地表异常遥感探测与即时诊断方法研究框架

doi:10.11947/j.AGCS.2022.20220124

摘要/Abstract

摘要： 由自然和人为因素引起的各类地表异常具有突发性、多样性、随机性和复杂性,导致传统的卫星遥感探测时效严重滞后于地表异常预警和应急处置的实际需要,地表异常实时化、智能化遥感探测已成为我国新时代社会与经济高质量发展的重大战略需求,也是当前遥感科学发展面临的重大技术挑战。本文在分析地表异常遥感即时探测面临的技术挑战及其研究的必要性基础上,围绕解决地表异常遥感探测“看不到、看不清、看不快”技术瓶颈背后的科学问题,从卫星、载荷、应用三位一体的新视角,提出以“通导遥”一体化、星上在轨处理、星地互馈机器学习等为代表的地表异常遥感即时探测机理与方法研究思路,构建包括地表异常遥感响应特征与语义表征、地表异常超大动态范围自适应即时遥感探测、地表异常遥感在轨即时诊断、地表异常遥感预警知识即时生成与表达等在内的地表异常遥感即时探测研究框架,为深入开展地表异常遥感即时探测机理与方法研究提供科学方案,为实现直到用户移动终端的地表异常遥感监测预警产品即时服务提供技术体系框架。

关键词: 地表异常, 遥感机理, 遥感即时探测

Abstract: Due to the abruptness, diversity, randomness and complexity of all kinds of earth surface anomalies caused by natural and human factors, the time-effectiveness of traditional satellite remote sensing is seriously lagging behind the actual needs of earth surface anomaly warning and emergency treatment. Real-time and intelligent remote sensing monitoring of earth surface anomalies has become an important strategic demand for high-quality social and economic development in China in the new era, and also a major technical challenge for the development of remote sensing science. Based on the analysis of the technical challenges and the necessity of research on the real-time remote sensing monitoring of earth surface anomalies, this paper focuses on solving the scientific problems behind the technical bottleneck of "not being able to see, not being able to see clearly and not being able to see quickly" in remote sensing monitoring of earth surface anomalies. From a new perspective of the trinity of satellite, payload and application, a series of new ideas on real-time monitoring of surface anomalies by the integration of "communication-navigation-remote sensing", on-orbit processing and satellite-earth reciprocal feeding machine learning have been put forward. A research framework for real-time remote sensing monitoring of earth surface anomalies is proposed, which consists of remote sensing response characteristics and semantic characterization of earth surface anomalies, adaptive real-time remote sensing monitoring of large dynamic range, real-time remote sensing detection in orbit, and real-time generation and expression of remote sensing early warning knowledge, these studies provide a scientific scheme for in-depth research on the mechanism and method of real-time monitoring of earth surface anomalies by remote sensing, and provide a the technical system framework for realizing real-time service of remote sensing monitoring and early warning products for earth surface anomalies up to the user's mobile terminal.

Key words: earth's surface anomalies, remote sensing mechanism, remote sensing real-time monitoring

中图分类号:

P237

王桥. 地表异常遥感探测与即时诊断方法研究框架[J]. 测绘学报, 2022, 51(7): 1141-1152.

WANG Qiao. Research framework of remote sensing monitoring and real-time diagnosis of earth surface anomalies[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(7): 1141-1152.

