号: 

表1 全球主要星载微光成像仪主要技术参数对比
Table 1 Comparison of main technical parameters of major global satellite-based low light sensors
图1 20221172115 UTC FY-3E/MERSI-LL拍摄的朝鲜半岛区域的低云(月相角为
(a) 微光影像可以观察到夜间月光照射的低云的轮廓; (b) 10.8 μm 红外图像由于对比度小无法显示出低云
Fig. 1 Low clouds on the Korean Peninsula taken by FY-3E/MERSI-LL at 2115 UTC on November 72022the moon phase angle is 9°
(a) Low light image shows the outline of low clouds illuminated by moonlight at night; (b) Brightness temperatures at 10.8 μm can not display the low clouds clearly due to its small contrast
图2 201444080859 UTCSuomi-NPP VIIRS/DNB拍摄的同心重力波图像 35
Fig. 2 Concentric gravity wave image from Suomi-NPP VIIRS/DNB at 080859 UTC on April 42014 35
图3 20227300830 UTC FY-3E/MERSI-LL拍摄的位于黄海上空的台风桑达影像
台风桑达北移至我国黄海上空时遭遇了强烈的垂直风切变导致台风的核心对流区和低层环流分离(月相角为141°); (a)FY-3E/MERSI-LL 10.8 μm红外图像,方框内可以看到台风桑达的核心对流区域;(b)FY-3E/MERSI-LL的微光图像,方框内可以看到(a)上无法显示的台风低层的螺旋状环流,与(a)的对流核心区域存在较大偏移;(b)还能看到位于低层环流北侧的对流热塔和闪电,对应于图(a)处的台风对流核心区域
Fig. 3 FY-3E/MERSI-LL images of typhoon Songda over the Yellow Sea at 0830 UTC on July 302022
The typhoon Songda encountered a strong vertical wind shear at 08:30 UTC on July 30, 2022 when it moved northward over the Yellow Sea in China, resulting in the separation of the typhoon’s core convection zone and the low-level circulation (the moon phase angle is 141°). (a) Infrared image at 10.8 μm band of FY-3E/MERSI-LL, the core convection area of typhoon Songda can be seen in the box; (b) The corresponding low light image of FY-3E/MERSI-LL, the spiral circulation of typhoon at the lower level that cannot be shown on subfigure (a) (see in the box), which has a large deviation from the convective core area in subfigure (a); The convective heat tower and the lightning on the north side of the low-level circulation also can be seen on (b) relative to the typhoon convective core area on (a)
图4 20223232300 UTC FY-3E/MERSI-LL拍摄的墨西哥湾海域上线状对流的影像(月相角为78°
(a)微光影像,可以明显看到线状对流上明亮的闪电;(b) 10.8 μm的红外影像,显示了积云线;(c)图(a)闪电区域的局部放大图,闪电表现为亮度远大于背景值的局部亮点
Fig. 4 FY-3E/MERSI-LL images of linear convection in the Gulf of Mexico waters at 2300 UTC on March 232022the moon phase angle is 78°
(a) The bright lightning on the linear convection can be clearly seen in this low light image; (b) Infrared image at 10.8 μm band shows the cumulus line;(c) The partial enlarged view of the lightning area in (a). The lightning appears as a local bright spot with a brightness far greater than the background value
图5 20121010022 UTC Suomi-NPP VIIRS拍摄的南极洲上空南极光的DNB图像 51
(a)绘制了经纬线的南极上空DNB图像;(b)放大显示了(a)中的黄色方框,展示了月光下可见的冰山;(c)放大显示了(a)中的红色方框,展示了明亮的极光现象;(b)和(c)中的蓝色线条代表6 km的长度
Fig. 5 Suomi-NPP VIIRS/DNB images of the aurora australis over Antarctica at 0022 UTC on October 12012 51
(a) DNB image over Antarctica with latitude and longitude lines plotted; (b) Zoomed in on the yellow box highlighted in(a),focused on icebergs visible in the moonlight. (c) Zoomed in on the red box highlighted in (a), focused on an element of the aurora. The blue bars in (b)and (c) represent a length of 6 km
图6 202063日中国黄河入海口泥沙遥感影像
