Application and trend analysis of remote sensing technology for earthquake emergency investigation
- Vol. 26, Issue 10, Pages: 1920-1934(2022)
Published： 07 October 2022
DOI： 10.11834/jrs.20210078
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摘要
地震是一种会造成人类生命财产重大损失的突发性自然灾害，震后第一时间启动应急响应并开展灾情的快速评估能有效地减轻地震灾害带来的破坏。空间对地观测技术为宏观性的地震应急与调查工作提供了便捷、经济的途径，随着空间对地观测技术与数据处理技术的不断发展，各国学者对遥感应急调查开展了大量深入的研究工作，相关研究成果已广泛地应用于地震应急的实际工作中。但是，遥感数据类型与处理技术的多样化也带来了应急信息的散乱，导致遥感快速应急响应系统性不强，使得应急服务不持续，一定程度上限制了遥感技术的效能；为此，针对现阶段遥感技术在地震应急调查中的应用情况，在总结地震应急调查常用遥感技术手段的基础上，分析了遥感快速应急响应面临的技术挑战，重点梳理了地震应急不同阶段对遥感数据及应急专题产品产出类型与时效性的现实需求，结合震后灾区影像数据的情况，系统地分析了光学、雷达、激光雷达遥感技术在地震应急调查应用中的技术现状与存在的问题。在实际地震应用案例分析的基础，总结剖析遥感应急工作存在的问题，并重点从海量数据快速处理、震害信息智能化提取、多源数据协同分析3个技术层面论述了遥感地震应急面临的核心困难，基于此，结合在轨数据实时、海量数据快速处理就灾情智能化识别的多技术联合、多源数据协同分析、发展敏捷卫星等几个方面论述了未来遥感技术在防震减灾中的发展趋势，以期推动遥感监测手段提供动态、实时、持续的空间信息应急服务能力，提高地震应急工作的快速响应、精细化与业务化应用能力。本文的研究可以为多源遥感技术在地震应急调查中的科研及业务应用提供很好的参考，更高效的发挥遥感技术在防震减灾工作中的应用能力与水平。
Abstract
Earthquakes are sudden natural disasters that cause great loss of human life and property. However
starting an emergency response and carrying out rapid assessment of the disaster situation during the first few moments after an earthquake can effectively reduce the damage caused by the earthquake. Space Earth Observation Technology plays an important role in earthquake emergency because of its macro
fast
and wide coverage. With the continuous development of space earth observation technology and data processing technology
scholars worldwide have conducted several in-depth research on the extraction of earthquake damage information in the remote sensing emergency process. However
in actual emergency operations
a universal workflow does not exist. To promote in-depth and real operational efficiency of remote sensing earthquake emergency work
the problems in remote sensing emergency work are analyzed
and the future development trend of remote sensing earthquake emergency is put forward
so as to make the application of remote sensing technology in earthquake prevention and disaster reduction efficient. The timeliness of remote sensing emergency to a certain extent affects the efficiency and accuracy of decision-making that is vital in emergency assistance. At different stages of a disaster
the demand for remote sensing images
such as spatial resolution and time resolution
varies. In view of the application of remote sensing technology in earthquake emergency investigation
we analyze the application of remote sensing technology in the process of earthquake emergency by means of a literature review. According to the classification of optical remote sensing image and SAR image
we analyze and introduce the methods of earthquake damage information investigation using different type of remote sensing images
such as supervision classification
change detection
and depth learning.
In the recognition of earthquake damage information
high-resolution optical remote sensing images usually only use their spectral features
ignoring the application of spatial distribution features and geometric features. Traditional pixel based classification methods are easy to contain salt and pepper effect in the classification results
so it is necessary to develop object-based multi feature knowledge driven classification technology on this basis. Therefore
the method of combining object-oriented analysis and knowledge integration will become the mainstream method of earthquake disaster extraction and evaluation in the future. For SAR images
the seismic damage evaluation of single temporal SAR images mainly focuses on the average seismic damage evaluation in blocks
and there is less research on the imaging mechanism
feature performance and information extraction of single buildings. After the earthquake
the earthquake damage targets are complex and diverse. In order to fully realize the automatic extraction of earthquake damage targets based on remote sensing images
it still needs the continuous improvement and development of the algorithm.Traditional change detection methods are mainly aimed at the same type of sensors. The effective combination and interactive utilization of remote sensing image data from different sources is also the development trend in the future. The characteristic information of earthquake damage targets with different degrees of earthquake damage in remote sensing images is also different. The feature-based object-oriented change detection method can make full use of the feature information of the image and effectively improve the accuracy of seismic damage identification. Therefore
the focus of multi temporal image change detection is the effective application of spatial features in object level change detection.
We then summarize the existing problems and discuss the main difficulties faced by remote sensing earthquake emergency and the solutions from three aspects. Combined with real-time orbit data and practical work
the paper analyzes the future development trend of remote sensing technology in earthquake prevention and disaster reduction from the aspects of multi-technology combination of intelligent disaster identification
multi-source data collaborative analysis
and development of agile satellite. Through this approach
we promote remote sensing monitoring means to provide dynamic
real-time
and continuous space information emergency service
and improve the rapid development of earthquake emergency work response
refinement
and business application. This research can provide a good reference for the scientific research and business application of multi-source remote sensing technology in earthquake emergency investigation
and give more efficient play to the applicability and level of remote sensing technology in earthquake prevention and disaster reduction.
