Changes Analysis of Post-Fire Vegetation Spectrum and Index Based on Time Series GF-1 WFV Images

被引:3
作者
Sun Gui-fen [1 ]
Qin Xian-lin [1 ]
Yin Ling-yu [1 ]
Liu Shu-chao [1 ]
Li Zeng-yuan [1 ]
Chen Xiao-zhong [2 ]
Zhong Xiang-qing [2 ]
机构
[1] Chinese Acad Forestry, State Forestry Adm, Key Lab Forestry Remote Sensing & Informat Tech, Res Inst Forest Resources Informat Tech, Beijing 100091, Peoples R China
[2] Forestry Informat Ctr Sichuan Prov, Chengdu 610081, Sichuan, Peoples R China
关键词
GF-1 WFV data; Spectral features; Vegetation index; Time series; Vegetation restoration; VARIABILITY; RECOVERY;
D O I
10.3964/j.issn.1000-0593(2018)02-0511-07
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
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 with the 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.
引用
收藏
页码:511 / 517
页数:7
相关论文
共 7 条
[1]   Post-fire vegetation recovery in Portugal based\newline on spot/vegetation data [J].
Gouveia, C. ;
DaCamara, C. C. ;
Trigo, R. M. .
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2010, 10 (04) :673-684
[2]   Variability and persistence of post-fire biological legacies in jack pine-dominated ecosystems of northern Lower Michigan [J].
Kashian, Daniel M. ;
Corace, R. Gregory, III ;
Shartell, Lindsey M. ;
Donner, Deahn M. ;
Huber, Philip W. .
FOREST ECOLOGY AND MANAGEMENT, 2012, 263 :148-158
[3]   Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel [J].
van Leeuwen, Willem J. D. ;
Casady, Grant M. ;
Neary, Daniel G. ;
Bautista, Susana ;
Antonio Alloza, Jose ;
Carmel, Yohay ;
Wittenberg, Lea ;
Malkinson, Dan ;
Orr, Barron J. .
INTERNATIONAL JOURNAL OF WILDLAND FIRE, 2010, 19 (01) :75-93
[4]   Assessing post-fire vegetation recovery using red-near infrared vegetation indices: Accounting for background and vegetation variability [J].
Veraverbeke, S. ;
Gitas, I. ;
Katagis, T. ;
Polychronaki, A. ;
Somers, B. ;
Goossens, R. .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2012, 68 :28-39
[5]   Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM plus data [J].
Vila, Jose Pablo Solans ;
Barbosa, Paulo .
ECOLOGICAL MODELLING, 2010, 221 (01) :75-84
[6]  
[王鑫 Wang Xin], 2014, [中国农学通报, Chinese Agricultural Science Bulletin], V30, P155
[7]  
Xian W., 2016, J SW CHINA NORMAL U, V41, P1, DOI [10.13718/j.cnki.xsxb.2016.09.001, DOI 10.13718/J.CNKI.XSXB.2016.09.001]