参考文献

[1] 戎志国,刘诚,孙涵,等.卫星火情探测灵敏度试验与火情遥感新探测通道选择[J].地球科学进展, 2007, 22(8):866-871. RONG Zhiguo, LIU Cheng, SUN Han, et al. Sensitivity experiment for fire detecting using satellites' data and new detection channel selection for fire remote sensing[J]. Advances in Earth Science, 2007, 22(8):866-871.
[2] 栾玉洁,郭金运,高永刚,等.基于Sentinel-1B SAR数据的2018年寿光洪水遥感监测及灾害分析[J].自然灾害学报, 2021, 30(2):168-175. DOI:10.13577/j.jnd.2021.0217. LUAN Yujie, GUO Jinyun, GAO Yonggang, et al. Remote sensing monitoring of flood and disaster analysis in Shouguang in 2018 from Sentinel-1B SAR data[J]. Journal of Natural Disasters, 2021, 30(2):168-175. DOI:10.13577/j.jnd.2021.0217.
[3] 黄文江,师越,董莹莹,等.作物病虫害遥感监测研究进展与展望[J].智慧农业, 2019, 1(4):1-11. HUANG Wenjiang, SHI Yue, DONG Yingying, et al. Progress and prospects of crop diseases and pests monitoring by remote sensing[J]. Smart Agriculture, 2019, 1(4):1-11.
[4] 刘筱怡.基于多元遥感技术的古滑坡识别与危险性评价研究[D].北京:中国地质科学院, 2020. LIU Xiaoyi. Identification and hazard assessment of ancient landslides based on multi-source remote sensing technology[D]. Beijing:Chinese Academy of Geological Sciences, 2020.
[5] 王桥.中国环境遥感监测技术进展及若干前沿问题[J].遥感学报, 2021, 25(1):25-36. WANG Qiao. Progress of environmental remote sensing monitoring technology in China and some related frontier issues[J]. National Remote Sensing Bulletin, 2021, 25(1):25-36.
[6] YANG Liping, DRISCOL J, SARIGAI S, et al. Towards synoptic water monitoring systems:a review of AI methods for automating water body detection and water quality monitoring using remote sensing[J]. Sensors, 2022, 22(6):2416.
[7] ZHANG Rongqun, ZHU Daolin. Study of land cover classification based on knowledge rules using high-resolution remote sensing images[J]. Expert Systems with Applications, 2011, 38(4):3647-3652.
[8] 范一大,吴玮."高分四号"发射成功助力防灾减灾事业[J].中国减灾, 2016(3):48-49. FAN Yida, WU Wei. "Gaofen-4" successfully launched to help disaster prevention and mitigation[J]. China Disaster Reduction, 2016(3):48-49.
[9] NAKASHIMA T. An anatomic study on the Martin-Gruber anastomosis[J]. Surgical and Radiologic Anatomy, 1993, 15(3):193-195.
[10] 王振峰,刘纪平.获取机制下的地理空间数据互操作研究[J].武汉大学学报(信息科学版), 2009, 34(9):1034-1038. WANG Zhenfeng, LIU Jiping. Geo-spatial data interoperability in mechanism of acquisition[J]. Geomatics and Information Science of Wuhan University, 2009, 34(9):1034-1038.
[11] 王锦地,张立新,柳钦火,等.中国典型地物波谱知识库[M].北京:科学出版社, 2009. WANG Jindi, ZHANG Lixin, LIU Qinhuo, et al. Spectral knowledge base of typical features in China[M]. Beijing:Science Press, 2009.
[12] LIU Sen, TIAN Jingqi, WANG Lei, et al. Hydrothermal treatment of grass:a low-cost, green route to nitrogen-doped, carbon-rich, photoluminescent polymer nanodots as an effective fluorescent sensing platform for label-free detection of Cu (Ⅱ) ions[J]. Advanced Materials, 2012, 24(15):2037-2041.
[13] WANG Jun, LU Wei, TONG Yuxin, et al. Leaf morphology, photosynthetic performance, chlorophyll fluorescence, stomatal development of lettuce (Lactuca sativa L.) exposed to different ratios of red light to blue light[J]. Frontiers in Plant Science, 2016, 7:250.
[14] FICHOT C G, DOWNING B D, BERGAMASCHI B A, et al. High-resolution remote sensing of water quality in the San Francisco Bay-Delta estuary[J]. Environmental Science&Technology, 2016, 50(2):573-583.
[15] 张良培,沈焕锋.遥感数据融合的进展与前瞻[J].遥感学报, 2016, 20(5):1050-1061. ZHANG Liangpei, SHEN Huanfeng. Progress and future of remote sensing data fusion[J]. Journal of Remote Sensing, 2016, 20(5):1050-1061.