关键词
遥感地震应急调查应急专题产品震害信息提取
Keywords
remote sensingearthquakeemergency investigationemergency special productsearthquake damage information extraction
references
Anders N S, Seijmonsbergen A C and Bouten W. 2013. Geomorphological change detection using object-based feature extraction from multi-temporal LiDAR data. IEEE Geoscience and Remote Sensing Letters, 10(6): 1587-1591 [DOI: 10.1109/LGRS.2013.2262317http://dx.doi.org/10.1109/LGRS.2013.2262317]
Arciniegas G A, Bijker W, Kerle N and Tolpekin V A. 2007. Coherence- and amplitude-based analysis of seismogenic damage in Bam, Iran, using ENVISAT ASAR data. IEEE Transactions on Geoscience and Remote Sensing, 45(6): 1571-1581 [DOI: 10.1109/TGRS.2006.883149http://dx.doi.org/10.1109/TGRS.2006.883149]
Baatz M and Schäpe A. 1999. Object-oriented and Multi-scale image analysis in Semantic networks//Proceedings of the 2nd International Symposium on Operationalization of Remote Sensing. Enschede, ITC, AUG: 87-109
Bitelli G, Camassi R, Gusella L and Mognol A. 2004. Image change detection on urban areas: the earthquake case//Proceedings of the 20th International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Istanbul, Turkey, 7(12): 692-697
Blaschke T. 2010. Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65(1): 2-16 [DOI: 10.1016/j.isprsjprs.2009.06.004http://dx.doi.org/10.1016/j.isprsjprs.2009.06.004]
Chen J B, Liu S X, Wang C Y, You S C and Wang Z W. 2013. Research on urban water body extraction using knowledge-based decision tree. Remote Sensing Information, 28(1): 29-33, 37
陈静波, 刘顺喜, 汪承义, 尤淑撑, 王忠武. 2013. 基于知识决策树的城市水体提取方法研究. 遥感信息, 28(1): 29-33, 37 [DOI: 10.3969/j.issn.1000-3177.2013.01.007http://dx.doi.org/10.3969/j.issn.1000-3177.2013.01.007]
Chen L Z, Shen X H, Wang H, Hong S Y and Jing F. 2016. Application of high-resolution remote sensing technique to earthquake studies in China. Acta Seismologica Sinica, 38(3): 333-344
陈立泽, 申旭辉, 王辉, 洪顺英, 荆凤. 2016. 我国高分辨率遥感技术在地震研究中的应用. 地震学报, 38(3): 333-344 [DOI: 10.11939/jass.2016.03.002http://dx.doi.org/10.11939/jass.2016.03.002]
Chen Q H. 2007. Research and realization of multi-sources remote sensing data on object oriented. Wuhan: China University of Geosciences
陈启浩. 2007. 面向对象的多源遥感数据分类技术研究与实现. 武汉: 中国地质大学
Chen R, Guo X Y, Du J and Hu X. 2020. Monitoring of disturbance on ecological environment caused by earthquake and post-disaster reconstruction at Heye Village area of Jiuzhaigou using the high-resolution remote sensing imageries. Quaternary Sciences, 40(5): 1350-1358
陈润, 郭忻怡, 杜杰, 胡晓. 2020. 地震地质灾害及灾后重建对九寨沟荷叶寨区域生态环境扰动的遥感监测. 第四纪研究, 40(5): 1350-1358 [DOI:10.11928/j.issn.1001-7410.2020.05.22http://dx.doi.org/10.11928/j.issn.1001-7410.2020.05.22]
Chen W F，Guo H M and Zhang Y. 2014. Fast acquisition and analytical processing system of earthquake disaster information in Sichuan Province. Journal of Catastrophology，29（2）：116-122
陈维锋, 郭红梅, 张翼. 2014. 四川省地震灾情快速上报接收处理系统.灾害学, 29(2):116-122 [DOI:10.3969/j.issn.1000-811X.2014.02.023http://dx.doi.org/10.3969/j.issn.1000-811X.2014.02.023]
Chen X L and Xie G L. Quick evaluation and decision making for earthquake disaster by airborne remote sensing. Journal of Natural Disasters, 5(3): 29-34
陈鑫连, 谢广林. 1996. 航空遥感的震害快速评估与救灾决策. 自然灾害学报, 5(3): 29-34
Chini M, Bignami C, Stramondo S and Pierdicca N. 2008. Uplift and subsidence due to the 26 December 2004 Indonesian earthquake detected by SAR data. International Journal of Remote Sensing, 29(13): 3891-3910 [DOI: 10.1080/01431160701871112http://dx.doi.org/10.1080/01431160701871112]
Chini M, Cinti F R and Stramondo S. 2011. Co-seismic surface effects from very high resolution panchromatic images: the case of the 2005 Kashmir (Pakistan) earthquake. Natural Hazards and Earth System Sciences, 11(3): 931-943 [DOI: 10.5194/nhess-11-931-2011http://dx.doi.org/10.5194/nhess-11-931-2011]
Dell’Acqua F, Bignami C, Chini M, Lisini G, Polli D A and Stramondo S. 2011. Earthquake damages rapid mapping by satellite remote sensing data: L'Aquila April 6th, 2009 event. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4(4): 935-943 [DOI: 10.1109/JSTARS.2011.2162721http://dx.doi.org/10.1109/JSTARS.2011.2162721]
Dekker R J. 2011. High-resolution radar damage assessment after the earthquake in Haiti on 12 January 2010. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 4(4):960-970.[ DOI:10.1109/JSTARS.2011.2164516]
Dong L G and Shan J. 2013. A comprehensive review of earthquake-induced building damage detection with remote sensing techniques. ISPRS Journal of Photogrammetry and Remote Sensing, 84: 85-99 [DOI: 10.1016/j.isprsjprs.2013.06.011http://dx.doi.org/10.1016/j.isprsjprs.2013.06.011]
Dou A X, Ma Z J, Huang W L, Wang X Q and Yuan X X. 2013. Automatic identification approach of building damages caused by earthquake based on airborne LiDAR and multispectral imagery. Remote Sensing Information, 28(4): 103-109
