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作 者:靳华安[1] 刘殿伟[1] 王宗明[1] 宋开山[1] 李方[1] 杨飞[1] 杜嘉[1] 李凤秀[1]
机构地区:[1]中国科学院东北地理与农业生态研究所
出 处:《生态学杂志》2008年第5期803-808,共6页Chinese Journal of Ecology
基 金:中国科学院知识创新工程重点项目(KZCX3-SW-356);中国科学院长春净月潭遥感站网络台站基金资助项目
摘 要:利用中巴资源卫星CBERS-02影像提取的归一化植被指数(NDVI)和同期野外实测的叶面积指数(LAI)数据,分析了三江平原洪河自然保护区草甸、沼泽植被、灌丛和岛状林4种湿地植被及样本总体的NDVI与LAI之间的相关关系,建立了NDVI与不同湿地植被类型叶面积指数间的线性和非线性回归模型,并制作完成洪河自然保护区LAI空间分布图。结果表明,整个研究区样本总体的LAI估算效果不太理想,其NDVI与LAI的相关性仅为0.523;将研究区分为草甸、沼泽、灌丛和岛状林4种湿地植被类型,NDVI与各植被型LAI的相关性和估算效果均有很大程度的提高,所建立的LAI遥感反演模型以三次曲线回归方程拟合精度最高,R2分别达到0.723、0.588、0.837、0.720。以上结果表明,结合地面实测数据并基于遥感植被分类的基础上,CBERS-02遥感影像可用于较大区域内湿地植被生理参数的反演研究。By using the normalized difference vegetation index (NDVI) extracted from CBERS- 02 data and the leaf area index (LAI) data obtained from field measurement, this paper analyzed the relationships between the NDVI and the LAI of total samples of meadow, marsh vegetation, shrubs, and islanded forests of the wetland vegetation in Honghe Nature Reserve of Sanjiang Plain. The linear and non-linear regression models between NDVI and LAI of different wetland vegetation types were established, and the spatial distribution of LAI in the Honghe Nature Reserve was mapped. The results showed that it was unsatisfactory for the whole samples to estimate the LAI, With the correlation coefficient being only 0. 523. After the total samples were divided into four vegetation types, i. e. , meadow vegetation, marsh vegetation, shrub and islanded forest, the correlation coefficients and the estimation accuracy were improved evidently. Cubic equations were found to be the best in the different forms of the regression models for retrieving the LAI of wetland vegetation by using CBERS data, with the R^2 value being 0. 723, 0. 588, 0. 837, and 0. 720, respectively. It was indicated that with the combination of field-measured data and remote sensing-based vegetation classification, CBERS-02 data could be used for the larger scale estimation of the physiological parameters of wetland vegetation.
分 类 号:Q948[生物学—植物学] P237[天文地球—摄影测量与遥感]
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