(a) 2020年6月3日中国黄海区域Suomi-NPP VIIRS/DNB影像(月相角为28.4°),黄色方框显示了黄河入海口的悬浮泥沙,由于散射特性强辐射值高于周围海域;(b)对应区域的高德地图平台上的卫星遥感影像(https://www.amap.com)
Fig. 6 Remote sensing images of sediment at the mouth of the Yellow River in China on June 32020
(a) Suomi-NPP VIIRS/DNB image of the Yellow Sea region of China on June 3, 2020 (the moon phase angle is 28.4°). The yellow box shows the suspended sediment at the estuary of the Yellow River. Due to the strong scattering characteristics, the reflected radiance is significantly higher than that of the surrounding sea area. (b) The corresponding region’s satellite remote sensing image from Gaude map platform website (https://www.amap.com)
图7 20131301723 UTC Suomi-NPP VIIRS捕捉的位于南部西里伯斯海(印度尼西亚)的内孤立波 50
(a) VIIRS/M15热红外图像提供了云分布的细节;(b) VIIRS/DNB图像展示了一个内孤立波调制了原本明亮的月球亮斑而表现为暗线
Fig. 7 Suomi-NPP VIIRS captured an internal solitary wave packet in the southern Celebes SeaIndonesiaat 1723 UTC on January 302013 50
(a) VIIRS/M15 thermal infrared imagery provides the details on the cloud distribution; (b) VIIRS/DNB imagery reveals an internal solitary wave packet, which modulates the bright moon glint radiance and induces some dark curved lines
图8 2018714140049 UTC武汉大学“珞珈一号”01星拍摄中国华东地区灯光影像
(b)为(a)中红色方框区域的放大显示,蓝色方框内的亮点为舟山群岛附近的渔船
Fig. 8 The nighttime light image of East China on July 142018 at 140049 UTC Lj-1 01Wuhan University
(b) The enlarged display of the red box area in (a), and the scattered bright spots in the blue box are the fishing boats near Zhoushan Islands
图9 201982Suomi-NPP VIIRS/DNBGanesha号观测到的位于印度尼西亚爪哇岛南部的牛奶海 66
(a) 2019年8月2日17:52 UTC爪哇牛奶海的Suomi-NPP VIIRS/DNB图像,显示了约100 000 km 2的发光海洋;(b) DNB辐射值(取log 10后)沿纬度方向的截面图,绿色线为沿X点到Y点的截面,显示了牛奶海中最明亮区域,黑色线为Ganesha号路径的截面,其中蓝色部分为穿过牛奶海的区域
Fig. 9 Suomi NPP VIIRS/DNB and Ganesha’s ship observed the milky sea in south of JavaIndonesia 66
(a) Suomi-NPP VIIRS/DNB image of Java milky sea at 17:52 UTC on August 2,2019, showing a about 100 000 km 2 swath of glowing ocean;(b) Cross-sections of DNB radiance (log 10-scaled) along the latitudinal direction. The green line is the cross-section between position X and position Y, showing the brightest area of the milky sea,and the black line is the transect of the Ganesha’s track, of which the blue portion represents the part passing through the milky sea
图10 201581101342 GMT(格林尼治平均时间)的VIIRS/DNB图像
图像中伴随着浓烟的高亮区域即为森林火灾发生的区域(https://www.star.nesdis. noaa.gov/star/documents/meetings/2015JPSSAnnual/dayThree/03_Session7a_Straka_DNB_Disasters.pdf)
Fig. 10 The VIIRS/DNB image at 101342 GMTGreenwich mean timeon August 12015
Shows the forest fire and the smoke plume (https://www.star.nesdis.noaa.gov/star/documents/meetings/2015JPSSAnnual/dayThree/03_Session7a_Straka_DNB_Disasters.pdf)
表2 未来星载微光成像仪主要技术参数设计
Table 2 Design of main technical parameters for future satellite-based low light sensors
1 CROFT T A. Nighttime images of the earth from space[J]. Scientific American, 1978, 239(1): 86-98.
2 ZHUO Li, CHEN Jin, SHI Peijun, et al. Modeling population density of China in 1998 based on DMSP/OLS nighttime light image[J]. Acta Geographica Sinica, 2005, 60(2): 266-276.
