基于RVI分区的淀山湖蓝藻暴发期叶绿素a的遥感估测  

RS Estimation of Chlorophyll-a Concentration Based on RVI Regionalization during Algae Blooming Period in Dianshan Lake

作　　者：顾万花[1] 马蔚纯[1] 周立国[1] 汤琳[2] 怀红燕[2] 

机构地区：[1]复旦大学环境科学与工程系,上海200433 [2]上海市环境监测中心,上海200030

出　　处：《环境科学研究》2011年第6期666-672,共7页Research of Environmental Sciences

基　　金：国家高技术研究发展计划(863)项目(2008AA06Z401);教育部博士点新教师基金项目(2010007120013);中国科学院遥感应用研究所开放基金(OFSLRSS201009)

摘　　要：以淀山湖为研究区域,利用MODIS数据探讨蓝藻暴发期叶绿素a质量浓度〔ρ(Chla)〕的遥感估算方法.为了提高估算精度,解决蓝藻暴发期因ρ(Chla)差异较大而产生的估测模型的参数适应性问题,引入比值植被指数(Ratio VegetationIndex,RVI)分类法,将RVI>0.95的区域界定为高蓝藻含量水体,将RVI≤0.95的区域界定为较清洁水体,并基于分区分别建立遥感估算模型.结果表明,分区后MODIS数据叶绿素a估测模型能更好地映射ρ(Chla)的变化,基于RVI的分类估算方法可以有效地提高淀山湖水体蓝藻暴发期ρ(Chla)的估算精度.The method of estimating chlorophyll-a（Chla） mass concentration during an algae bloom with remote sensing data MODIS was explored with a case study in Dianshan Lake.Ratio Vegetation Index（RVI） was introduced to solve the problem of model parameter adaptability caused by the large differences in Chla concentration during the algae bloom and to improve the estimation precision.Water body where RVI0.95 is defined as concentrated Chla regions and RVI≤0.95 as clean regions,and remote sensing models were then developed for the two regions separately.Study results indicate that the remote sensing model based on MODIS data can better reflect the distribution of Chla after regionalization,and the new algorithm can effectively improve the estimation precision of Chla mass concentration during an algae bloom in Dianshan Lake.

关 键 词：MOIDS 叶绿素A 比值植被指数(RVI) 淀山湖 

分 类 号：X524[环境科学与工程—环境工程]