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Remote Sensing for Natural Resources    2024, Vol. 36 Issue (2) : 142-150     DOI: 10.6046/zrzyyg.2023030
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Exploring the spatio-temporal variations and forest restoration of burned zones in the Great Xing’an Range based on MODIS time series data
WANG Jian1(), DU Yuling1, GAO Zhao2, LYU Haiyan1, SHI Lei1()
1. College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China
2. The First Geodetic Survey Team of the Ministry of Natural Resources, Shaanxi Bureau of Surveying, Mapping and Geoinformation, Xi’an 710054, China
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Abstract  

Forest fires are one of the most significant disturbance factors affecting forest ecosystems. Exploring their spatio-temporal variations and forest restoration holds certain sociological and ecological significance. The Great Xing’an Range, possessing the largest primitive area in China, is a key area suffering frequent forest fires. Hence, this study extracted the distribution information of burned zones in the Great Xing’an Range from 2002 to 2021 from the MODIS time series products involving burned zones, land cover, and gross primary productivity (GPP). Moreover, it statistically analyzed the post-fire forest restoration. The results show that: ① Fires in the forest area of the Great Xing’an Range showed an overall downward trend from 2002 to 2021, but the burned areas showed fluctuating changes. Both the burned area and fire frequency were the highest in 2003, followed by 2008, with the lowest burned area seen in 2019; ② Forest fires occurred primarily in spring and autumn, with the highest burned area and fire frequency in March and the second highest fire frequency in September; ③ Forest fires manifested an uneven spatial distribution from northeast to southwest, predominantly in the Great Xing’an Range within Heilongjiang and Hulunbuir City of Inner Mongolia. Moreover, the forest fire area in Inner Mongolia far exceeded that in Heilongjiang. The analysis of forest types in burned zones reveals that the burned areas decreased in the order of broad-leaved, mixed, and needle-leaved forests. According to the time series analysis of GPP in burned zones, GPP values recovered the fastest in the first year post-fire, but it took nearly seven years to recover to the pre-fire growth level. Different forest types manifested significantly distinct post-fire restoration rates, which decreased in the order of broad-leaved, needle-leaved, and mixed forests. Overall, ascertaining the spatio-temporal distribution of forest fires can provide data support for the arrangement and adjustment of fire prevention and control efforts, while investigating the post-fire forest restoration can provide a scientific basis for the rehabilitation and sustainable development of forests.
Keywords forest fire      Great Xing’an Range      burned zone      forest restoration      MODIS     
ZTFLH:  TP79  
Issue Date: 14 June 2024
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Jian WANG
Yuling DU
Zhao GAO
Haiyan LYU
Lei SHI
Cite this article:   
Jian WANG,Yuling DU,Zhao GAO, et al. Exploring the spatio-temporal variations and forest restoration of burned zones in the Great Xing’an Range based on MODIS time series data[J]. Remote Sensing for Natural Resources, 2024, 36(2): 142-150.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2023030     OR     https://www.gtzyyg.com/EN/Y2024/V36/I2/142
Fig.1  Location of the study area
重采样
编号		 重采样类型 包含的IGBP类型 对应的IGBP编号
10 针叶林 常绿针叶林、落叶针叶林 1,3
20 阔叶林 常绿阔叶林、落叶阔叶林 2,4
30 针阔混交林 混交林 5
40 其他林种 郁闭灌木丛、稀疏灌木丛、多树草地、稀树草地 6,7,8,9
Tab.1  IGBP forest land cover classification in Great Xing’an Range
Fig.2  Annual changes of forest area and burned area in Greater Khingan Mountains
Fig.3  Monthly changes of forest fires in the Greater Khingan Mountains
Fig.4  Spatial distribution maps of forest fires
森林类型 过火面积/
108 hm2		 占总过火面
积的比例/%		 森林类型
占比/%
阔叶林 3 453.59 25.33 18.95
针叶林 110.82 0.81 7.39
混交林 221.63 1.63 6.64
其他林种 9 846.31 72.23 67.03
Tab.2  Forest fire area and forest types distribution in the Greater Khingan Mountains
Fig.5  Trend of GPP in the Greater Khingan Mountains forest region
Fig.6  Distribution of cumulative forest overfire in Greater Khingan Mountains
Fig.7  Comparison of the average GPP values in July between the burned area and total forest area
年份 GPP总产值/(×104 gC·m-2) 总产值比例/%
针叶林 阔叶林 混交林 针叶林 阔叶林 混交林
2002年 514.10 65.95 89.40 76.79 9.85 13.35
2003年 288.27 36.97 41.04 78.70 10.09 11.20
2004年 411.10 65.83 63.61 76.05 12.18 11.77
2005年 414.72 73.28 67.79 74.62 13.18 12.20
2006年 401.79 74.80 62.67 74.51 13.87 11.62
2007年 480.75 88.55 74.85 74.63 13.75 11.62
2008年 445.81 72.63 60.89 76.95 12.54 10.51
2009年 504.37 79.85 59.84 78.31 12.40 9.29
2010年 540.19 76.37 66.08 79.13 11.19 9.68
2011年 515.82 70.04 49.75 81.15 11.02 7.83
2012年 610.78 84.05 48.86 82.13 11.30 6.57
2013年 542.83 82.75 38.45 81.75 12.46 5.79
2014年 603.19 111.19 55.01 78.40 14.45 7.15
2015年 559.94 106.39 54.86 77.64 14.75 7.61
2016年 643.04 123.39 65.02 77.34 14.84 7.82
2017年 480.60 111.90 67.15 72.86 16.96 10.18
2018年 354.19 77.83 40.05 75.03 16.49 8.48
2019年 353.97 58.06 32.85 79.57 13.05 7.38
2020年 343.13 52.63 39.41 78.85 12.09 9.06
2021年 347.30 52.51 39.17 79.12 11.96 8.92
均值 467.79 78.25 55.84 77.68 12.92 9.40
Tab.3  GPP production data of different vegetation types in the burned area in July
Fig.8  Means and error bars of GPP in July for different vegetation types in the burned area
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