基于ENVISAT ASAR数据的东洞庭湖湿地植被遥感监测研究

针对湿地资源监测的需要，以东洞庭湖湿地为研究对象，开展基于ENVISAT ASAR数据的湿地植被遥感监测研究。湿地遥感影像分类是湿地遥感研究的一大难题，通过分析雷达影像的后向散射系数发现，由多时相的同极化、交叉极化波段合成的雷达影像对湿地地物的区分能力最强。研究表明：将基于原图像的灰度级共生矩阵所提取的Contrast纹理特征与滤波后图像的灰度特征组合用于分类，以此实现相干斑噪声的抑制，同时减少地物固有结构信息的损失，实验结果证明该方法可以提高湿地分类精度，其总体精度达到8759%，Kappa值为0822 8，将东洞庭湖湿地划分为水体、芦苇（荻）滩地、草滩地（苔草、虉草等）、森林滩地（杨树、柳树等）、优势种不明显的植物滩地和沉水植物、裸露泥滩地.

STUDY ON THE REMOTE SENSING MONITORING OF WETLAND VEGETATION IN EAST DONGTING LAKE USING ENVISAT ASAR DATA

ENVISAT ASAR Alternating Polarization images acquired at different dates，with diverse polarizations and incident angles，were used for mapping wetland vegetations of the East Dongting Lake.Based on the analysis of backscattering coefficients，an image which is made up of cross and like polarized signals gathered from multi temporal ASAR data provides better separation between classes than a combination of like polarized signals.Meanwhile，adopting the tone of filtered images combined with the “Contrast” texture feature based on the GLCM of unfiltered images to form the feature vector.The experimental result showed that the improved scheme has enhanced the performance of classification，overall accuracy of classification is 87.59% and Kappa index is 0.8228.Finally，the wetland located at East Dongting Lake was divided into water area，Phragmites and Miscanthus sacchariflorus，Carex and Phalaris arundinacea，woodland (Populus and Wilows)，planted land without dominant species，submerged vegetations and bare land.