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Remote Sensing Technology and Application  2022, Vol. 37 Issue (3): 721-730    DOI: 10.11873/j.issn.1004-0323.2022.3.0721
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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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     
Received:  21 November 2020      Published:  25 August 2022
ZTFLH:  TP79  
Corresponding Authors:  Zelang Miao     E-mail:;
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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.

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MOD11A2(LST)MODIS-Terra1 0008-Day2004~2019
MOD14A1MODIS-Terra1 0001-Day2015~2019
FireCCI-BA(Pixel)Envisat-MERIS & MODIS Aqua & Terra25030-Day2015~2019
CCI-LandcoverEnvisat-MERIS & MODIS Aqua & Terra3001-Year2015~2018
Table 1  Description of the data product
Fig.1  Geolocation of Amazon Basin and its vegetation coverage status
Fig.2  MGDI burned area extraction result during 2015 to 2019
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
Table 2  Consistency test between MGDI and FireCCI-BA
Fig.3  Drastic burned area consistency test
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
Table 3  Statistical table of drastic burned area consistency test
Fig.4  Distribution of burned area
Fig.5  Distribution of burned degree in different country during 2015 to 2019
Table 4  Different countries’ burned degree proportion during 2015 to 2019
Fig.6  Fire occurrence time in five years
Fig.7  Burned area distribution in high season and low season (2015~2019)
Fig.8  Interannual variation of different landcover in 5 years(Z-Score)
Fig.9  Landcover distribution in burned area
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