窦爱霞, 马宗晋, 黄文丽, 王晓青, 袁小祥. 2013. 基于机载LiDAR和多光谱图像的建筑物震害自动识别方法. 遥感信息, 28(4): 103-109 [DOI: 10.3969/j.issn.1000-3177.2013.04.018http://dx.doi.org/10.3969/j.issn.1000-3177.2013.04.018]
Editorial Department of Satellite Application. 2014. The application of remote sensing develops in depth. Satellite Application, (6): 1
《卫星应用》编辑部. 2014. 遥感应用向纵深发展. 卫星应用, (6): 1
Fan Y D and Wu W. 2016. The successful launch of “Gaofen-4” has helped the cause of disaster prevention and mitigation .Disaster Reduction in China, (2):48-49
范一大, 吴玮. 2016. “高分四号”发射成功助力防灾减灾事业. 中国减灾, (2):48-49 [DOI: 10.3969/j.issn.1002-4549.2016.03.010http://dx.doi.org/10.3969/j.issn.1002-4549.2016.03.010]
Forestier G, Puissant A, Wemmert C and Gançarski P. 2012. Knowledge-based region labeling for remote sensing image interpretation. Computers, Environment and Urban Systems, 36(5): 470-480 [DOI: 10.1016/j.compenvurbsys.2012.01.003http://dx.doi.org/10.1016/j.compenvurbsys.2012.01.003]
Gamba P and Casciati F. 1998. GIS and image understanding for near-real-time earthquake damage assessment: remote sensing and GIS for hazards. Photogrammetric Engineering and Remote Sensing, 64(10): 987-994[DOI:10.1117/1.482668http://dx.doi.org/10.1117/1.482668]
Gamba P, Dell’Acqua F and Odasso L. 2007. Object-oriented building damage analysis in VHR optical satellite images of the 2004 tsunami over Kalutara, Sri Lanka//2007 Urban Remote Sensing Joint Event. Paris: IEEE: 1-5 [DOI: 10.1109/URS.2007.371787http://dx.doi.org/10.1109/URS.2007.371787]
Gong L X, Li Q, Zhang J F, Zeng Q M, Liu M Z and Li C L. 2013. Object-oriented detection of earthquake building damages. Earthquake, 33(2): 109-114
龚丽霞, 李强, 张景发, 曾琪明, 刘明众, 李成龙. 2013. 面向对象的房屋震害变化检测方法. 地震, 33(2): 109-114 [DOI: 10.3969/j.issn.1000-3274.2013.02.014http://dx.doi.org/10.3969/j.issn.1000-3274.2013.02.014]
Goodenough D G, Goldberg M, Plunkett G and Zelek J. 1987. An expert system for remote sensing. IEEE Transactions on Geoscience and Remote Sensing, GE-25(3): 349-359 [DOI: 10.1109/TGRS.1987.289805http://dx.doi.org/10.1109/TGRS.1987.289805]
Grant L B, Mueller K J, Gath E M, Cheng H, Edwards R L, Munro R and Kennedy G L. 1999. Late Quaternary uplift and earthquake potential of the San Joaquin Hills, Southern Los Angeles Basin, California. Geology, 27(11): 1031-1034 [DOI: 10.1130/0091-7613(1999)027<1031:LQUAEP>2.3.CO;2http://dx.doi.org/10.1130/0091-7613(1999)027<1031:LQUAEP>2.3.CO;2]
Guida R, Iodice A and Riccio D. 2010. Monitoring of collapsed built-up areas with high resolution SAR images//2010 IEEE International Geoscience and Remote Sensing Symposium. Honolulu: IEEE: 2422-2425 [DOI: 10.1109/IGARSS.2010.5650083http://dx.doi.org/10.1109/IGARSS.2010.5650083]
Guo H D, Liu L Y and Fan X T. 2011.Study of earth observation for disaster reduction in Wenchuan and Yushu earthquakes. Geological Journal of China Universities, 17(1):12
郭华东, 刘良云, 范湘涛. 2011. 对地观测技术用于汶川和玉树地震灾害的研究. 高校地质学报, 17(1):12 [DOI:10.3969/j.issn.1006-7493.2011.01.001http://dx.doi.org/10.3969/j.issn.1006-7493.2011.01.001]
Guo H D, Lu L L and Ma J W. 2009. An improved auto matic detection method for earthquake-collapsed buildings rom ADS40 image. Chinese Science Bulletin, 54(17): 2581-2585: 3303-3307
郭华东, 鹿琳琳, 马建文. 2009. 一种改进的地震灾害倒塌房屋遥感信息自动识别方法. 科学通报, 54(17): 2581-2585[DOI::10.1007/s11434-009-0461-3http://dx.doi.org/10.1007/s11434-009-0461-3]
Guo H D, Wang X Y, Li X W, Liu G, Zhang L and Yan S Y. 2010. Yushu earthquake synergic analysis using multimodal SAR datasets. Chinese Science Bulletin, 55(31): 3499-3503
郭华东, 王心源, 李新武, 刘广, 张露, 阎世勇. 2010. 多模式SAR玉树地震协同分析. 科学通报, 55(13): 1195-1199[DOI: 10.1007/s11434-010-0292-2http://dx.doi.org/10.1007/s11434-010-0292-2]
Hagi T and Sun Y H. 1988. Earthquake and city. Recent Developments in World Seismology, (7): 39-40
萩原尊礼, 孙永华. 1988. 地震与城市. 国际地震动态, (7): 39-40[DOI: CNKI:SUN:GJZT.0.1988-07-013http://dx.doi.org/CNKI:SUN:GJZT.0.1988-07-013]
Hoffmann J. 2007. Mapping damage during the Bam (Iran) earthquake using interferometric coherence. International Journal of Remote Sensing, 28(6): 1199-1216 [DOI: 10.1080/01431160600928567http://dx.doi.org/10.1080/01431160600928567]
Hu G J, Li S Z and Hu H Y. 2009. A data transmission system of earth observation satellite and the design of satellite earth link. Remote Sensing Information, 1:66-69,74
胡国军, 李世忠, 胡海彦. 2009 一种对地观测卫星的数据传输系统及星地链路设计. 遥感信息, 1: 66-69,74[DOI: 10.3969/j.issn.1000-3177.2009.01.013http://dx.doi.org/10.3969/j.issn.1000-3177.2009.01.013]
Huyck C K, Adams B J, Cho S, Chung H C and Eguchi R T. 2005. Towards rapid citywide damage mapping using neighborhood edge dissimilarities in very high-resolution optical satellite imagery— application to the 2003 Bam, Iran, earthquake. Earthquake Spectra, 21(S1): 255-266 [DOI: 10.1193/1.2101907http://dx.doi.org/10.1193/1.2101907]
