Spatial and temporal distribution patterns of grassland fire and its response to meteorological factors in XinBarag Prairie of northwestern China

Gong Da-peng; Kang Feng-feng; Liu Xiao-dong

doi:10.13332/j.1000-1522.20170402

Journal of Beijing Forestry University > 2018 > 40(2): 82-89. > DOI: 10.13332/j.1000-1522.20170402

Gong Da-peng, Kang Feng-feng, Liu Xiao-dong. Spatial and temporal distribution patterns of grassland fire and its response to meteorological factors in XinBarag Prairie of northwestern China[J]. Journal of Beijing Forestry University, 2018, 40(2): 82-89. DOI: 10.13332/j.1000-1522.20170402

Citation:

PDF (976 KB)

Spatial and temporal distribution patterns of grassland fire and its response to meteorological factors in XinBarag Prairie of northwestern China

College of Forestry, Beijing Forestry University, Beijing 100083, China

More Information

Received Date: November 13, 2017
Revised Date: December 27, 2017
Published Date: January 31, 2018

Graphical Abstract

Abstract

Abstract

ObjectiveGrassland fire is a key disturbance factor in natural ecosystems and it greatly influences ecosystem structure and function. XinBarag Prairie of northwestern China is one of the important grassland ecosystems in China. With the frequent occurrence of extreme weather events, more extra serious wildfires will occur in this region. This study could provide a scientific basis for zoning grassland fire risks and wildfire management.
MethodIn this study, the spatial and temporal patterns of wildfires in XinBarag Prairie were analyzed using statistical software, GIS and ENVI based on MODIS data from 2001 to 2016. Through the integration of meteorological data, the impact of meteorological factors on the characteristics of monthly variations in grassland fire was investigated.
ResultXinBarag Prairie had regular distribution in the spatial and temporal patterns of wildfires. In the temporal patterns, annual burned area had a fluctuation period of 10 years generally in the whole region. The monthly burned area had significant differences among various months and the burned area was mainly distributed in April, May, September and October. The time corresponds to spring and autumn, in which fire disaster occurred frequently. In spatial patterns, the high frequencies of wildfires were all widely distributed near the country s borders. The large-scale fires crossing the border line will pose a serious threat to the steppe in China; There were close relations between grassland fire and meteorological factors. Grassland fires easily occurred and spreaded in areas with monthly average temperature ranged between 0 and 10 ℃, monthly total rainfall ranged between 0 and 20 mm, monthly mean relative humidity was below 40% and monthly mean wind speed was above 5 m/s.
ConclusionThe preventing region of grassland fire in XinBarag Prairie should concentrate in its western, southeastern and northeastern regions, and the monitoring and management of grassland fire in border region should be strengthened.In time, we should concern April, May, September and October, especially the areas with monthly average temperature between 0 and 10 ℃, monthly total rainfall between 0 and 20 mm, monthly mean relative humidity below 40% and monthly mean wind speed above 5 m/s. In addition, future research will focus on the fluctuation period of grassland fire from longer temporal and wider spatial scale to explore the dynamic change of wildfires and its influencing factors more effectively.
- grassland fire,
- MODIS,
- spatial and temporal pattern,
- meteorological factor

FullText(HTML)

References (41)

