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文章摘要
基于卫星影像的太湖蓝藻水华遥感强度指数和等级划分算法设计
Design of Intensity Index and Build up Degree Classification Algorithm Development for Cyanobacterica Blooms in Lake Taihu Based on Satellite Remote Sensing
  
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中文关键词: 
英文关键词: 
基金项目:国家水环境监测技术体系研究与示范(2009ZX07527-006); 国家科技支撑计划“基于环境一号等国产卫星的环境遥感监测应用技术集成与示范研究”(2008BAC34B07-01)
作者单位
李旭文 江苏省环境监测中心 
牛志春 江苏省环境监测中心 
姜晟 江苏省环境监测中心 
金焰 江苏省环境监测中心 
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中文摘要:
      对太湖地区近10余年来共32景Landsat TM/ETM遥感影像进行大气校正处理,获得地表反射率影像,在这些影像上采集了分布在不同片区、不同发生季节、不同集聚程度的蓝藻水华样区,提取了不同蓝藻水华的可见—近红外波段反射率数据。统计表明蓝藻水华在TM 4波段的反射率有较宽的动态范围,能定量反映蓝藻集聚程度,TM 2也是监测蓝藻水华不可或缺的波段,其与TM 3波段反射率差与蓝藻密度关系密切。设计了蓝藻水华遥感强度CBI指数,提出了划分蓝藻水华等级的遥感算法。
英文摘要:
      32 Landsat TM/ETM scenes of Lake Taihu spanning the past 10 years were atmospherically corrected to generate surface reflectance images, then region of interest(ROIs) were overlaid on cyanobacteria blooms which occurred at various locations on those images, the visible and NIR spectral reflectance means and other statistics information were collected and examined. It was shown TM band 4 spectral reflectance of cyanobacteria blooms usually have wide value range and can be used to quantitatively monitor the build up of cyanobacteria. TM band 2 spectral reflectance also demonstrates similar spectral characteristics and its difference with spectral reflectance at band 3 can indicate cyanobacterica densities in water bodies. A new remote sensing based index, cyanobacterica bloom intensity (CBI), was designed and an algorithm for delineate cyanobacterica severity was put forward.
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