Ishii M, Goto T, Sugiyama T, Saji H and Abe K. 2002. Detection of earthquake damaged areas from aerial photographs by using color and edge information//Proceedings of the 5th Asian Conference on Computer Vision. Melbourne，Australia: 23-25
Ito Y, Hosokawa M, Lee H and Liu J G. 2000. Extraction of damaged regions using SAR data and neural networks//Proceeding of 19th International Society for Photogrammetry and Remote Sensing (ISPRS) Conference. Amsterdam: 156-163
Jin D J. 2012. Methods of extracting building damage from high resolution SAR image. Beijing: Institute of Earthquake Forecasting
金鼎坚. 2012. 高分辨率SAR影像建筑物震害信息提取方法研究. 北京: 中国地震局地震预测研究所
Kohiyama M and Yamazaki F. 2005. Damage detection for 2003 Bam, Iran, earthquake using Terra-ASTER satellite imagery. Earthquake Spectra, 21(S1): 267-274 [DOI: 10.1193/1.2098947http://dx.doi.org/10.1193/1.2098947]
Li D R. 2009. Intelligent earth observation systems and earthquake relief. Science of Surveying and Mapping, 34(1): 8-10
李德仁. 2009. 对地观测与抗震救灾. 测绘科学, 34(1): 8-10 [DOI: 10.3771/j.issn.1009-2307.2009.01.001http://dx.doi.org/10.3771/j.issn.1009-2307.2009.01.001]
Li D R, Wang M, Shen X and Dong Z P. 2017. From earth observation satellite to earth observation brain. Geomatics and Information Science of Wuhan University, 42(2): 143-149
李德仁, 王密, 沈欣, 董志鹏. 2017. 从对地观测卫星到对地观测脑. 武汉大学学报(信息科学版), 42(2): 143-149 [DOI: 10.13203/j.whugis20160526http://dx.doi.org/10.13203/j.whugis20160526]
Li P J, Xu H Q, Liu S A and Guo J C. 2009. Urban building damage detection from very high resolution imagery using one-class SVM and spatial relations//2009 IEEE International Geoscience and Remote Sensing Symposium. Cape Town: IEEE: V-112-V-114 [DOI: 10.1109/IGARSS.2009.5417719http://dx.doi.org/10.1109/IGARSS.2009.5417719]
Li Q, Zhang J F, Gong L X, Xue T F and Jiang H B. 2018. Extraction of earthquake-collapsed buildings based on correlation change detection of multi-texture features in SAR images. Journal of Remote Sensing, 22(S1): 128-138
李强, 张景发, 龚丽霞, 薛腾飞, 蒋洪波. 2018. SAR图像纹理特征相关变化检测的震害建筑物提取. 遥感学报, 22(S1): 128-138 [DOI: 10.11834/jrs.20187185http://dx.doi.org/10.11834/jrs.20187185]
Li Q. 2018. Study on key technology of earthquake emergency using multi-mode remote sensing data. Harbin: Institute of Engineering Mechanics, China Earthquake Administration
李强. 2018. 多模式遥感数据地震应急关键技术研究. 哈尔滨: 中国地震局工程力学研究所
Li Q, Zhang J F and Luo Y. 2019. Recognition of earthquake-induced landslide and spatial distribution patterns triggered by the Jiuzhaigou earthquake in August 8, 2017. JOURNAL OF REMOTE SENSING, 23(4):11
李强, 张景发, 罗毅. 2019. 2017年"8.8"九寨沟地震滑坡自动识别与空间分布特征. 遥感学报, 2019, 23(4):11 [DOI:10.11834/jrs.20197345http://dx.doi.org/10.11834/jrs.20197345]
Li Q, Gong L X and Zhang J F. 2019. A correlation change detection method integrating PCA and multi- texture features of SAR image for building damage detection. European Journal of Remote Sensing, 52(1): 435-447 [DOI: 10.1080/22797254.2019.1630322http://dx.doi.org/10.1080/22797254.2019.1630322]
Li Q, Jiao Q S and Zhang J F. 2016. Research on building extraction of earthquake damage of ground LiDAR point cloud based on object-oriented. Science Technology and Engineering, 16(19): 244-249
李强, 焦其松, 张景发. 2016. 基于地面激光雷达技术点云的北川县城震害建筑物提取研究. 科学技术与工程, 16(19): 244-249 [DOI: 10.3969/j.issn.1671-1815.2016.19.042http://dx.doi.org/10.3969/j.issn.1671-1815.2016.19.042]
Li Q and Zhang J F. 2013. Extraction of building information from high resolution images based on CART decision tree. Earthquake, 33(2): 96-102
李强, 张景发. 2013. 基于CART决策树提取高分辨率遥感影像建筑物信息. 地震, 33(2): 96-102 [DOI: 10.3969/j.issn.1000-3274.2013.02.012http://dx.doi.org/10.3969/j.issn.1000-3274.2013.02.012]
Li S J and Liu M. 2018. Application of satellite remote sensing in emergency monitoring of major earthquake disaster in China. City and Disaster Reduction, (4): 7-10
李素菊, 刘明. 2018. 卫星遥感在我国重大地震灾害应急监测中的应用. 城市与减灾, (4): 7-10[DOI: CNKI:SUN:CSJZ.0.2018-04-003http://dx.doi.org/CNKI:SUN:CSJZ.0.2018-04-003]
Liu J H. 2003. A method study on automatic recognition and classification of earthquake-caused building damage in cities using remote Sensing. Beijing: Institute of Geology, China Earthquake Administrator
柳稼航. 2003. 利用遥感技术进行城市建筑物震害的自动识别与分类方法研究. 北京: 中国地震局地质研究所
Liu Y H, Qu C Y, Shan X J, Song X G, Zhang G F and Zhang G H. 2010. Application of SAR data to damage identification of the Wenchuan earthquake. Acta Seismologica Sinica, 32(2): 214-223
刘云华, 屈春燕, 单新建, 宋小刚，张桂芳，张国宏. 2010. SAR遥感图像在汶川地震灾害识别中的应用. 地震学报, 32(2): 214-223[DOI: 10.3969/j.issn.0253-3782.2010.02.009http://dx.doi.org/10.3969/j.issn.0253-3782.2010.02.009]
Mathieu B, Oustaloup A and Lanusse P. 1996. Third generation CRONE control: generalized template and curvilinear template//Symposium on Control Optimization and Supervision. IEEE, Lille: 149-155.
