多源遥感影像融合在太湖蓝藻监测中的应用  

Integrated Application of Multi-sources Remotely Sensed Imagery in Cyanobacteria Bloom Monitoring

作　　者：李亚春 王净[2] 谢志清[3] 谢小萍 

机构地区：[1]江苏省气象服务中心,江苏南京210008 [2]徐州师范大学城市环境学院,江苏徐州221116 [3]江苏省气象科学研究所,江苏南京210008

出　　处：《遥感技术与应用》2013年第4期569-575,共7页Remote Sensing Technology and Application

基　　金：江苏省科技支撑项目(BE2011840);中国气象局新技术推广项目(CMAT2007M30)联合资助

摘　　要：基于空间分辨率分别为1 100m和500m的NOAA/AVHRR和EOS/MODIS遥感数据,考虑遥感影像区域内各像素之间的区域特征,设计了基于小波分析的区域能量融合方法(REFS_wt),低频小波系数采用平均值而高频系数采用区域能量法,并与基于像素灰度值的区域能量法(REFS_pl)进行融合性能比较,结果表明REFS_wt法的融合性能明显优于REFS_pl。将此方法应用于太湖蓝藻监测,将空间分辨率较低的AVHRR影像蓝藻水华信息与较高分辨率的MODIS影像融合,得到较高分辨率的太湖蓝藻水华遥感监测图,融合图像信息量和清晰度都有所提高。It is significant to monitor cyanobacteria bloom accurately and rapidly with remote sensing meth ods by multi-sources satellite data, In this paper,it took NOAA/AVHRR data which has lower spectral resolution of 1 100 m and Terra（Aqua）/MODIS data which has higher spectral resolution of 500 m as the main data sources. A region-based wavelet transform fusion method （REFS_wt） was presented which took the average as the low frequency coefficient and the high frequency coefficient was calculated by regional energy method. Then a comparison was made between the presented method and another image fusion scheme based on regional pixel energy（REFS_pD. The experimental results showed that the REFS_wt method was better than the region-based pixel energy fusion method in improving spectrum quality of re mote sensing images. This studied method has been effectively applied to cyanobacteria bloom monitoring and early-warning for Lake Taihu. And the fused images could preserve all useful information from primi tive images and that the clarity and information quantity were improved.

关 键 词：多源遥感影像 融合 区域特征 蓝藻 太湖 

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