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REMOTE SENSING FOR LAND & RESOURCES    2001, Vol. 13 Issue (1) : 42-46     DOI: 10.6046/gtzyyg.2001.01.08
Technology and Methodology |
STUDY ON THE STATISTICAL CHARACTERISTICS OF SEISMIC DISASTER INFORMATION OF BUILDING IN REMOTE SENSING IMAGE
CAO Dai-yong1, SHI Xian-zhong1, ZHANG Jing-fa2
1. China University of Mining and Technology, Beijing 100083, China;
2. Institute of Crustal Dynamics, State Seismological Bureau, Beijing 100085, China
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Abstract  The formation mechanism of seismic disaster information of building in remote sensing image is discussed in the paper. A series of special parameters which reveal the building seismic disaster information are brought forward based on study of the image grey scale and image texture characteristics. Statistical analysis of test image sub-sections of different styles shows the average value, standard deviation and variance of grey scales are the effective indicators for recognition and classification of building seismic disaster in digital images, the texture inverse difference matrix and texture correlation can be used as the supplementary indicators.
Keywords  Soil stalinization      Salinity characteristics      Spectral characteristics      Caka-Gonghe basin       
Issue Date: 02 August 2011
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QI Hao-Ping
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QI Hao-Ping,WENG Yong-Ling,ZHAO Fu-Yue, et al. STUDY ON THE STATISTICAL CHARACTERISTICS OF SEISMIC DISASTER INFORMATION OF BUILDING IN REMOTE SENSING IMAGE[J]. REMOTE SENSING FOR LAND & RESOURCES, 2001, 13(1): 42-46.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2001.01.08     OR     https://www.gtzyyg.com/EN/Y2001/V13/I1/42


[1] 王晓青.航空影像灾害自动识别的初步研究.见:庄逢甘编.中国地方遥感应用进展【M】.北京:宇航出版社,1997.



[2] 丁军,王丹.遥感图像上城市震害信息的获取及其应用【J】.灾害学,1996,(1),82-86.



[3] 陈鑫连.地震灾害的航空遥感信息快速评估与救灾决策【M】.北京:地震出版社,1992.



[4] 宁书年.遥感图像处理与应用【M】.北京:地震出版社,1995.



[5] 洪继光.灰度—梯度共生矩阵纹理分析方法【J】.自动化学报,1984,(1).
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