卓莉, 陈晋, 史培军, 等. 基于夜间灯光数据的中国人口密度模拟[J]. 地理学报, 2005, 60(2): 266-276.
3 SUTTON P C, COSTANZA R. Global estimates of market and non-market values derived from nighttime satellite imagery, land cover, and ecosystem service valuation[J]. Ecological Economics, 2002, 41(3): 509-527.
4 WELCH R. Monitoring urban population and energy utilization patterns from satellite Data[J]. Remote Sensing of Environment, 1980, 9(1): 1-9.
5 SU Yongxian, CHEN Xiuzhi, YE Yuyao, et al. The characteristics and mechanisms of carbon emissions from energy consumption in China using DMSP/OLS night light imageries[J]. Acta Geographica Sinica, 2013, 68(11): 1 513-1 526.
苏泳娴, 陈修治, 叶玉瑶, 等. 基于夜间灯光数据的中国能源消费碳排放特征及机理[J]. 地理学报, 2013, 68(11): 1 513-1 526.
6 MA Ting. Spatiotemporal characteristics of urbanization in China from the perspective of remotely sensed big data of nighttime light[J]. Journal of Geo-Information Science, 2019, 21(1): 59-67.
马廷. 夜光遥感大数据视角下的中国城市化时空特征[J]. 地球信息科学学报, 2019, 21(1): 59-67.
7 LI Guihua, FAN Junfu, ZHOU Yuke, et al. Development characteristics estimation of Shandong peninsula urban agglomeration using VIIRS night light data[J]. Remote Sensing Technology and Application, 2020, 35(6): 1 348-1 359.
李桂华, 范俊甫, 周玉科, 等. 基于VIIRS夜间灯光数据的山东半岛城市群发展特征研究[J]. 遥感技术与应用, 2020, 35(6): 1 348-1 359.
8 ZHANG Lin, LI Xi. Analysis on disparity of regional development in Pakistan under perspective of nighttime light remote sensing[J]. Geomatics and Information Science of Wuhan University, 2022, 47(2): 269-279.
张霖, 李熙. 夜光遥感视角下的巴基斯坦区域发展差异分析[J]. 武汉大学学报(信息科学版), 2022, 47(2): 269-279.
9 ELVIDGE C, BAUGH K, HOBSON V, et al. Satellite inventory of human settlements using nocturnal radiation emissions: a contribution for the global toolchest[J]. Global Change Biology, 1997, 3(5): 387-395.
10 HU Xiuqing, XU Hanlie, LEI Songtao, et al. Overview of low light detection and application of FY-3 early morning satellite[J]. Acta Optica Sinica, 2022, 42(12): 33-46.
胡秀清, 徐寒列, 雷松涛, 等. 风云三号黎明星微光探测及应用综述[J]. 光学学报, 2022, 42(12): 33-46.
11 WANG W H, CAO C Y, BAI Y, et al. Assessment of the NOAA S-NPP VIIRS geolocation reprocessing improvements[J]. Remote Sensing, 2017, 9(10). DOI:10.3390/rs9100974 .
12 LIAO L B, WEISS S, MILLS S, et al. Suomi NPP VIIRS day-night band on-orbit performance[J]. Journal of Geophysical Research: Atmospheres, 2013, 118(22): 12 705-12 718.
13 SCHUELER C F, LEE T F, MILLER S D. VIIRS constant spatial-resolution advantages[J]. International Journal of Remote Sensing, 2013, 34(16): 5 761-5 777.
14 LEE S, CHIANG K, XIONG X X, et al. The S-NPP VIIRS day-night band on-orbit calibration/characterization and current state of SDR products[J]. Remote Sensing, 2014, 6(12): 12 427-12 446.