References

[1]	雒瑞森.全球火格局的时空变异及其机理分析[D].杭州: 浙江大学, 2013. http://d.wanfangdata.com.cn/Thesis/Y2405202 Luo R S. Global analysis of spatial and temporal variations of fire patterns and the mechanisms [D]. Hangzhou: Zhejiang University, 2013. http://d.wanfangdata.com.cn/Thesis/Y2405202
[2]	Li Z, Fraser R, Jin J, et al. Evaluation of satellite-based algorithms for fire detection and mapping within North America[J/OL]. Journal of Geophysical Research, 2003, 108(D2): 4076 [2017-05-11]. www.researchgate.net/publication/24611. DOI: 10.1029/2001JD001377.
[3]	周广胜, 卢琦.气象与森林草原火灾[M].北京:气象出版社, 2009. Zhou G S, Lu Q. Meteorology and forest-grassland fire[M]. Beijing: China Meteorological Press, 2009.
[4]	陈世荣.草原火灾遥感监测与预警方法研究[D].北京: 中国科学院研究生院, 2006. http://d.wanfangdata.com.cn/Thesis/J008377 Chen S R. A study of grassland fire monitoring and early warning methods using remote sensing[D]. Beijing: Chinese Academy of Sciences, 2006. http://d.wanfangdata.com.cn/Thesis/J008377
[5]	胡海清, 李楠, 孙龙, 等.伊春地区森林火灾时空分布格局[J].东北林业大学学报, 2011, 39(10):67-70. doi: 10.3969/j.issn.1000-5382.2011.10.019 Hu H Q, Li N, Sun L, et al. Spatial and temporal distribution patterns of forest fires in Yichun, Heilongjiang Province[J]. Journal of Northeast Forestry University, 2011, 39(10):67-70. doi: 10.3969/j.issn.1000-5382.2011.10.019
[6]	马楠楠, 张彦雷, 李建, 等.黑龙江呼玛县森林火灾时空分布特征[J].东北林业大学学报, 2016, 44(5):20-23. doi: 10.3969/j.issn.1000-5382.2016.05.005 Ma N N, Zhang Y L, Li J, et al. Spatial and temporal distribution characteristics of forest fire in Huma County of Heilongjiang Province[J]. Journal of Northeast Forestry University, 2016, 44(5):20-23. doi: 10.3969/j.issn.1000-5382.2016.05.005
[7]	杨广斌, 唐小明, 宁晋杰, 等.北京市1986—2006年森林火灾的时空分布规律[J].林业科学, 2009, 45(7):90-95. doi: 10.3321/j.issn:1001-7488.2009.07.015 Yang G B, Tang X M, Ning J J, et al. Spatial and temporal distribution pattern of forest fire occurred in Beijing from 1986 to 2006[J]. Scientia Silvae Sinicae, 2009, 45(7):90-95. doi: 10.3321/j.issn:1001-7488.2009.07.015
[8]	Seol A, Lee B, Chung J. Analysis of the seasonal characteristics of forest fires in South Korea using the multivariate analysis approach[J]. Journal of Forest Research, 2012, 17(1):45-50. doi: 10.1007/s10310-011-0263-8
[9]	郑琼, 邸雪颖, 金森.伊春地区1980—2010年森林火灾时空格局及影响因子[J].林业科学, 2013, 49(4):157-163. http://www.cnki.com.cn/Article/CJFDTotal-LYKE201304026.htm Zheng Q, Di X Y, Jin S. Temporal and spatial patterns of forest fires in Yichun Area during 1980-2010 and the influence of meteorological factors[J] Scientia Silvae Sinicae, 2013, 49(4):157-163. http://www.cnki.com.cn/Article/CJFDTotal-LYKE201304026.htm
[10]	王明玉, 孙龙, 舒立福, 等.林火在空间上的波动性及其区域化行为[J].林业科学, 2006, 42(5):98-103. http://d.old.wanfangdata.com.cn/Periodical/lykx200605018 Wang M Y, Sun L, Shu L F, et al. Fluctuation of forest fire in spatial space and their regional behavior[J] Scientia Silvae Sinicae, 2006, 42(5):98-103. http://d.old.wanfangdata.com.cn/Periodical/lykx200605018
[11]	苏立娟, 何友均, 陈绍志. 1950—2010年中国森林火灾时空特征及风险分析[J].林业科学, 2015, 51(1):88-96. doi: 10.3969/j.issn.1006-1126.2015.01.018 Su L J, He Y J, Chen S Z. Temporal and spatial characteristics and risk analysis of forest fires in China from 1950 to 2010[J] Scientia Silvae Sinicae, 2015, 51(1):88-96. doi: 10.3969/j.issn.1006-1126.2015.01.018
[12]	贺宝华, 陈良富, 陶金花, 等.基于观测几何的环境卫星红外相机遥感火点监测算法[J].红外与毫米波学报, 2011, 30(2):104-108. http://d.old.wanfangdata.com.cn/Periodical/hwyhmb201102002 He B H, Chen L F, Tao J H, et al. A contextual fire detection algorithm based on observation geometry for HJ-1B-IRS[J]. Journal of Infrared and Millimeter Waves, 2011, 30(2):104-108. http://d.old.wanfangdata.com.cn/Periodical/hwyhmb201102002
[13]	Liu W, Wang L, Zhou Y, et al. A comparison of forest fire burned area indices based on HJ satellite data[J]. Natural Hazards, 2016, 81(2):1-10. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=765ea3bd943a5ed6b87dfda99e70d31c
