• 论文与研究报告 •

### 大兴安岭不同植被火后NDVI恢复过程

1. 中国林业科学研究院森林生态环境与保护研究所 国家林业局森林保护学重点实验室 北京 100091
• 收稿日期:2014-08-28 修回日期:2014-11-13 出版日期:2015-02-25 发布日期:2015-03-11
• 通讯作者: 田晓瑞
• 基金资助:

国家自然科学基金项目(31270695); 林业公益性行业科研专项(201004074)。

### NDVI Recovery Process for Post-Fire Vegetation in Daxing'anling

Miao Qinglin, Tian Xiaorui, Zhao Fengjun

1. Key Laboratory of Forest Protection of State Forestry Administration Research Institute of Forest Ecology, Environment and Protection, CAF Beijing 100091
• Received:2014-08-28 Revised:2014-11-13 Online:2015-02-25 Published:2015-03-11

【目的】 利用卫星遥感技术研究火后植被恢复过程及影响因子,分析不同火烧强度、不同植被类型的火后归一化植被指数(NDVI)变化特征,研究大兴安岭东南部火后不同植被恢复过程,为在长时间尺度上进行北方林火后植被恢复过程研究与监测提供参考。【方法】 基于火烧前后一系列的MODIS数据,利用NDVI和地面调查数据,以2006年大兴安岭松岭特大森林火灾为例,研究不同植被类型在不同强度火烧后的植被恢复过程。根据火烧前后NDVI变化提取过火区; 结合地面调查,利用监督分类方法划分火烧强度等级; 根据火烧强度分级图和土地覆盖类型图,建立属性数据库,生成火烧强度等级-植被类型图。以2003—2005年同期NDVI最大值为对照,在时间序列上分析植被类型和火烧强度对火后NDVI恢复的影响。根据邻近未过火区的NDVI变化,分析气象因子对NDVI的影响。【结果】 轻度、中度和重度火烧区所占比例分别为29%,40%和31%。主要植被类型常绿针叶林、针阔混交林和灌丛的重度火烧部分分别占50%,52%和60%。重度火烧区域所占比例随着坡度增大而升高。在火后NDVI的变化过程中,各森林类型变化趋势相近,灌丛、草地和沼泽的变化趋势相近。【结论】 火后NDVI总体呈上升趋势,并呈现明显的年际波动。除草地外其余植被类型在重度火烧后的NDVI值均明显低于中、轻度火烧,但中、轻度火烧的不同植被类型之间差异不明显。森林重度火烧区NDVI在火后第2年达到最低,轻度火烧区火后6年NDVI基本恢复到火前水平。针阔混交林火后盖度的恢复速度较其他森林类型快。火烧强度对森林群落垂直结构的影响显著,森林火烧后灌木层盖度高于未火烧区,且火烧强度越高,这种现象越显著。双因素方差分析显示植被类型和火烧强度对火烧迹地NDVI恢复特征的影响显著, 且火烧强度对火后植被恢复的影响更关键,但二者交互影响不显著。未过火区NDVI平均值为0.801 2,波动范围为-3.3%~3.4%,过火区dNDVI的变化约25%是由气象因子引起的,其他主要源于植被变化。dNDVI指标可以很好地反映火烧前后植被指数变化,有较好的时序性和空间可获取性,对火烧迹地恢复过程有指示作用。

Abstract:

【Objective】The remote sensing technology was used to monitor the vegetation restoration after fire, providing a scientific base for carrying out restoration measures in burned areas. The normalized difference vegetation index (NDVI) is an important index to reflect the growth condition and distribution of vegetation. It has been proved in previous studies that this index has a significant correlation with vegetation coverage. Thus the increasing biomass and the vegetation coverage in burned areas can be monitored through the satellite remote sensing images.【Method】 The Songling burned area, which was burned in spring of 2006, in Daxing'anling was selected as a case study. A series of NDVI data before and after the fire, which were extracted from the MODIS data, and the field investigation data were used to analyze the relationships between vegetation characteristics after fire, burned severity and vegetation types. Data of NDVI in the burned area were extracted before and just after the fire, and the fire severity was classified using the supervised classification method. The maximum NDVI in the same date of August in 2003-2005 was used as the contrast to analyze the vegetation index changes on the time series. 【Result】Low, moderate and high burning severities were accounted for 28.93%, 40.1% and 30.97% burned area, respectively. The dominated vegetation types with high-burning severity were evergreen coniferous forest, broadleaf and conifer mixed forest, and brushwood, which were accounted for 50.37%, 52.22%, and 59.49%, respectively. The proportion of high severity burned areas increased with the ascending slope. 【Conclusion】 The post-fire NDVI showed a increasing trend generally. NDVI value of each vegetation type in the area with high-burning severity was significantly lower than the low and moderate burning severity areas, except for the grassland. But there was no significant difference in NDVI between the areas with low and moderate burning severity. In the second year, the vegetation coverage in high burning severity areas reached the minimum. The NDVI of these vegetation types in low burning severity areas recovered to pre-fire level in 6 years after fire. The coverage of broadleaf and conifer mixed forests recovered faster than other forest types. Fire severity affected forest vertical structure. The burned forests had greater shrub coverage than un-burned ones, and this phenomenon was more obvious in the forests with high fire severity. The natural restoration of brushwood, grassland and marsh was faster than that of forests, thus these areas don't need artificial aids to update. Natural restoration of the tree layer in forests with high-burning severity is very slow, the artificial update will speed up the succession process of forest communities. Periodic drought has an influence on NDVI, especially for the post-fire grassland. The two-factor ANOVA showed that vegetation type and fire severity had a significant influence on the vegetation index. dNDVI can reflect the changes of the vegetation well, which has a good temporal and spatial availability and plays an important role in monitoring the post-fire vegetation restoration.

Key words: burned area, NDVI, vegetation restoration