15 XU Wei, JIN Guang, WANG Jiaqi. Optical imaging technology of JL-1 lightweight high resolution multispectral remote sensing satellite[J]. Optics and Precision Engineering, 2017, 25(8): 1 969-1 978.
徐伟, 金光, 王家骐. 吉林一号轻型高分辨率遥感卫星光学成像技术[J]. 光学精密工程, 2017, 25(8): 1 969-1 978.
16 ZHANG G, LI L T, JIANG Y H, et al. On-orbit relative radiometric calibration of the night-time sensor of the LuoJia1-01 satellite[J]. Sensors, 2018, 18(12). DOI:10.3390/s18124225 .
17 XIA Lang, MAO Kebiao, SUN Zhiwen, et al. Method for detecting cloud at night from VIIRS data based on DNB[J]. Remote Sensing for Land & Resources, 2014, 26(3): 74-79.
夏浪, 毛克彪, 孙知文, 等. 基于DNB验证的VIIRS夜间云检测方法[J]. 国土资源遥感, 2014, 26(3): 74-79.
18 JOACHIM L, STORCH T. Cloud detection for night-time panchromatic visible and near-infrared satellite imagery[Z]. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020: 853-860.
19 EYRE J, BROWNSCOMBE J L, ALLAM R. Detection of fog at night using Advanced Very High Resolution Radiometer (AVHRR) imagery[J]. Meteorological Magazine, 1984, 113: 266-271.
20 JIANG J, YAN W, MA S, et al. Three cases of a new multichannel threshold technique to detect fog/low Stratus during nighttime using SNPP data[J]. Weather and Forecasting, 2015, 30(6): 1 763-1 780.
21 ZHOU Xiaoke, YAN Wei, BAI Heng, et al. Detection of heavy fogs and low clouds during nighttime using DMSP-OLS data[J]. Remote Sensing Information, 2012, 27(6): 86-90.
周小珂, 严卫, 白衡, 等. 基于DMSP/OLS数据的夜间低云大雾监测技术研究[J]. 遥感信息, 2012, 27(6): 86-90.
22 MILLER S D, NOH Y J, GRASSO L D, et al. A physical basis for the overstatement of low clouds at night by conventional satellite infrared-based imaging radiometer Bi-spectral techniques[J]. Earth and Space Science, 2022, 9(2). DOI: 10.1029/2021EA002137 .
23 HU S S, MA S, YAN W, et al. A new multichannel threshold algorithm based on radiative transfer characteristics for detecting fog/low stratus using night-time NPP/VIIRS data[J]. International Journal of Remote Sensing, 2017, 38(21): 5 919-5 933.
24 WALTHER A, HEIDINGER A K, MILLER S. The expected performance of cloud optical and microphysical properties derived from Suomi NPP VIIRS day/night band lunar reflectance[J]. Journal of Geophysical Research: Atmospheres, 2013, 118(23): 13 230-13 240.
25 MIN M, DENG J B, LIU C, et al. An investigation of the implications of lunar illumination spectral changes for day/night band-based cloud property retrieval due to lunar phase transition[J]. Journal of Geophysical Research: Atmospheres, 2017, 122(17): 9 233-9 244.
26 HOLTON J R. The role of gravity wave induced drag and diffusion in the momentum budget of the mesosphere[J]. Journal of the Atmospheric Sciences, 1982, 39(4): 791-799.
27 FRITTS D C, ALEXANDER M J. Gravity wave dynamics and effects in the middle atmosphere[J]. Reviews of Geophysics, 2003, 41(1). DOI:10.1029/2001RG000106 .
28 MCLANDRESS C. On the importance of gravity waves in the middle atmosphere and their parameterization in general circulation models[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 1998, 60(14): 1 357-1 383.
29 GELLER M A, ALEXANDER M J, LOVE P T, et al. A comparison between gravity wave momentum fluxes in observations and climate models[J]. Journal of Climate, 2013, 26(17): 6 383-6 405.
30 MILLER S D, STRAKA W C, YUE J, et al. Upper atmospheric gravity wave details revealed in nightglow satellite imagery[J]. Proceedings of the National Academy of Sciences of the United States of America, 2015, 112(49): E6728-E6735.