Matsuoka M and Yamazaki F. 2000. Use of interferometric satellite SAR for earthquake damage detection//Proceedings of 6th International Conference on Seismic Zonation. Earthquake Engineering Research Institute: 103-108
Matsuoka M and Yamazaki F. 2004a. Use of SAR intensity imagery for earthquake damage detection//Proceedings of the 2nd International Workshop on Remote Sensing for post-Disaster Response. Newport Beach: IEEE: 7-8
Matsuoka M and Yamazaki F. 2004b. Use of satellite SAR intensity imagery for detecting building areas damaged due to earthquakes. Earthquake Spectra, 20(3): 975-994 [DOI: 10.1193/1.1774182http://dx.doi.org/10.1193/1.1774182]
Matsuoka M and Yamazaki F. 2006. Use of SAR imagery for monitoring areas damaged due to the 2006 Mid Java, Indonesia Earthquake//Proceedings of 4th International Workshop on Remote Sensing for Disaster Response. Cambridge, UK：25-26
Miao L T. 1990. Research on earthquake emergency work. Recent Developments in World Seismology, (11): 34-37
苗良田. 1990. 关于地震应急工作的研究. 国际地震动态, (11): 34-37
Mitomi H, Yamazaki F and Matsuoka M. 2001. Development of automated extraction method for building damage area based on maximum likelihood classifier//Proceedings of the 8th International Conference on Structural Safety and Reliability. California: Newport Beach, CA(US), Swets & Zeitlinge: 2430-2442
Miura H, Modorikawa S and Chen S H. 2012. Texture analysis of high-resolution satellite images for damage detection in the 2010. Haiti Earthquake .Journal of Jaee, 12(6): 2-20[DOI: 10.5610/jaee.12.6_2http://dx.doi.org/10.5610/jaee.12.6_2]
Nie G Z, An J W and Deng Y. 2012. Advances in earthquake emergency disaster service. Seismology and Geology, 34(4): 782-791
聂高众, 安基文, 邓砚. 2012. 地震应急灾情服务进展. 地震地质, 34(4): 782-791 [DOI: 10.3969/j.issn.0253-4967.2012.04.020http://dx.doi.org/10.3969/j.issn.0253-4967.2012.04.020]
Peng L, Xu S N, Mei J J and Su F H. 2017. Earthquake-induced landslide recognition using high-resolution remote sensing images. Journal of Remote Sensing, 21(4): 509-518
彭令, 徐素宁, 梅军军, 苏凤环. 2017. 地震滑坡高分辨率遥感影像识别. 遥感学报, 21(4): 509-518 [DOI: 10.11834/jrs.20176176http://dx.doi.org/10.11834/jrs.20176176]
Rathje E M, Woo K S, Crawford M and Neuenschwander A. 2005. Earthquake damage identification using multi-temporal high-resolution optical satellite imagery//Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium. Seoul: IEEE: 5045-5048 [DOI: 10.1109/IGARSS.2005.1526812http://dx.doi.org/10.1109/IGARSS.2005.1526812]
Rensink R A. 2002. Change detection. Annual Review of Psychology, 53: 245-277 [DOI: 10.1146/annurev.psych.53.100901.135125http://dx.doi.org/10.1146/annurev.psych.53.100901.135125]
Ren F. 2017. Research on earthquake disaster assessment based on satellite remote sensing technology. Technical Information, 15(19): 8-10
任峰. 2017. 基于卫星遥感技术的地震灾害评估研究. 科技资讯, (19): 8-10[DOI: 10.16661/j.cnki.1672-3791.2017.19.008http://dx.doi.org/10.16661/j.cnki.1672-3791.2017.19.008]
Ridd M K and Liu J J. 1998. A comparison of four algorithms for change detection in an urban environment. Remote Sensing of Environment, 63(2): 95-100 [DOI: 10.1016/S0034-4257(97)00112-0http://dx.doi.org/10.1016/S0034-4257(97)00112-0]
Sakamoto M, Takasago Y, Uto K, Kakumoto S, Kosugi Y and Doihara T. 2004. Automatic detection of damaged area of Iran earthquake by high-resolution satellite imagery//2004 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Anchorage: IEEE: 1418-1421 [DOI: 10.1109/IGARSS.2004.1368685http://dx.doi.org/10.1109/IGARSS.2004.1368685]
Sato R, Soma K, Yajima Y, Yamaguchi Y and Yamada H. 2007. Classification of stricken residential houses by the Mid Niigata Prefecture Earthquake based on POLSAR image analysis//2007 IEEE International Geoscience and Remote Sensing Symposium. Barcelona: IEEE: 200-203 [DOI: 10.1109/IGARSS.2007.4422764http://dx.doi.org/10.1109/IGARSS.2007.4422764]
Shao Y, Zhao Z M, Huang F X, Xiao Q, Wang Y X and Zhang F L. 2016. Precise emergency service system construction and demonstration through synergy observation of spaceborne, airborne, and ground remote sensing. Journal of Remote Sensing, 20(6): 1485-1490
邵芸, 赵忠明, 黄富祥, 肖青, 王宇翔, 张风丽. 2016. 天空地协同遥感监测精准应急服务体系构建与示范. 遥感学报, 20(6): 1485-1490 [DOI: 10.11834/jrs.20166368http://dx.doi.org/10.11834/jrs.20166368]
Stefanov W L, Ramsey M S and Christensen P R. 2001. Monitoring urban land cover change: an expert system approach to land cover classification of semiarid to arid urban centers. Remote Sensing of Environment, 77(2): 173-185 [DOI: 10.1016/S0034-4257(01)00204-8http://dx.doi.org/10.1016/S0034-4257(01)00204-8]
Stramondo S, Bignami C, Chini M, Pierdicca N and Tertulliani A. 2006. Satellite radar and optical remote sensing for earthquake damage detection: results from different case studies. International Journal of Remote Sensing, 27(20): 4433-4447 [DOI: 10.1080/01431160600675895http://dx.doi.org/10.1080/01431160600675895]
Stramondo S, Chini M, Salvi S, Bignami C, Zoffoli S and Boschi E. 2008. Ground deformation imagery of the May Sichuan earthquake. Eos Transactions American Geophysical Union, 89(37): 341-342 [DOI: 10.1029/2008EO370002http://dx.doi.org/10.1029/2008EO370002]
Suchenwirth L, Förster M, Cierjacks A, Lang F and Kleinschmit B. 2012. Knowledge-based classification of remote sensing data for the estimation of below- and above-ground organic carbon stocks in riparian forests. Wetlands Ecology and Management, 20(2): 151-163 [DOI: 10.1007/s11273-012-9252-8http://dx.doi.org/10.1007/s11273-012-9252-8]
Sui H G. 2013. On the challenge of real-time processing of remote sensing data in disaster emergency response. Disaster Reduction in China, 12X: 28-29
眭海刚. 2013. 论灾害应急响应遥感数据实时处理面临的挑战. 中国减灾, 12X: 28-29[DOI:CNKI:SUN:ZGJI.0.2013-24-011]
Sui H G, Feng W Q, Li W Z, Sun K M and Xu C. 2018. Review of change detection methods for multi-temporal remote sensing imagery. Geomatics and Information Science of Wuhan University，43(12)：1885-1898.
