[1]严恩萍,林辉,洪奕丰,等.杉木人工林叶面积指数估测及影响因子分析[J].水土保持研究,2013,20(04):75-81.
　YAN En-ping,LIN Hui,HONG Yi-feng,et al.Analysis on LAI Estimation and Its Effecting Factors for Chinese Fir Plantation[J].Research of Soil and Water Conservation,2013,20(04):75-81.
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杉木人工林叶面积指数估测及影响因子分析

《水土保持研究》[ISSN:1005-3409/CN:61-1272/P] 卷: 20 期数: 2013年04期 页码: 75-81 栏目: 出版日期: 2013-08-28
Title:
Analysis on LAI Estimation and Its Effecting Factors for Chinese Fir Plantation
作者:
严恩萍1, 林辉1, 洪奕丰2, 张雨1, 陈利1
1. 中南林业科技大学 林业遥感信息工程研究中心, 长沙 410004;
2. 国家林业局 华东森林资源监测中心, 杭州 310019
Author(s):
YAN En-ping1, LIN Hui1, HONG Yi-feng2, ZHANG Yu1, CHEN Li1
1. Research Center of Forest Remote Sensing & Information Engineering, Central South University of Forestry & Technology, Changsha 410004, China;
2. East China Monitoring Center of the Forest Resources, State Forestry Administration, Hangzhou 310019, China
关键词:
遥感; 叶面积指数; 回归模型; SPOT 5; 杉木人工林
Keywords:
remote sensing; leaf area index; regression model; SPOT 5; Chinese fir plantation
分类号:
S718.55
摘要:
叶面积指数是植被长势监测中最常用的参数之一，开展叶面积指数定量估测可为LAI信息的大区域监测提供参考。以湖南攸县黄丰桥林场的SPOT 5影像为数据源，结合地面实测数据，通过MCARI、SAVI、MSAVI、NDVI间的相关性和回归分析构建16种叶面积指数估测模型，探索适合杉木LAI的估测模型及影响因子。四种植被指数均与杉木叶面积指数具有较高的相关性，依次为MCARI、SAVI、MSAVI、NDVI，以MCARI为自变量的指数回归模型y=1.031exp（3.379x）估测精度最高，达87.69%；杉木LAI随龄组的增大呈上升趋势，最大值出现在成熟林，比LAI最小的幼龄林高0.30；不同坡向杉木LAI两两之间差异显著，半阳坡LAI明显大于其他坡向。研究表明，龄组和坡向是影响杉木LAI的重要因子，限制其生长和分布的首要因素是水湿条件，其次是温度。
Abstract:
Leaf area index (LAI) is one of the most important parameters for monitoring vegetation growth. In order to provide reference for LAI monitoring across large region, the study of LAI estimation and its effecting factors was conducted, which was carried out on Huang Fengqiao Forest Farm, You county, Hunan province, China. Based on the SPOT 5 data and ground survey data, sixteen LAI estimation models were constructed for determining the most suitable LAI estimation model and impact factor by using correlation analysis and regression analysis among four vegetation indexes (NDVI, SAVI, MSAVI and MCARI). The results show that the correlation between four vegetation indexes and fir leaf area index was strong, which were MCARI, SAVI, MSAVI, NDVI correspondingly. Among them, the exponential regression model with NDVI as the independent variable [y=1.031exp(3.379x)] has the highest estimation accuracy (87.69%). The LAI of fir tended to increase with the rise of group ages. The highest LAI value existed in the mature forest, while the lowest LAI value was found in the young forest, and the difference value between these two forests was 0.3. Two fir groups with various slope aspects show significant difference in LAI values, and values from the fir with a half-sunny slope were obviously higher than others. It can be concluded that group age and slope aspect were two important factors affecting the LAI of Chinese fir planation, and the primary factor limiting the growth and distribution of fir plantation was wet condition, followed by temperature.

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备注/Memo

收稿日期:2013-01-21;改回日期:2013-02-23。
基金项目:“十二五”国家高技术研究发展计划课题（2012AA102001）；国家自然科学基金项目（31100412）
作者简介:严恩萍(1986-),女,湖北省鄂州市人,博士研究生,主要从事林业遥感和地理信息系统应用研究。E-mail:yep1209@163.com
通讯作者:林辉(1965-),女,湖北黄冈人,教授,博士生导师,主要从事森林经理学、遥感技术与地理信息系统的教学和科研工作。E-mail:linhui88@sina.com

更新日期/Last Update: 1900-01-01