31 MILLER S D, MILLS S P, ELVIDGE C D, et al. Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities[J]. Proceedings of the National Academy of Sciences of the United States of America, 2012, 109(39): 15 706-15 711.
32 YUE J, MILLER S D, HOFFMANN L, et al. Stratospheric and mesospheric concentric gravity waves over tropical cyclone Mahasen: joint AIRS and VIIRS satellite observations[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2014, 119: 83-90.
33 MILLER S D, STRAKA W C, YUE J, et al. The dark side of hurricane Matthew: unique perspectives from the VIIRS day/night band[J]. Bulletin of the American Meteorological Society, 2018, 99(12): 2 561-2 574.
34 HU S S, MA S, YAN W, et al. Measuring gravity wave parameters from a nighttime satellite low-light image based on two-dimensional stockwell transform[J]. Journal of Atmospheric and Oceanic Technology, 2019, 36(1): 41-51.
35 AZEEM I, YUE J, HOFFMANN L, et al. Multisensor profiling of a concentric gravity wave event propagating from the troposphere to the ionosphere[J]. Geophysical Research Letters, 2015, 42(19): 7 874-7 880.
36 XU S, YUE J, XUE X H, et al. Dynamical coupling between hurricane Matthew and the middle to upper atmosphere via gravity waves[J]. Journal of Geophysical Research: Space Physics, 2019, 124(5): 3 589-3 608.
37 LAI C, YUE J, XU J Y, et al. Suomi NPP VIIRS/DNB imagery of nightglow gravity waves from various sources over China[J]. Advances in Space Research, 2017, 59(8): 1 951-1 961.
38 SHI G C, HU X, YAO Z G, et al. Case study on stratospheric and mesospheric concentric gravity waves generated by deep convection[J]. Earth and Planetary Physics, 2021, 5(1): 79-89.
39 DVORAK V F. Tropical cyclone intensity analysis using satellite data[M]. Washington, D.C.: U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1984.
40 VELDEN C S, OLANDER T L, ZEHR R M. Development of an objective scheme to estimate tropical cyclone intensity from digital geostationary satellite infrared imagery[J]. Weather and Forecasting, 1998, 13(1): 172-186.
41 OLANDER T, VELDEN C. The advanced Dvorak technique: continued development of an objective scheme to estimate tropical cyclone intensity using geostationary infrared satellite imagery[J]. Weather and Forecasting, 2007, 22(2): 287-298.
42 HAWKINS J D, SOLBRIG J E, MILLER S D, et al. Tropical cyclone characterization via nocturnal low-light visible illumination[J]. Bulletin of the American Meteorological Society, 2017, 98(11): 2 351-2 365.
43 HAWKINS J D, LEE T F, TURK J, et al. Real-time Internet distribution of satellite products for tropical cyclone reconnaissance[J]. Bulletin of the American Meteorological Society, 2001, 82(4): 567-578.
44 VELDEN C, DANIELS J, STETTNER D, et al. Recent innovations in deriving tropospheric winds from meteorological satellites[J]. Bulletin of the American Meteorological Society, 2005, 86(2): 205-224.
45 SIMPSON J, HALVERSON J B, FERRIER B S, et al. On the role of “hot towers” in tropical cyclone formation[J]. Meteorology and Atmospheric Physics, 1998, 67(1): 15-35.
46 DEMETRIADES N W, HOLLE R, BUSINGER S, et al. Eyewall lightning outbreaks and tropical cyclone intensity change[C]// Proceedings of the preprints, 29th conference on Hurricanes and tropical meteorology. Tucson, AZ, American Meteorlogical Society, 2010.
47 DEMARIA M, DEMARIA R. Applications of lightning observations to tropical cyclone intensity forecasting. Preprints [C] //Proceedings of the 16th conference on satellite meteorology and oceanography AZ Phoenixet al. American Meteorlogical Society, 2009.
48 HOFFMANN L, WU X, ALEXANDER M J. Satellite observations of stratospheric gravity waves associated with the intensification of tropical cyclones[J]. Geophysical Research Letters, 2018, 45(3): 1 692-1 700.