[14]	Liu M, Zhao J, Guo X, et al. Study on climate and grassland fire in HulunBuir, Inner Mongolia Autonomous Region, China[J]. Sensors, 2017, 17(3):616. doi: 10.3390/s17030616
[15]	Araújo F M D, Ferreira L G, Arantes A E. Distribution patterns of burned areas in the Brazilian Biomes: an analysis based on satellite data for the 2002-2010 Period[J]. Remote Sensing, 2012, 4(7):1929-1946. doi: 10.3390/rs4071929
[16]	邓欧, 李亦秋, 冯仲科, 等.基于空间Logistic的黑龙江省林火风险模型与火险区划[J].农业工程学报, 2012, 28(8):200-205. doi: 10.3969/j.issn.1002-6819.2012.08.031 Deng O, Li Y Q, Feng Z K, et al. Model and zoning of forest fire risk in Heilongjiang Province based on spatial Logistic[J].Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(8): 200-205. doi: 10.3969/j.issn.1002-6819.2012.08.031
[17]	何诚, 巩垠熙, 张思玉, 等.基于MODIS数据的森林火险时空分异规律研究[J].光谱学与光谱分析, 2013, 33(9):2472-2477. doi: 10.3964/j.issn.1000-0593(2013)09-2472-06 He C, Gong Y X, Zhang S Y, et al. Forest fire division by using MODIS data based on the temporal-spatial variation law[J]. Spectroscopy and Spectral Analysis, 2013, 33(9):2472-2477. doi: 10.3964/j.issn.1000-0593(2013)09-2472-06
[18]	贾旭, 高永, 齐呼格金, 等.基于MODIS数据的内蒙古野火时空变化特征[J].中国生态农业学报, 2017, 25(1):127-135. http://d.old.wanfangdata.com.cn/Periodical/stnyyj201701016 Jia X, Gao Y, Qihugejin, et al. MODIS-based spatial-temporal distribution of wildfire in Inner Mongolia[J]. Chinese Journal of Eco-Agriculture, 2017, 25(1): 127-135. http://d.old.wanfangdata.com.cn/Periodical/stnyyj201701016
[19]	Zhu Q, Rong T, Sun R. A case study on fractal simulation of forest fire spread[J]. Science in China, 2000, 43(1):104-112. doi: 10.1007/BF02903854
[20]	Ponomarev E I, Kharuk V I, Ranson K J. Wildfires dynamics in Siberian larch forests[J]. Forests, 2016, 7(6):125. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=forests-07-00125
[21]	Csiszar I, Fraser R, Hao W M. Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data[J]. Remote Sensing of Environment, 2007, 108(2):198-208. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=e8edc4e3e0025153aa2ff917dc0f68f6
[22]	Li Z, Nsdon S, Cihlar J, et al. Satellite-based mapping of Canadian boreal forest fires: evaluation and comparison of algorithms[J]. International Journal of Remote Sensing, 2000, 20(16):3071-3082. doi: 10.1109-TCPMT.2011.2162069/
[23]	Femandez A, Illera P, Casanova J L. Automatic mapping of surfaces affected by forest fires in Spain using AVHRR NDVI composite image data[J]. Remote Sensing of Environment, 1997, 60(2):153-162. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=2743fdb173a8e16382e3704243c4ec03
[24]	Fraser R H, Li Z, Cihlar J. Hotspot and NDVI differencing synergy (HANDS): a new technique for burned area mapping over boreal forest[J]. Remote Sensing of Environment, 2000, 74(3):362-376. doi: 10.1016/S0034-4257(00)00078-X
[25]	Leeuwen W J D V, Huete A R, Laing T W. MODIS vegetation index compositing approach[J]. Remote Sensing of Environment, 1999, 69(99):264-280. doi: 10.1016-S0034-4257(99)00022-X/
[26]	Barbosa P M, Grégoire J M, Pereira J M C. An algorithm for extracting burned areas from time series of AVHRR GAC data applied at a continental scale[J]. Remote Sensing of Environment, 1999, 69(3):253-263. doi: 10.1016/S0034-4257(99)00026-7
[27]	Martin M P, Chuvieco E. Mapping and evaluation of burned land from multi-temporal analysis of AVHRR NDVI images[J]. EARSeL Advances in Remote Sensing, 1995, 4(3):7-13.
[28]	Zhang X, Kondragunta S, Quayle B. Estimation of biomass burned areas using multiple-satellite-observed active fires[J]. IEEE Transactions on Geoscience & Remote Sensing, 2011, 49(11):4469-4482. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=c94f08d876833026465b4a9a0984e25c
