| 摘要: |
| 以东莞市内桉树林为研究对象， 2014 年 Landsat 8 数据及森林资源调查数据作为主要信息源，
通过相关分析和主成分分析，探讨 TM 光谱值、植被指数对东莞桉树健康度的解释作用。结果表明：公
顷株数、郁闭度、 TM11/TM10、 TM7、 TM11-TM10、 EVI、平均胸径、坡向、坡位、 PVI、 TM5/TM4、
坡度、海拔和 NDVI 是反映桉树林健康度的主要因子，利用遥感因子 TM7、 TM11-TM10、 TM5/TM4、
TM11/TM10、 NDVI、 EVI、 PVI 可快速判断桉树林的健康状况，判对率达 92.00%。 |
| 关键词: 森林健康 主成分分析 遥感 桉树 |
| DOI： |
| 分类号:TP75 |
| 基金项目: |
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| Analysis of Forest Health Based on Remote Sensing Technology ——A Case Study of Eucalyptus in Dongguan |
|
fanjing and Yangyanqiong
|
|
College of Forestry and Landscape Architecture, South China Agricultural University,College of Forestry and Landscape Architecture, South China Agricultural University
|
| Abstract: |
| Based on the data of Landsat 8 and forest resources investigation, the paper discusses TM spectral
values and vegetation indices how to interpret the health degree of the eucalyptus forests in Dongguan. Through
the correlation analysis and principal component analysis, the result showed that the main factors that reflect the
health of eucalyptus forests are the number of plants per hectare, canopy density, TM11/TM10, TM7, TM11-
TM10, EVI, mean DBH, slope aspect, slope position, PVI, TM5/TM4, slope degree, elevation, and NDVI. The
health status of eucalyptus forests can be determined quickly through the remote sensing factors of TM7, TM11-
TM10, TM5/TM4, TM11/TM10, NDVI, EVI, PVI, and the precision rate is 92.00%. |
| Key words: forest health principal component analysis remote sensing eucalyptus |