49 BANKERT R L, SOLBRIG J E, LEE T F, et al. Automated lightning flash detection in nighttime visible satellite data[J]. Weather and Forecasting, 2011, 26(3): 399-408.
50 MILLER S, STRAKA W III, MILLS S, 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): 6 717-6 766.
51 SEAMAN C J, MILLER S D. VIIRS captures aurora motions[J]. Bulletin of the American Meteorological Society, 2013, 94(10): 1 491-1 493.
52 AKASOFU S I. The development of the auroral substorm[J]. Planetary and Space Science, 1964, 12(4): 273-282.
53 CHAMI M, LARNICOL M, MIGEON S, et al. Potential for nocturnal satellite detection of suspended matter concentrations in coastal waters using a panchromatic band: a feasibility study based on VIIRS (NASA/NOAA) spectral and radiometric specifications[J]. Optics Express, 2020, 28(10): 15 314-15 330.
54 HUANG C W. Estimating coastal water turbidity using VIIRS nighttime measurement[D]. Tampa, FL, USA: University of South Florida, 2019.
55 HU Shensen. Data radiometric calibration and application technology of VIIRS low-light-level channel[D]. Changsha: National University of Defense Technology, 2019.
胡申森. VIIRS微光通道数据辐射定标与应用技术[D]. 长沙: 国防科技大学, 2019.
56 WANG M Q, HU C M. Extracting oil slick features from VIIRS nighttime imagery using a Gaussian filter and morphological constraints[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(10): 2 051-2 055.
57 SHI W, WANG M H. Ocean dynamics observed by the VIIRS day/night band satellite observations[J]. Remote Sensing, 2018, 10(2). DOI:10.3390/rs10010076 .
58 ELVIDGE C, ZHIZHIN M, BAUGH K, et al. Automatic boat identification system for VIIRS low light imaging data[J]. Remote Sensing, 2015, 7(3): 3 020-3 036.
59 LEBONA B, KLEYNHANS W, CELIK T, et al. Ship detection using VIIRS sensor specific data[C]// 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Beijing: IEEE, 2016: 1 245-1 247.
60 COZZOLINO E, LASTA C A. Use of VIIRS DNB satellite images to detect jigger ships involved in the Illex argentinus fishery[J]. Remote Sensing Applications: Society and Environment, 2016, 4: 167-178.
61 GUO Ganggang, FAN Wei, XUE Jialun, et al. Identification for operating pelagic light-fishing vessels based on NPP/VIIRS low light imaging data[J]. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(10): 245-251.
郭刚刚, 樊伟, 薛嘉伦, 等. 基于NPP/VIIRS夜光遥感影像的作业灯光围网渔船识别[J]. 农业工程学报, 2017, 33(10): 245-251.
62 XUE C C, GAO C X, HU J, et al. Automatic boat detection based on diffusion and radiation characterization of boat lights during night for VIIRS DNB imaging data[J]. Optics Express, 2022, 30(8): 13 024-13 038.
63 SHAO J N, YANG Q Y, LUO C Y, et al. Vessel detection from nighttime remote sensing imagery based on deep learning[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 12 536-12 544.
64 SUN S J, LU Y C, LIU Y X, et al. Tracking an oil tanker collision and spilled oils in the East China Sea using multisensor day and night satellite imagery[J]. Geophysical Research Letters, 2018, 45(7): 3 212-3 220.
65 MILLER S D, HADDOCK S H D, ELVIDGE C D, et al. Detection of a bioluminescent milky sea from space[J]. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(40): 14 181-14 184.
66 MILLER S D. Boat encounter with the 2019 Java bioluminescent milky sea: views from on-deck confirm satellite detection[J]. Proceedings of the National Academy of Sciences of the United States of America, 2022, 119(29). DOI: 10.1073/pnas.2207612119 .
67 WANG J, ZHOU M, XU X G, et al. Development of a nighttime shortwave radiative transfer model for remote sensing of nocturnal aerosols and fires from VIIRS[J]. Remote Sensing of Environment, 2020, 241. DOI: 10.1016/j.rse.2020.111727 .
