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摘要： 洪涝灾害范围是表征洪涝灾害时空分布特征的关键物理参数,是洪涝灾害灾情评估的主要内容和重要基础。充分利用遥感技术、地面站网观测数据和实地调查核查等手段,是当前“天、空、地、现场”一体化开展洪涝灾害范围动态监测的研究前沿。针对洪涝灾害范围实时动态演变过程监测时效性受数据和信息提取效率制约的问题,提出了基于HJ\|1 CCD数据利用区域生长算法的洪涝灾害范围提取模型。在研究多种地物目标的影像特征与光谱响应特征基础上,采用区域生长算法对2013年汛期黑龙江省抚远县洪涝灾害范围进行识别和判定。结果表明:汛期内稳定高频次获取的HJ\|1 CCD数据能为洪涝灾害范围识别和动态演变过程监测提供数据保障。区域生长法提取集中连片水体的效率高,能够将过去目视解译、人工勾画需要5 h的工作量缩短到10 min之内;提取结果宏观性强,在影响范围大的洪涝灾害范围动态监测业务中发挥着重要的作用。 关键词： 洪涝范围;  HJ-1 CCD;  区域生长;  动态监测     Abstract: Flood disaster extent is a key physical parameter to characterize flood disaster temporal and spatial distribution,and it is the major content and basis of disaster losses assessment.It is a preceding study to perform space\|airborne\|ground\|field integrated flood extent dynamics monitoring using remote sensing technique,ground observation network data and filed surveys.A flood disaster extent extraction model using HJ\|1 CCD data was developed on the basis of region growing algorithm.This model was used to improve the efficiency of flood disaster extent real time dynamic evolution monitoring which resulted from the data acquisition and information extraction efficiency.First,spatial distributions and spectral response characteristics of ground targets were analyzed.Then flood disaster in Fuyuan county of Heilongjiang province was chose as an example to use the region growing algorithm for identification and determination of the disaster extent.The results indicated that the stable and high\|frequency acquisition capacity of HJ\|1 CCD data can support flood disaster extent identification and dynamic evolution monitoring during the flood season.The region growing method can extract concentrated water with high efficiency.Which cost 10 minutes to finish the work,thus that could cost 5 hours by visual interpretation and artificial sketch in the past.The extraction method plays an important role in a large area of flood disaster dynamic monitoring.

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