眭海刚, 冯文卿, 李文卓, 孙开敏，徐川. 2018. 多时相遥感影像变化检测方法综述. 武汉大学学报：信息科学版，43(12)：1885-1898., 43(12):14[ DOI:10.13203/j.whugis20180251http://dx.doi.org/10.13203/j.whugis20180251]
Tan Q Q, Liu Q and Wang Z Y. 2013. Rapid production technology of earthquake emergency thematic map based on high-resolution remote sensing image//Satellite Navigation and Positioning and Beidou System Application 2013—Beidou Brilliant China. China Satellite Navigation and Positioning Association; China Disaster Prevention Association
谭庆全, 刘群, 王占英. 2013. 基于高分辨率遥感影像的地震应急专题图快速制作技术// 卫星导航定位与北斗系统应用2013——应用北斗 光彩中国. 中国卫星导航定位协会;中国灾害防御协会
Tomowski D, Klonus S, Ehlers M, Michel U and Reinartz P. 2010. Change visualization through a texture-based analysis approach for disaster applications//ISPRS Proceedings, Seiten 1-6. SymposiumISPRSCommission VII. Vienna, Austria: 263-268
Tong L H, Cheng L, Li M C, Chen Y M, Wang Y F and Zhang W. 2013. Extraction of building contours and corners from terrestrial LiDAR data. Journal of Image and Graphics, 18(7): 876-883
童礼华, 程亮, 李满春, 陈焱明, 王亚飞, 张雯. 2013. 地面LiDAR数据中建筑轮廓和角点提取. 中国图象图形学报, 18(7): 876-883 [DOI: 10.11834/jig.20130718http://dx.doi.org/10.11834/jig.20130718]
Turker M and San B T. 2004. Detection of collapsed buildings caused by the 1999 Izmit, turkey earthquake through digital analysis of post-event aerial photographs. International Journal of Remote Sensing, 25(21): 4701-4714 [DOI: 10.1080/01431160410001709976http://dx.doi.org/10.1080/01431160410001709976]
Tzeng Y C, Chiu S H, Chen D and Chen K S. 2007. Change detections from SAR images for damage estimation based on a spatial chaotic model//2007 IEEE International Geoscience and Remote Sensing Symposium. Barcelona: IEEE: 1926-1930 [DOI: 10.1109/IGARSS.2007.4423203http://dx.doi.org/10.1109/IGARSS.2007.4423203]
Vu T T, Matsuoka M and Yamazaki F. 2005. Preliminary results in development of an object-based image analysis method for earthquake damage assessment //3rd International Workshop on Remote Sensing for Post-Disaster Response. Chiba，Japan: 128
Wang C, Zhang Y S, Wang X and Yu Y. 2020.Remote sensing image change detection method based on deep neural networks. Journal of Zhejiang University（Engineering Science）, 54(11)：2138-2148
王昶，张永生，王旭，于英. 2020. 基于深度学习的遥感影像变化检测方法.浙江大学学报(工学版)54(11)：2138-2148[DOI:10.3785/j.issn.1008-973X.2020.11.009http://dx.doi.org/10.3785/j.issn.1008-973X.2020.11.009]
Wang D X. 2016. The reform of disaster management system in Japan: in view of the aftermath of "March 11 East Japan earthquake. Nankai Journal (Philosophy Literature and Social Science Edition), (6): 86-92
王德迅. 2016. 日本灾害管理体制改革研究——以“3·11东日本大地震”为视角. 南开学报(哲学社会科学版), (6): 86-92
Wang L T, Wang S X and Zhou Y.2010. Urgent monitoring and analysis on Yushu Earthquake using remote sensing. Journal of Remote Sensing, (5):1053-1066
王丽涛, 王世新, 周艺. 2010. 青海玉树地震灾情遥感应急监测分析. 遥感学报, (5):1053-1066 [DOI:CNKI:SUN:YGXB.0.2010-05-018http://dx.doi.org/CNKI:SUN:YGXB.0.2010-05-018]
Wang H L and Bai R Z. 1992. Monitoring ground temperature anomalies in earthquake areas with meteorological satellites: a case study of two earthquakes in Datong, Shanxi Province. Remote Sensing Information, (2):6-7
王宏禄, 白锐峥. 用气象卫星监测地震区地温异常:以山西大同两次地震为例. 遥感信息, 1992(2):6-7
Wang L. 1988. Discussion on regional crustal stability in Yingkou area from the structural interpretation of remote sensing images. Land Resources, (4):74-82
王丽. 1988. 从遥感影像的构造解译讨论营口地区区域地壳稳定性. 国土资源, (4):74-82
Wang M, Wang J, Jiang Y and Ma X B. 2010. The earthquake survey of geological hazards and spatial analysis in Wenchuan County. Journal of Geo-information Science, (4):480-486
王猛, 王军, 江煜. 2010. 汶川地震地质灾害遥感调查与空间特征分析. 地球信息科学学报, (4): 480-486[DOI:CNKI:SUN:DQXX.0.2010-04-007http://dx.doi.org/CNKI:SUN:DQXX.0.2010-04-007]
Wang S. 2015. Research on Earthquake Induced Landsides Extraction from Multi-source Remote Sensing Data in the Wenchuan. China University of Geosciences (Beijing)
王赛. 2015. 基于多源遥感数据的汶川地震型滑坡信息提取研究. 北京：中国地质大学(北京)
Wang T L and Jin Y Q. 2012. Post-earthquake building damage assessment using multi-mutual information from pre-event optical image and postevent SAR image. IEEE Geoscience and Remote Sensing Letters, 9(3):452-456[DOI:10.1109/LGRS.2011.2170657http://dx.doi.org/10.1109/LGRS.2011.2170657]
Wang X Q，Dou A X and Wang L. 2015.RS-based assessment of seismic intensity of the 2013 Lushan，Sichuan， MsChina7.0 earthquake. Chinese Journal of Geophysics，58（1）：163-171
王晓青, 窦爱霞, 王龙. 2015. 2013年四川芦山7.0级地震烈度遥感评估. 地球物理学报, 58(1):163-171[ DOI: 10.6038/cjg20150114http://dx.doi.org/10.6038/cjg20150114]
Wang Y, Wang X Q, Dou A X, Sun S M and Fu C. 2012. Object-oriented remote sensing data classification method application in earthquake damage rapid extraction. Recent Developments in World Seismology. (6):1-5
