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遥感技术与应用  2022, Vol. 37 Issue (3): 721-730    DOI: 10.11873/j.issn.1004-0323.2022.3.0721
遥感应用     
基于MODIS数据的亚马逊热带雨林火灾时空变化规律研究
刘立越1,2(),苗则朗1,2(),吴立新1,2
1.中南大学 地球科学与信息物理学院,湖南 长沙 410083
2.中南大学 地灾感知认知预知实验室,湖南 长沙 410083
Spatial-temporal Variability of Amazon Tropical Rainforest Fire based on MODIS Data
Liyue Liu1,2(),Zelang Miao1,2(),Lixin Wu1,2
1.School of Geoscience and Info-Physics,Central South University,Changsha 410083,China
2.Lab of Geohazards Perception,Cognition and Prediction,Changsha 410083,China
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摘要:

频繁发生的森林大火对亚马逊热带雨林造成了大面积破坏,获取不同年份的火灾影响范围以及植被破坏情况,有助于了解该地区火灾时空演变规律以及火灾与植被的相互作用关系,进而探究火灾发展机理,为防灾减灾提供科学依据。为此,利用2015~2019年MODIS植被指数产品与地表温度产品,构建MODIS全球扰动指数模型(MGDI),结合火点数据 (以下统称MOD14A1)、植被连续场数据(Vegetation Continuous Field,VCF)提取1 000 m分辨率下的燃烧范围和燃烧强度,并分析研究区域5年内的火灾分布时空规律。实验结果表明:①火灾主要分布在巴西中部以及巴西与玻利维亚的交界处,占燃烧区总面积的67%左右;②燃烧范围以及燃烧强度的综合信息显示火灾整体呈现出“升—降—升”的趋势;③火灾多发生于灌木草地(50%以上)以及阔叶林(30%),且火灾多发在旱季;在全球变暖大背景下,火灾发生频率呈上升趋势;(4)人类活动范围扩张、不合理农业开垦、森林砍伐导致研究区内草地退化严重,农业用地以及建筑用地逐年上升,在一定程度上为火灾的发生、传导提供了良好的条件。

关键词: 亚马逊火灾全球扰动指数模型燃烧区时空变化    
Abstract:

Frequent forest fires have caused extensive vegetation destruction in the Amazon tropical rain forest. It’s of great importance to obtain the fire influence range and vegetation destruction in different years to understand the spatio-temporal evolution of fire in this area, study the interaction between fire and vegetation, and then explore the fire development mechanism, so as to provide a scientific basis for disaster forest and reduction. To this end, the MODIS vegetation index products and surface temperature products range from 2015 to 2019 were used in this paper to construct the MODIS Global Disturbance Model (MGDI), combined with fire point data (hereinafter collectively referred to as MOD14A1) and Vegetation Continuous Field (VCF)to extract combustion scope and intensity at 1 000 m resolution, and the spatial and temporal law of burned area within 5 years of the study area was analyzed. The results revealed that :(1) Burned area are mainly distributed in the central part of Brazil and the border between Brazil and Bolivia, accounting for about 67% of the total burning area;(2) The information of burned area and burned intensity comprehensively `indicated that the fire showing a “rise-drop-rise” trend;(3) The fire mainly occurred in shrub grassland(more than 50%) and broad-leaved forest(30%), and most of them took place during the dry season; under the global warming circumstance, the fire frequency increased a lot;(4) The expansion of human activities, unreasonable agricultural reclamation and deforestation lead to serious grassland degradation in the study area, and agricultural land and construction land are increasing year by year, which provides good conditions for the occurrence and conduction of fire to a certain extent.

Key words: Amazon    Fire    MGDI    Burned area    Spatial and temporal variation
收稿日期: 2020-11-21 出版日期: 2022-08-25
ZTFLH:  TP79  
基金资助: 国家自然科学基金项目(42171084);中南大学创新驱动计划(2020CX036);中南大学研究生科研创新项目(2020zzts646);湖南省研究生科研创新项目(CX20200223)
通讯作者: 苗则朗     E-mail: liulue@csu.edu.cn;Zelang.miao@csu.edu.cn
作者简介: 刘立越(1996-),男,江西九江人,硕士研究生,主要从事光学遥感环境变化监测研究。E?mail: liulue@csu.edu.cn
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引用本文:

刘立越,苗则朗,吴立新. 基于MODIS数据的亚马逊热带雨林火灾时空变化规律研究[J]. 遥感技术与应用, 2022, 37(3): 721-730.

Liyue Liu,Zelang Miao,Lixin Wu. Spatial-temporal Variability of Amazon Tropical Rainforest Fire based on MODIS Data. Remote Sensing Technology and Application, 2022, 37(3): 721-730.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.3.0721        http://www.rsta.ac.cn/CN/Y2022/V37/I3/721

数据产品卫星系统空间分辨率/m时间分辨率起止时间
MOD13A1(EVI)MODIS-Terra50016-Day2004~2019
MOD11A2(LST)MODIS-Terra1 0008-Day2004~2019
MOD14A1MODIS-Terra1 0001-Day2015~2019
MOD44B(VCF)MODIS-Terra5001-Year2015~2019
FireCCI-BA(Pixel)Envisat-MERIS & MODIS Aqua & Terra25030-Day2015~2019
CCI-LandcoverEnvisat-MERIS & MODIS Aqua & Terra3001-Year2015~2018
表1  数据产品描述
图1  亚马逊平原地理位置及植被覆盖度状况
图2  2015~2019年MGDI燃烧区提取结果
年份TPTNFPFNAccKappa
201569 07011 095 196202 302184 26096.65%0.25
201660 90011 113 070191 703178 03396.80%0.23
201784 97411 104 441187 011184 08596.79%0.30
201836 20111 281 372131 866120 41297.82%0.21
2019107 66811 092 463202 962184 71496.65%0.34
表2  MGDI与FireCCI-BA一致性检验统计表
图3  剧烈燃烧区一致性检验
年份TPTNFPFNAcc/%Kappa
20158 56475 1888 5911 02889.700.59
99633 09581562095.960.56
20161 56619 9592 65357486.960.30
1 81714 0991 60577986.970.30
201728562 93461551698.240.33
55632 4992311 04596.280.45
201835610 55646822694.010.48
26533 93316447498.170.45
20193 18025 5144 66897683.560.44
2 72329 1463 1031 17188.170.50
表3  剧烈燃烧区一致性检验统计表
图4  燃烧区分布
图5  2015~2019不同国家燃烧强度分布
年份燃烧强度玻利维亚巴西哥伦比亚秘鲁委内瑞拉年际占比/%
2015年内不同燃烧强度占比/%I7.8784.781.450.555.3527.06
II11.4080.801.360.945.4620.88
III9.9683.221.970.524.3324.99
2016I18.6471.211.314.204.6514.55
II20.8469.862.233.543.5415.53
III13.8876.201.493.804.6319.82
2017I20.9178.410.090.090.5319.10
II33.5464.880.240.241.1016.69
III27.5870.8500.221.3514.61
2018I21.1123.5830.762.4722.085.54
II25.1715.7338.812.1018.185.82
III21.2027.1724.462.7224.466.03
2019I59.1530.606.330.283.6433.75
II71.0617.947.330.203.4741.07
III63.9822.946.070.386.6434.56
表4  2015~2019各个国家燃烧强度占比
图6  5年内研究区火灾发生时间
图7  旺季淡季火灾分布(2015~2019年)
图8  5年内不同地物年际变化趋势(Z分数)
图9  燃烧区地物分布
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