[29]	Li Y P, Zhao J J, Guo X Y, et al. The influence of land use on the grassland fire occurrence in the northeastern Inner Mongolia Autonomous Region, China[J]. Sensors, 2017, 17(3), 437. doi: 10.3390/s17030437
[30]	Giglio L, Werf G R V D, Randerson J T, et al. Global estimation of burned area using MODIS active fire observations[J]. Atmospheric Chemical Physics, 2006, 6(4):957-974. doi: 10.5194/acp-6-957-2006
[31]	赵凤君, 舒立福.气候异常对森林火灾发生的影响研究[J].森林防火, 2007(1):21-23. doi: 10.3969/j.issn.1002-2511.2007.01.009 Zhao F J, Shu L F. Influence of climate anomaly on forest fire occurrence[J]. Forest Fire Prevention, 2007(1):21-23. doi: 10.3969/j.issn.1002-2511.2007.01.009
[32]	丽娜, 包玉龙, 银山, 等.中蒙边境地区草原火时空分布特征分析[J].灾害学, 2016, 31(3):207-210. doi: 10.3969/j.issn.1000-811X.2016.03.035 Li N, Bao Y L, Yin S, et al. Spatiotemporal characteristics of grassland fire in China-Mongolia border regions[J]. Journal of Catastrophology, 2016, 31(3):207-210. doi: 10.3969/j.issn.1000-811X.2016.03.035
[33]	Araújo F M D, Ferreira L G. Satellite-based automated burned area detection: a performance assessment of the MODIS MCD45A1 in the Brazilian savanna[J]. International Journal of Applied Earth Observation & Geoinformation, 2015, 36:94-102.
[34]	Ruiz J A M, Lázaro J R G, Cano I D, et al. Burned area mapping in the north American boreal forest using Terra-MODIS LTDR (2001-2011): a comparison with the MCD45A1, MCD64A1 and BA GEOLAND-2 products[J]. Remote Sensing, 2014, 6(1):815-840. doi: 10.3390/rs6010815
[35]	杨伟, 张树文, 姜晓丽.基于MODIS时序数据的黑龙江流域火烧迹地提取[J].生态学报, 2015, 35(17):5866-5873. http://d.old.wanfangdata.com.cn/Periodical/stxb201517032 Yang W, Zhang S W, Jiang X L. Burned area mapping for Heilongjiang Basin based on MODIS time series data[J]. Acta Ecologica Sinica, 2015, 35(17):5866-5873. http://d.old.wanfangdata.com.cn/Periodical/stxb201517032
[36]	曲熠鹏, 郑淑霞, 白永飞.蒙古高原草原火行为的时空格局与影响因子[J].应用生态学报, 2010, 21(4):807-813. http://d.old.wanfangdata.com.cn/Periodical/yystxb201004001 Qu Y P, Zheng S X, Bai Y F. Spatiotemporal patterns and driving factors of grassland fire on Mongolian Plateau[J]. Chinese Journal of Applied Ecology, 2010, 21(4):807-813. http://d.old.wanfangdata.com.cn/Periodical/yystxb201004001
[37]	傅泽强.内蒙古干草原火灾时空分布动态研究[J].内蒙古气象, 2001(1):28-30. doi: 10.3969/j.issn.1005-8656.2001.01.014 Fu Z Q. Distribution and dynamics of fire in steppe of Inner Mongolia[J]. Meteorology Journal of Inner Mongolia, 2001(1): 28-30. doi: 10.3969/j.issn.1005-8656.2001.01.014
[38]	谢力, 温刚, 符淙斌.中国植被覆盖季节变化和空间分布对气候的响应:多年平均结果[J].气象学报, 2002, 60(2):181-187. doi: 10.3321/j.issn:0577-6619.2002.02.007 Xie L, Wen G, Fu Z B. The response of the vegetation seasonal variability and its spatial pattern to climate variation in China: multi-year average[J]. Acta Meteorologica Sinica, 2002, 60(2):181-187. doi: 10.3321/j.issn:0577-6619.2002.02.007
[39]	刘晓东, 王博.森林燃烧主要排放物研究进展[J].北京林业大学学报, 2017, 39(12):118-124. doi: 10.13332/j.1000-1522.20170307 Liu X D, Wang B. Review on the main emission products released by forest combustion[J]. Journal of Beijing Forestry University, 2017, 39(12):118-124. doi: 10.13332/j.1000-1522.20170307
[40]	胡海清, 金森.黑龙江省林火规律研究(Ⅱ):林火动态与格局影响因素的分析[J].林业科学, 2002, 38(2):98-102. doi: 10.3321/j.issn:1001-7488.2002.02.017 Hu H Q, Jin S. Study on forest fire regime of Heilongjiang Province (II): analysis on factors affecting fire dynamics and distributions[J]. Scientia Silvae Sinicae, 2002, 38(2):98-102. doi: 10.3321/j.issn:1001-7488.2002.02.017
[41]	孙海滨, 王美莲, 张红星, 等.大兴安岭森林火灾与气象因子相关性研究[J].内蒙古农业大学学报(自然科学版), 2012, 33(5-6):87-90. http://cdmd.cnki.com.cn/Article/CDMD-10225-2009133899.htm Sun H B, Wang M L, Zhang H X, et al. Correlation analysis between forest fire and meteorological elements in Daxinganling Mountain[J]. Journal of Inner Mongolia Agricultural University(Natural Science Edition), 2012, 33(5-6):87-90. http://cdmd.cnki.com.cn/Article/CDMD-10225-2009133899.htm