王岩, 王晓青, 窦爱霞. 2012. 面向对象遥感分类方法在震害快速提取中的应用. 国际地震动态, (6):1-5 [DOI: 10.3969/j.issn.0253-4975.2012.06.288http://dx.doi.org/10.3969/j.issn.0253-4975.2012.06.288]
Wang X Q, Dou A X, Sun G Q, Ding X, Wang L and Yuan X X. 2013. Intensity assessment of the 2010 Yushu MS7.1 earthquake based on synthetic seismic damage index. Earthquake, 33(2): 1-10
王晓青, 窦爱霞, 孙国清, 丁香, 王龙, 袁小祥. 2013. 基于综合震害指数的玉树地震烈度遥感评估研究. 地震, 33(2): 1-10 [DOI: 10.3969/j.issn.1000-3274.2013.02.001http://dx.doi.org/10.3969/j.issn.1000-3274.2013.02.001]
Wei Y M, Li J N, Chen Y and Gao J F. 2021. Research on optical remote sensing characteristics of coseismic surface rupture of different types of seismogenic faults. Quaternary Sciences, 41(6): 1513-1531
魏永明, 李剑南, 陈玉, 高锦风. 2021. 不同类型发震断层的同震地表破裂光学遥感特征研究. 第四纪研究, 41(6): 1513-1531[DOI:10.11928/j.issn.1001-7410.2021.06.01http://dx.doi.org/10.11928/j.issn.1001-7410.2021.06.01]
Wen X, Zhou B and Yan C H. 2014. Building damage detection based on object-oriented classification method--a case study in Yushu earthquake. Seismological and Geomagnetic Observation and Research, 35(5/6): 134-143
文翔, 周斌, 阎春恒. 2014. 遥感分类方法在建筑物震害提取中的应用(以玉树地震为例). 地震地磁观测与研究, 35(5/6): 134-143 [DOI: 10.3969/j.issn.1003-3246.2014.05/06.025http://dx.doi.org/10.3969/j.issn.1003-3246.2014.05/06.025]
Wu M C, Liu J and Cosgrove J. 2014. Modelling of Yingxiu–Beichuan fault zone based on refined DInSAR data of 2008 Wenchuan earthquake. Tectonophysics, 630:193-207 [DOI:10.1016/j.tecto.2014.05.024http://dx.doi.org/10.1016/j.tecto.2014.05.024]
Wu H J, Guo M Z and Zhang J. 2006. Application of remote sensing technology in the field of earthquake prevention and disaster reduction. Earthquake Engineering and Engineering Vibration, 26(3):267-269
吴焕娟, 郭明珠, 张皎. 2006. 遥感技术在防震减灾领域中的应用. 地震工程与工程振动, 26(3):267-269[ DOI:10.3969/j.issn.1000-1301.2006.03.074http://dx.doi.org/10.3969/j.issn.1000-1301.2006.03.074]
Xing H L, Jiang T and Li W Y. 2005. Key problems on developing and revising the urban emergency response plan of destructive earthquakes. Earthquake, 25(3): 115-122
邢海灵, 蒋通, 李文艺. 2005. 城市破坏性地震应急预案的编制与修订要点探讨. 地震, 25(3): 115-122 [DOI: 10.3969/j.issn.1000-3274.2005.03.017http://dx.doi.org/10.3969/j.issn.1000-3274.2005.03.017]
Xu C J, Lin D L and Wen Y M. 2010. Extract and Analysis Surface Deformation Caused by Wenchuan Mw7.9 Earthquake from InSAR Data. Geomatics and Information Science of Wuhan University, 35(10): 1138-1142
许才军, 林敦灵, 温扬茂. 2010. 利用InSAR数据的汶川地震形变场提取及分析. 武汉大学学报(信息科学版), 35(10): 1138-1142
Xu J H, Nie G Z and Liu W Q. 2010. Multiple and Heterogeneous Earthquake Disaster Information Classification and Code. Journal of Catastrophology, 25(B10): 286-290
徐敬海, 聂高众, 刘伟庆. 2010. 多源异构地震灾情分类与编码研究. 灾害学, 2010, 25(B10): 286-290[ DOI:10.3969/j.issn.1000-811X.2010.z1.062http://dx.doi.org/10.3969/j.issn.1000-811X.2010.z1.062]
Xue T F. 2017. Earthquake damaged buildings extraction from SAR images using change detection technology based on multiple features. Harbin: Institute of Engineering Mechanics, China Earthquake Administration (薛腾飞. 2017. 基于SAR多特征变化检测的震害建筑物提取研究. 哈尔滨: 中国地震局工程力学研究所)
Xue T F, Zhang J F and Li Q. 2016. Extraction of earthquake damage buildings from multi-source remote sensing data based on correlation change detection and object-oriented classification techniques. Acta Seismologica Sinica, 38(3): 496-505
薛腾飞, 张景发, 李强. 2016. 基于相关变化检测与面向对象分类技术的多源遥感图像震害信息提取. 地震学报, 38(3): 496-505 [DOI: 10.11939/jass.2016.03.017http://dx.doi.org/10.11939/jass.2016.03.017]
Yang Z and Cheng J Y. 1993. Survey of earthquake disasters by airborne remote sensing in Nanchang and Gengma Area. Remote Sensing for Land & Resources, 5(1): 17-22
杨喆, 程家喻. 澜沧──耿马地震灾情的航空遥感调查. 国土资源遥感, 1993, 5(1):17-22[DOI: 10.6046/gtzyyg.1993.01.04http://dx.doi.org/10.6046/gtzyyg.1993.01.04]
Ye X，Wang J and Qin Q M. 2016. Damaged building detection based on GF-1 satellite remote sensing image: a case study for Nepal Ms8.1 earthquake. Acta Seismologica Sinica，38（3）：477-485
叶昕, 王俊, 秦其明. 2016. 基于高分一号卫星遥感图像的建筑物震害损毁检测研究——以2015年尼泊尔M_S8.1地震为例. 地震学报, (3):477-485[DOI:10.11939/jass.2016.03.015http://dx.doi.org/10.11939/jass.2016.03.015]
Yonezawa C and Takeuchi S. 2001. Decorrelation of SAR data by urban damages caused by the 1995 Hyogoken-Nanbu earthquake. International Journal of Remote Sensing, 22(8): 1585-1600 [DOI: 10.10.1080/01431160118187http://dx.doi.org/10.10.1080/01431160118187]
Yonezawa C, Tomiyama N and Takeuchi S. 2002. Urban damage detection using decorrelation of SAR interferometric data//IEEE International Geoscience and Remote Sensing Symposium. Toronto: IEEE: 2051-2053 [DOI: 10.1109/IGARSS.2002.1026441http://dx.doi.org/10.1109/IGARSS.2002.1026441]
You Z B. 2016. Analysis and reference of emergency response to Kumamoto earthquake in Japan. Administrative Reform, (8):3