68 ZHANG J, REID J S, MILLER S D, et al. Strategy for studying nocturnal aerosol optical depth using artificial lights[J]. International Journal of Remote Sensing, 2008, 29(16): 4 599-4 613.
69 JOHNSON R S, ZHANG J, HYER E J, et al. Preliminary investigations toward nighttime aerosol optical depth retrievals from the VIIRS day/night band[J]. Atmospheric Measurement Techniques, 2013, 6(5): 1 245-1 255.
70 MCHARDY T M, ZHANG J, REID J S, et al. An improved method for retrieving nighttime aerosol optical thickness from the VIIRS day/night band[J]. Atmospheric Measurement Techniques, 2015, 8(11): 4 773-4 783.
71 ZHANG J L, JAKER S L, REID J S, et al. Characterization and application of artificial light sources for nighttime aerosol optical depth retrievals using the visible infrared imager radiometer suite day/night band[J]. Atmospheric Measurement Techniques, 2019, 12(6): 3 209-3 222.
72 JIANG Mengdie, CHEN Lin, HE Yuqing, et al. Nighttime aerosol optical depth retrievals from VIIRS day/night band data[J]. National Remote Sensing Bulletin, 2022, 26(3): 493-504.
姜梦蝶, 陈林, 何玉青, 等. 利用NPP/VIIRS微光数据反演夜间气溶胶光学厚度[J]. 遥感学报, 2022, 26(3): 493-504.
73 WANG J, AEGERTER C, XU X G, et al. Potential application of VIIRS day/night band for monitoring nighttime surface PM2.5 air quality from space[J]. Atmospheric Environment, 2016, 124: 55-63.
74 FU D, XIA X, DUAN M, et al. Mapping nighttime PM2.5 from VIIRS DNB using a linear mixed-effect model[J]. Atmospheric Environment, 2018, 178: 214-222.
75 XU G Y, REN X D, XIONG K N, et al. Analysis of the driving factors of PM2.5 concentration in the air: a case study of the Yangtze River Delta, China[J]. Ecological Indicators, 2020, 110. DOI: 10.1016/j.ecolind.2019.105889 .
76 ZHANG G, SHI Y R, XU M Z. Evaluation of LJ1-01 nighttime light imagery for estimating monthly PM2.5 concentration: a comparison with NPP-VIIRS nighttime light data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020. DOI:10.1109/JSTARS.2020.3002671 .
77 MIN M, ZHENG J Y, ZHANG P, et al. A low-light radiative transfer model for satellite observations of moonlight and earth surface light at night[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2020, 247. DOI:10.1016/j.jqsrt.2020.106954 .
78 MIN M, ZHANG L, ZHENG J Y, et al. Can the Earth-Moon distance influence the accuracy of lunar irradiance with the plane-parallel assumption in atmospheric radiative transfer at night?[J]. Journal of the Atmospheric Sciences, 2021. DOI: 10.1175/JAS-D-20-0198.1 .
79 SOLBRIG J E, MILLER S D, ZHANG J L, et al. Assessing the stability of surface lights for use in retrievals of nocturnal atmospheric parameters[J]. Atmospheric Measurement Techniques, 2020, 13(1): 165-190.
80 ZHOU M, WANG J, CHEN X, et al. Nighttime smoke aerosol optical depth over U.S. rural areas: first retrieval from VIIRS moonlight observations[J]. Remote Sensing of Environment, 2021, 267. DOI: 10.1016/j.rse.2021.112717 .
81 MATSON M, DOZIER J. Identification of subresolution high temperature sources using a thermal IR sensor[J]. Photogrammetric Engineering and Remote Sensing, 1981, 47(9):1 311-1 318.
82 ELVIDGE C, ZHIZHIN M, BAUGH K, et al. Extending nighttime combustion source detection limits with short wavelength VIIRS data[J]. Remote Sensing, 2019, 11(4). DOI:10.3390/rs11040395 .
83 POLIVKA T N, WANG J, ELLISON L T, et al. Improving nocturnal fire detection with the VIIRS day-night band[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(9): 5 503-5 519.
