红树林湿地植被生物量的雷达遥感估算  

Estimating Mangrove Wetland Biomass Using Radar Remote Sensing

作　　者：黎夏[1] 叶嘉安[2] 王树功[3] 刘凯[4] 刘小平[1] 钱峻屏[5] 陈晓越[2] 何执兼[1] 覃朝锋[3] 

机构地区：[1]中山大学地理科学与规划学院,广东广州510275 [2]香港大学城市规划及环境管理研究中心 [3]中山大学环境科学研究所,广东广州510275 [4]中国科学院广州地球化学研究所,广东广州510640 [5]广州地理研究所,广东广州510070

出　　处：《遥感学报》2006年第3期387-396,共10页NATIONAL REMOTE SENSING BULLETIN

基　　金：广东省自然科学基金项目(031647);"985工程"GIS与遥感的地学应用科技创新平台重大项目

摘　　要：根据雷达后向散射系数建立了红树林湿地植被生物量的估算模型,并运用遗传算法确定其中非线性模型的最优参数。对比分析表明,雷达后向散射系数模型比NDVI模型在植被生物量估算中有更高的精度。使用NDVI指数有可能导致某些植被类型的生物量估算出现较大的误差。这是因为一些具有密集冠层的草本植被(例如互花米草等)有比红树林高得多的NDVI值。而雷达遥感所具有的侧视特点及一定的穿透能力能有效地获取植被的垂直信息,大大减低植被生物量估算的误差。Guangdong in south China has the largest area of mangrove wetlands in China. However, the mangrove wetlands have been rapidly diminishing because of the rapid urbanization. Remote sensing can be used to provide important information for the protection of the mangrove wetlands. Traditional optical remote sensing has difficulties in monitoring the wetlands in this region because of frequent cloud covers. The wellknown NDVI index from optical remote sensing has drawbacks in obtaining the trunk information for mangrove forests. In this paper, comparisons were made between the NDVI models and backscatter models in estimating wetland biomass. Regression and analytical models were used to establish the relationships between remote sensing data and wetland biomass. The optimal parameter values for the analytical model were determined by using genetic algorithms. Experiments indicate that the models using radar remote sensing data have significant accuracy improvement in terms of Root Mean-Square Error（ RMSE）. It is found that the use of the single NDVI index may produce serious errors in biomass estimation. The errors occur because some herbaceous species with dense canopy, such as Spartina anglica, may have much higher NDVI values than mangrove forests.

关 键 词：雷达遥感 遗传算法 生物量 红树林湿地 NDVI 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] X87[自动化与计算机技术—控制科学与工程]