基于二阶段算法的HJ-CCD数据过火区制图

利用环境减灾小卫星多光谱数据研究过火区的制图方法,并分析对比了4种植被指数对于过火区的分离性。结果表明:基于可见光和近红外的BAI(Burned Area Index)与GEMI(Global Environment Monitoring Index)指数对于过火区的分离能力较好。在此基础上,采用二阶段识别算法对实验区的过火区进行提取。首先采用严格的阈值提取燃烧较为严重的过火像元,并以此作为第二阶段过火区识别的“种子”点,该阶段以减少误判为目的;第二阶段采用区域生长提取其他过火区域,同时采取较为宽松的阈值作为生长准则,以减少漏判,最后得出过火区边界。精度验证结果表明:该方法提取的过火区误判率为5.5%,漏判率为12.7%。

Burned Area Mapping Using HJ-1A/B CCD Data based on Two-phase Algorithm

The possibility of using HJ-1A/B CCD data for regional burned area mapping with a two-phase algorithm was investigated.Four kinds of vegetation indices were tested for the seperability between burned area and other land types.The result showed that the Burned Area Index (BAI) and Global Environment Monitoring Index (GEMI),based on the reflectance of RED and NIR (Near Infrared) bands of HJ-1A/B CCD,presentel good discrimination capability.Rigid multi-thresholds based on BAI and GEMI were used to discriminate the more severe burned area to minimize the commission error in the first phase.And the “seed” pixels extracted from the first phase were used to generate in the second phase.Loose thresholds were applied as the generation criterion in the second phase to obtain the burned region boundary,and this phase will minimize the omission error.The accuracy assessment showed the burned area commission error was 5.5%,and the omission error was 12.7%.The results underline the feasibility of the two-phase algorithm for regional burned area mapping by HJ-1A/B CCD data.