84 ELVIDGE C, ZHIZHIN M, HSU F C, et al. VIIRS nightfire: satellite pyrometry at night[J]. Remote Sensing, 2013, 5(9): 4 423-4 449.
85 WANG J, ROUDINI S, HYER E J, et al. Detecting nighttime fire combustion phase by hybrid application of visible and infrared radiation from Suomi NPP VIIRS[J]. Remote Sensing of Environment, 2020, 237. DOI: 10.1016/j.rse.2019.111466 .
86 ELVIDGE C D, CINZANO P, PETTIT D R, et al. The nightsat mission concept[J]. International Journal of Remote Sensing, 2007, 28(12): 2 645-2 670.
[1] 方红亮, 车涛, 晋锐, 李爱农, 李新, 李增元, 刘绍民, 马明国, 肖青, 张永光. 建设中国陆表遥感产品真实性检验基准台站网络的思考[J]. 地球科学进展, 2021, 36(12): 1215-1223.
[2] 王帅, 徐涵秋, 施婷婷. GF-1 WFV2传感器数据的缨帽变换系数反演[J]. 地球科学进展, 2018, 33(6): 641-652.
[3] 栾海军, 田庆久, 章欣欣, 聂芹, 朱晓玲. 定量遥感地表参数尺度转换研究趋势探讨[J]. 地球科学进展, 2018, 33(5): 483-492.
[4] 李爱农, 边金虎, 尹高飞, 靳华安, 赵伟, 张正健, 南希, 雷光斌. 山地典型生态参量遥感反演建模及其时空表征能力研究[J]. 地球科学进展, 2018, 33(2): 141-151.
[5] 晋锐, 李新, 马明国, 葛咏, 刘绍民, 肖青, 闻建光, 赵凯, 辛晓平, 冉有华, 柳钦火, 张仁华. 陆地定量遥感产品的真实性检验关键技术与试验验证[J]. 地球科学进展, 2017, 32(6): 630-642.
[6] 于文涛, 李静, 柳钦火, 曾也鲁, 尹高飞, 赵静, 徐保东. 中国地表覆盖异质性参数提取与分析[J]. 地球科学进展, 2016, 31(10): 1067-1077.
[7] 韩培, 舒红, 许剑辉. EnKF同化的背景误差协方差矩阵局地化对比研究[J]. 地球科学进展, 2014, 29(10): 1175-1185.
[8] 李大治, 晋锐, 车涛, 高莹, 耶楠, 王树果. 联合机载PLMR微波辐射计和MODIS产品反演黑河中游张掖绿洲土壤水分研究 *[J]. 地球科学进展, 2014, 29(2): 295-305.
[9] 栾海军,田庆久,余 涛,胡新礼,黄彦,刘李,杜灵通,魏曦. 定量遥感升尺度转换研究综述[J]. 地球科学进展, 2013, 28(6): 657-664.
[10] 李峰,李柏,吴蕾,杨荣康,邢毅,黄兴友,肖辉,王斌. WMO第八届阳江国际探空比对辅助遥感综合试验[J]. 地球科学进展, 2012, 27(8): 916-924.
[11] 马建文,秦思娴. 数据同化算法研究现状综述[J]. 地球科学进展, 2012, 27(7): 747-757.
[12] 摆玉龙, 李新, 韩旭军. 陆面数据同化系统误差问题研究综述[J]. 地球科学进展, 2011, 26(8): 795-804.
[13] 吴炳方,蒙继华,李强子. 国外农情遥感监测系统现状与启示[J]. 地球科学进展, 2010, 25(10): 1003-1012.
[14] 吴炳方,蒙继华,李强子,张飞飞,杜鑫,闫娜娜. “全球农情遥感速报系统(CropWatch)”新进展[J]. 地球科学进展, 2010, 25(10): 1013-1022.
[15] 田苗,王鹏新,孙威. 基于地表温度与植被指数特征空间反演地表参数的研究进展[J]. 地球科学进展, 2010, 25(7): 698-705.
阅读次数
全文


摘要