海岸带信息集成与战略规划研究中心知识库

(1) 中国科学院烟台海岸带研究所

With high temporal and spatial resolutions, HJ-1 CCD data can be used to dynamically monitor Ulva prolifera disaster on a large scale. Atmospheric correction is a basis for Ulva prolifera information extraction, but there is a difference between different atmospheric correction methods when they are used to process the same image. Based on the HJ-1 satellite images generated during the explosive growth period of Ulva prolifera in the central and southern Yellow Sea, the research carries out atmospheric correction by three methods including FLAASH, 6S and COST in a bid to eliminate atmospheric effects, and then extracts Ulva prolifera using NDVI threshold method. By marking off multiple study areas and calculating or analyzing a number of statistics such as spectrum, NDVI, class space, mixed pixel, threshold sensitivity and extraction results, the research compares the effect of three atmospheric correction methods on Ulva prolifera monitoring and provides assistance for the subsequent quantitative monitoring of Ulva prolifera. According to the result, when NDVI threshold method is used for Ulva prolifera information extraction, COST achieves a good monitoring effect, followed by FLAASH and 6S.

HJ-1 CCD数据具有较高的时间分辨率和空间分辨率,可以实现大范围的浒苔灾害动态监测,大气校正是实现浒苔信息提取的基础,但是不同大气校正方法对同一影像的处理结果会有差异。基于黄海中南部浒苔暴发时期的环境卫星影像,采用FLAASH、6S、COST 3种方法分别对其进行大气校正处理以消除大气影响,并运用NDVI阈值法提取浒苔,通过划分多个研究区以及对光谱特征、NDVI、类间距、混合像元、阈值敏感性、提取结果等多个变化量的统计与分析,比较了3种大气校正方法在浒苔提取中的效果,为后续浒苔定量化监测提供了帮助。结果表明:在采用NDVI阈值法提取浒苔信息时,使用COST大气校正会取得良好的提取效果,其次是FLAASH大气校正方法和6S大气校正方法。