[16] 孙伟健,林军,阮宁娟,等.国外光学遥感成像系统仿真软件发展综述与思考[J].航天返回与遥感, 2010, 31(3):70-75. SUN Weijian, LIN Jun, RUAN Ningjuan, et al. Summarization and consideration of oversea's simulation software development for optical remote sensing system[J]. Spacecraft Recovery&Remote Sensing, 2010, 31(3):70-75.
[17] 刘银年,孙德新,胡晓宁,等.高分五号可见短波红外高光谱相机设计与研制[J].遥感学报, 2020, 24(4):333-344. LIU Yinnian, SUN Dexin, HU Xiaoning, et al. Development of visible and short-wave infrared hyperspectral imager onboard GF-5 satellite[J]. National Remote Sensing Bulletin, 2020, 24(4):333-344.
[18] 李晓坤,陈桂林.地球静止轨道三轴稳定气象卫星辐射计——可见光通道CCD星敏感[J].科学技术与工程, 2007, 7(19):4897-4899. LI Xiaokun, CHEN Guilin. Three-axis stabidiged satellite radiometer of geostationary chaned-CCD starsenge of visible channd[J]. Science Technology and Engineering, 2007, 7(19):4897-4899.
[19] 阮宁娟,庄绪霞,李妥妥,等.空间光学遥感系统全链路仿真与分析[J].航天返回与遥感, 2013, 34(6):36-43. RUAN Ningjuan, ZHUANG Xuxia, LI Tuotuo, et al. End to end simulation and analysis of space optical remote sensing system[J]. Spacecraft Recovery&Remote Sensing, 2013, 34(6):36-43.
[20] 李德仁,王艳军,邵振峰.新地理信息时代的信息化测绘[J].武汉大学学报(信息科学版), 2012, 37(1):1-6. LI Deren, WANG Yanjun, SHAO Zhenfeng. Geo-informatization of new geographic information era[J]. Geomatics and Information Science of Wuhan University, 2012, 37(1):1-6.
[21] LIEBRECHT P, SCHIER J, BHASIN K B, et al. NASA's integrated space communications architecture[C]//SpaceOps 2010 Conference. Huntsville:AIAA, 2010:2174.
[22] 李德仁.脑认知与空间认知——论空间大数据与人工智能的集成[J].武汉大学学报(信息科学版), 2018, 43(12):1761-1767. LI Deren. Brain Cognition and spatial cognition:on integration of geo-spatial big data and artificial intelligence[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12):1761-1767.
[23] JUNG D H, KIM D H, AZIM M T, et al. A novel signal processing technique for Ku-band automobile FMCW fully polarimetric SAR system using triangular LFM[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 70:8500210.
[24] DU Bo, CAI Shihan, WU Chen. Object tracking in satellite videos based on a multiframe optical flow tracker[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12(8):3043-3055.
[25] 康旭辉,连剑,赵雪纲.基于SpaceVPX架构的星上高速载荷数据实时处理平台设计[J].航天器工程, 2018, 27(4):98-103. KANG Xuhui, LIAN Jian, ZHAO Xuegang. Spaceborne high-speed payload data real-time processing platform design based on spaceVPX architecture[J]. Spacecraft Engineering, 2018, 27(4):98-103.
[26] ZHENG Zixuan, GUO Jian, GILL E. Distributed onboard mission planning for multi-satellite systems[J]. Aerospace Science and Technology, 2019, 89:111-122.
[27] 李德仁,洪勇,王密,等.测绘遥感能为智能驾驶做什么?[J].测绘学报, 2021, 50(11):1421-1431. DOI:10.11947/j.AGCS.2021.20210280. LI Deren, HONG Yong, WANG Mi, et al. What can surveying and remote sensing do for intelligent driving?[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(11):1421-1431. DOI:10.11947/j.AGCS.2021.20210280.
[28] THOME K J, BIGGAR S F, WISNIEWSKI W. Cross comparison of EO-1 sensors and other Earth resources sensors to Landsat-7 ETM+using Railroad Valley Playa[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(6):1180-1188.
[29] ZHUKOV B, LORENZ E, OERTEL D, et al. Spaceborne detection and characterization of fires during the bi-spectral infrared detection (BIRD) experimental small satellite mission (2001-2004)[J]. Remote sensing of Environment, 2006, 100(1):29-51.
[30] 姚烨,乔彦峰,钟兴,等.凝视成像降质模型的超分辨率重建[J].光学学报, 2017, 37(8):109-118. YAO Ye, QIAO Yanfeng, ZHONG Xing, et al. Super-resolution reconstruction of staring imaging degraded model[J]. Acta Optica Sinica, 2017, 37(8):109-118.
[31] 叶伟文.长时序多源遥感数据的海洋赤潮环境异常检测方法研究[D].杭州:浙江大学, 2020. YE Weiwen. Research on anomaly detection method in marine red tide environment based on long-term multi-source remote sensing data[D]. Hangzhou:Zhejiang University, 2020.
