不同大气校正方法对浒苔遥感监测效果影响研究  

Effects of Different Atmospheric Correction Methods on Remote Sensing Monitoring Results of Ulva prolifera

作　　者：郑翔宇[1,2] 高志强 许宁[1,2] 徐福祥[1,2] 艾金泉 

机构地区：[1]中国科学院烟台海岸带研究所,山东烟台264003 [2]中国科学院大学,北京100049 [3]华东师范大学,上海200062

出　　处：《环境科学与技术》2017年第12期284-291,共8页Environmental Science & Technology

基　　金：青岛海洋科学与技术国家实验室鳌山科技创新计划项目(2016ASKJ02);中国科学院战略性先导科技专项(A类)(XDA1102 0000);中国科学院重点部署项目(KZZD-EW-14);科技部基础支撑项目(2014FY210600)

摘　　要：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。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 ef-fects, 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.

关 键 词：环境卫星 大气校正 浒苔 NDVI FLAASH 6S COST 

分 类 号：X55[环境科学与工程—环境工程]