游志斌. 2016. 日本熊本地震应急响应分析及借鉴. 行政管理改革, 2016(8):3 [DOI: 10.3969/j.issn.1674-7453.2016.08.013http://dx.doi.org/10.3969/j.issn.1674-7453.2016.08.013]
Yuan X X, Wang X Q, Dou A X, Dong Y F, Wang L and Jin D J. 2012. Terrestrial LiDAR-based 3D modeling analysis of surface rupture caused by Yushu earthquake. Seismology and Geology, 34(1): 39-46
袁小祥, 王晓青, 窦爱霞, 董彦芳, 王龙, 金鼎坚. 2012. 基于地面LiDAR玉树地震地表破裂的三维建模分析. 地震地质, 34(1): 39-46 [DOI: 10.3969/j.issn.0253-4967.2012.01.005http://dx.doi.org/10.3969/j.issn.0253-4967.2012.01.005]
Yusuf Y, Matsuoka M and Yamazaki F. 2001. Damage assessment after 2001 Gujarat earthquake using Landsat-7 satellite images. Journal of the Indian Society of Remote Sensing, 29(1): 17-22 [DOI: 10.1007/BF02989909http://dx.doi.org/10.1007/BF02989909]
Zhai W, Shen H F, Huang C L and Pei W S. 2016. Building earthquake damage information extraction from a single post-earthquake PolSAR image. Remote Sensing, 8(3): 171-185 [DOI: 10.3390/rs8030171http://dx.doi.org/10.3390/rs8030171]
Zhai W. 2016. Acquisition of building seismic disaster information based on single phase full polarization SAR image. Earthquake Research In Shanxi, (1):19-22+45
翟玮. 2016. 基于单时相全极化SAR影像的建筑物震害信息提取. 山西地震, (1):19-22+45[ DOI:CNKI:SUN:SXDZ.0.2016-01-006http://dx.doi.org/CNKI:SUN:SXDZ.0.2016-01-006]
Zhang D C. 1993. Preliminary study on visual interpretation marks of building damages caused by earthquakes on aerophotograph. Earthquake, (1): 26-30
张德成. 1993. 建筑物震害航空照片目视判读标志的初步研究. 地震, (1): 26-30
Zhang H Z, Wang Q, Zeng Q M and Jiao J. 2015. A novel approach to building collapse detection from post-seismic polarimetric SAR imagery by using optimization of polarimetric contrast enhancement//2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Milan: IEEE: 3270-3273 [DOI: 10.1109/IGARSS.2015.7326516http://dx.doi.org/10.1109/IGARSS.2015.7326516]
Zhang J F, Xie L L ang Tao X X. 2002. Change detection of remote sensing image for earthquake damaged buildings and its application in seismic disaster assessment. Journal of Natural Disasters, 11(2):59-64
张景发, 谢礼立, 陶夏新. 2002. 建筑物震害遥感图像的变化检测与震害评估. 自然灾害学报, 11(2):59-64 [DOI:10.3969/j.issn.1004-4574.2002.02.010http://dx.doi.org/10.3969/j.issn.1004-4574.2002.02.010]
Zhang K X, Ye H L, Zhang H J and Yang S Y. 2019. Analysis on rock slope failure and dynamic response induced by earthquake.Quaternary Sciences, 39(6): 1514-1523
张昆祥, 叶海林, 张化杰, 杨淑艳. 2019. 地震诱发岩质边坡破坏及动力响应分析. 第四纪研究, 39(6): 1514-1523 [DOI:10.11928/j.issn.1001-7410.2019.06.18http://dx.doi.org/10.11928/j.issn.1001-7410.2019.06.18]
Zhang W Y, Qin K, Zhang C C, Yang L N and Ma R F. 2007. On feature extraction from remote sensing image based on knowledge. Geospatial Information, 5(1): 66-69
张文元, 秦昆, 张成才, 杨丽娜, 马茹菲. 2007. 基于知识的遥感图像地物提取方法研究. 地理空间信息, 5(1): 66-69 [DOI: 10.3969/j.issn.1672-4623.2007.01.024http://dx.doi.org/10.3969/j.issn.1672-4623.2007.01.024]
Zhang Y M. 2012. Object-Oriented Classification of Polarimetric SAR Imagery Based on Polarimetricand Texture Features. Shandong University of Science and Technology(张艳梅. 2012. 融合极化和纹理特征的SAR影像面向对象分类. 山东科技大学)
Zhao F J and Zhang L. 2009. Object-oriented method for extracting seismic disaster information using remote sensing images—a case study of Wenchuan earthquake. Earthquake, 29(S1): 130-138
赵福军, 张磊. 2009. 面向对象的遥感震害信息提取方法——以汶川地震为例. 地震, 29(S1): 130-138 [DOI: 10.3969/j.issn.1000-3274.2009.z1.018http://dx.doi.org/10.3969/j.issn.1000-3274.2009.z1.018]
Zhao X Y, Hu K, Burns S F and Hu H T. 2019. Correction to: classification and sudden departure mechanism of high-speed landslides caused by the 2008 Wenchuan earthquake. Environmental Earth Sciences, 78(10): 301 [DOI: 10.1007/s12665-019-8287-zhttp://dx.doi.org/10.1007/s12665-019-8287-z]
Zhou C H, Du Y Y and Luo J C. 1996. A description model based on knowledge for automatically recognizing water from Noaa/Avhrr. Journal of Natural Disasters, 5(3): 100-108
周成虎, 杜云艳, 骆剑承. 1996. 基于知识的AVHRR影像的水体自动识别方法与模型研究. 自然灾害学报, 5(3): 100-108[DOI: CNKI:SUN:ZRZH.0.1996-03-015http://dx.doi.org/CNKI:SUN:ZRZH.0.1996-03-015]
Zhu B Q, Wei C J and Zhang Y Z. 1998. The quick extracting of earthquake disaster data by aerial remote sensing survey. Journal of Natural Disasters, 7(1): 34-39
朱博勤, 魏成阶, 张渊智. 1998. 航空遥感地震灾害信息的快速提取. 自然灾害学报, 7(1): 34-39 [DOI: CNKI:SUN:ZRZH.0.1998-01-005http://dx.doi.org/CNKI:SUN:ZRZH.0.1998-01-005]
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中国科学院遥感应用研究所
Aerospace Information Research Institute, Chinese Academy of Sciences
State Key Laboratory of Remote Sensing Science, Beijing Normal University
Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University
Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University
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