[32] 卞明明.基于MODIS影像的赤潮监测方法研究与应用[D].秦皇岛:河北科技师范学院, 2020. BIAN Mingming. Research and application of red tide Monitozring method based on MODIS images[D]. Qinhuangdao:Hebei Normal University of Science and Technology, 2020.
[33] JAIMES A, CHANG S F. Conceptual framework for indexing visual information at multiple levels[C]//Proceedings of the SPIE 3964, Internet Imaging. San Jose:SPIE, 1999:2-15.
[34] VOGEL J, SCHIELE B. Semantic modeling of natural scenes for content-based image retrieval[J]. International Journal of Computer Vision, 2007, 72(2):133-157.
[35] DU Bo, ZHANG Liangpei. Random-selection-based anomaly detector for hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(5):1578-1589.
[36] CUI Xiaoguang, TIAN Yuan, WENG Lubin, et al. Anomaly detection in hyperspectral imagery based on low-rank and sparse decomposition[C]//Proceedings of the SPIE 9069, Fifth International Conference on Graphic and Image Processing. Hong Kong, China:SPIE, 2014:90690R.
[37] 孟令博,耿修瑞.基于协峭度张量的高光谱图像异常检测[J].电子与信息学报, 2019, 41(1):150-155. MENG Lingbo, GENG Xiurui. A hyperspectral imagery anomaly detection algorithm based on cokurtosis tensor[J]. Journal of Electronics&Information Technology, 2019, 41(1):150-155.
[38] YU Dawen, JI Shunping. Grid based spherical CNN for object detection from panoramic images[J]. Sensors, 2019, 19(11):2622.
[39] 刘俊楠,刘海砚,陈晓慧,等.基于地理空间数据的知识图谱构建技术研究[J].中文信息学报, 2020, 34(11):29-36. LIU Junnan, LIU Haiyan, CHEN Xiaohui, et al. Construction of knowledge graph based on geo-spatial data[J]. Journal of Chinese Information Processing, 2020, 34(11):29-36.
[40] DAVIS C O, HORAN D M, CORSON M R. On-orbit calibration of the naval EarthMap observer (NEMO) coastal ocean imaging spectrometer (COIS)[C]//Proceedings of the SPIE 4132, Imaging Spectrometry Ⅵ. San Diego:SPIE, 2000.
[41] DOGGETT T, GREELEY R, CHIEN S, et al. Autonomous detection of cryospheric change with hyperion on-board Earth Observing-1[J]. Remote Sensing of Environment, 2006, 101(4):447-462.
[42] 杨思全.《国家综合防灾减灾规划(2016-2020年)》编制情况介绍[J].中国减灾, 2017(1):20-23. YANG Siquan. Introduction to the compilation of the national comprehensive disaster prevention and mitigation plan (2016-2020)[J]. China Disaster Reduction, 2017(1):20-23.
[43] 眭海刚,刘超贤,刘俊怡,等.典型自然灾害遥感快速应急响应的思考与实践[J].武汉大学学报(信息科学版), 2020, 45(8):1137-1145. SUI Haigang, LIU Chaoxian, LIU Junyi, et al. Reflection and exploration of rapid remote sensing emergency response for typical natural disasters[J]. Geomatics and Information Science of Wuhan University, 2020, 45(8):1137-1145.
[44] LIU Gaokai, YANG Ning, GUO Lei, et al. A one-stage approach for surface anomaly detection with background suppression strategies[J]. Sensors, 2020, 20(7):1829.
[45] YANG Xiao, XU Guangjun, LIU Yu, et al. Multi-source data analysis of mesoscale eddies and their effects on surface chlorophyll in the Bay of Bengal[J]. Remote Sensing, 2020, 12(21):3485.
[46] VOIGT S, GIULIO-TONOLO F, LYONS J, et al. Global trends in satellite-based emergency mapping[J]. Science, 2016, 353(6296):247-252.
[47] IRAHA Y, OKADA M, TOGUCHI M, et al. Multimodality imaging in secondary postpartum or postabortion hemorrhage:retained products of conception and related conditions[J]. Japanese Journal of Radiology, 2018, 36(1):12-22.
[48] HOOT N R, ARONSKY D. An early warning system for overcrowding in the emergency department[C]//Proceedings of the AMIA 2006 American Medical Informatics Association Annual Symposium. Washington:AMIA, 2006:339.