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基于时序高分一号宽幅影像火后植被光谱及指数变化分析
引用本文:孙桂芬,覃先林,尹凌宇,刘树超,李增元,陈小中,钟祥清. 基于时序高分一号宽幅影像火后植被光谱及指数变化分析[J]. 光谱学与光谱分析, 2018, 38(2): 511-517. DOI: 10.3964/j.issn.1000-0593(2018)02-0511-07
作者姓名:孙桂芬  覃先林  尹凌宇  刘树超  李增元  陈小中  钟祥清
作者单位:1. 中国林业科学研究院资源信息研究所,国家林业局林业遥感与信息技术实验室,北京 100091
2. 四川省林业信息中心,四川 成都 610081
基金项目:国防科工局重大专项项目(E0305/1112/05)和民用航天预研项目资助
摘    要:为了探究国产高分卫星遥感技术监测火干扰对植被生长影响的能力及其表征植被指数,选取2014年发生在四川省雅江县和冕宁县的两场森林火灾形成的火烧迹地作为研究区,利用火灾前后时序的高分一号宽幅(GF-1 WFV)数据,对不同受灾程度火烧迹地火灾前后的光谱特征变化进行分析,并以月为单位分析了不同受害程度植被火后两年内由GF-1 WFV数据生成的归一化植被指数(NDVI)、增强型植被指数(EVI)和全球环境监测植被指数(GEMI)等三种表征植被生长状态的植被指数的变化,结合研究区纬度、海拔和气候条件分析火后植被的年内恢复规律。结果表明:火烧造成植被色素和细胞结构破坏,使其不再表现出正常植被特有的光谱特征,在可见光区受害植被的反射率相比于正常植被偏高,且其值随受灾程度加重而升高;在近红外波段火干扰后的植被反射率降低,其值远低于正常植被的反射率值。NDVI,EVI和GEMI在表征植被恢复生长过程中存在高度相关性且对植被季节变化敏感,均能反映植被恢复的生长过程,具有描述火烧区植被恢复动态过程的能力;受灾植被恢复生长过程中的植被指数变化与正常植被年生长过程的植被指数变化趋势基本一致,同样存在生长季和非生长季;火烧区植被的NDVI,EVI和GEMI值相比正常植被对应植被指数值始终偏低,且植被受灾越严重,其植被指数值在同期中对应越低。

关 键 词:高分一号宽幅数据  光谱特征  植被指数  时间序列  植被恢复  
收稿时间:2017-03-31

Changes Analysis of Post-Fire Vegetation Spectrum and Index Based on Time Series GF-1 WFV Images
SUN Gui-fen,QIN Xian-lin,YIN Ling-yu,LIU Shu-chao,LI Zeng-yuan,CHEN Xiao-zhong,ZHONG Xiang-qing. Changes Analysis of Post-Fire Vegetation Spectrum and Index Based on Time Series GF-1 WFV Images[J]. Spectroscopy and Spectral Analysis, 2018, 38(2): 511-517. DOI: 10.3964/j.issn.1000-0593(2018)02-0511-07
Authors:SUN Gui-fen  QIN Xian-lin  YIN Ling-yu  LIU Shu-chao  LI Zeng-yuan  CHEN Xiao-zhong  ZHONG Xiang-qing
Affiliation:1. Research Institute of Forest Resources Information Technique, Chinese Academy of forestry,Key Laboratory of Forestry Remote Sensing and Information Techniques, State Forestry Administration, Beijing 100091, China2. Forestry Information Center of Sichuan Province, Chengdu 610081, China
Abstract:To explore the ability of domestic high-resolution satellite remote sensing technology monitoring the effect of fire disturbance on vegetation growth and the characterize vegetation index, two burned sites formed by forest fire in 2014 in Yajiang county and Mianning county of Sichuan province were selected as the study area. The change of vegetation spectral features of burned area at different burned severity between pre-fire and post-fire has been analyzed using the selected GF-1 WFV data. At the same time, post-firetime series GF-1 WFV data has been used to analyze the monthly variation of Normalized Difference Vegetation Index(NDVI), Enhanced Vegetation Index (EVI) and Global Environment Monitoring Index (GEMI) which can characterize vegetation growth status of fire disturbance vegetation at different fire severity during two years after the forest fires taking place. With Combination of the latitude, altitude and climatic conditions of the study area, vegetation recovery pattern of post-fire vegetation was analyzed. Results showed that the vegetation pigments and cell structure were destroyed by the fire, which made its spectral features no longer show the unique spectral characteristics of normal vegetation. In the visible region, spectral reflectance of fire-disturbed vegetation at different fire severity was higher than that of normal vegetation and its value increased withthe severity. In the near infrared band, the reflectance of vegetation decreased after fire disturbance and its value was much lower than that of normal vegetation. NDVI, EVI and GEMI were highly correlated in the characterization of vegetation restoration process and sensitive to vegetation seasonal variation, which made it capability to reflect vegetation restoration process and they had the ability to describe the dynamic process of vegetation restoration. The changes of vegetation index of disturbed vegetation in vegetation restoration process were basically same as that of normal vegetation. Growing and non-growing season existed in the restoration process of affected vegetation as well. NDVI, EVI and GEMI of the vegetation at burned area were always lower than those of the normal vegetation and the higher the vegetation burned severity, the lower the vegetation index value was.
Keywords:GF-1 WFV data  Spectral features  Vegetation index  Time series  Vegetation restoration  
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