Cited By

Cited by

Periodical cited type(8)

1.	袁然，梁映红，傅童成，胡生龙，汪盛，易自力，李蒙. 南荻水热液化耦合酶解联产多种纤维糖. 中国造纸. 2024(11): 71-80 .
2.	张婷，孙德娇，王彩衣，黄鑫，陈少强，黎飞望，杨齐. 甘蔗渣制备低聚木糖的工艺优化. 广西科学. 2023(04): 727-734 .
3.	童欣怡，李琦，陈文倩，赵林果. 杨木屑木聚糖碱法提取及其制备低聚木糖的工艺研究. 林业工程学报. 2020(01): 61-68 .
4.	朱增科，平清伟，张健，盛雪茹，李娜，石海强. 乙醇-水抽提法分离毛竹枝桠材组分的研究. 中国造纸. 2020(08): 52-56 .
5.	张威伟，张波，张乐平，蒋建新. 非酶法催化木质纤维原料转化制备低聚木糖研究进展. 林产化学与工业. 2020(06): 118-128 .
6.	邓元元，胡超，陈思宇，朱文娟，王刚，兰时乐. 啤酒糟制备低聚木糖功能饲料添加剂酶解条件优化. 中国饲料. 2019(09): 54-62 .
7.	陈冰炜，阚玉娜，袁诚，王新洲，黄曹兴，梅长彤，翟胜丞. 乙醇预处理对芦竹细胞壁的影响及荧光可视化分析. 林业工程学报. 2019(04): 59-65 .
8.	刘洋，胡小文，姚艳丽. NaOH预处理对甘蔗渣成分和酶解效率的影响. 甘蔗糖业. 2019(06): 28-38 .

Other cited types(4)

Get Citation

PDF

XML

Article views (1436) PDF downloads (95) Cited by(12)

Turn off MathJax

Article Contents

Abstract

References

Spatial and temporal distribution patterns of grassland fire and its response to meteorological factors in XinBarag Prairie of northwestern China

Abstract

References

Cited by

Periodical cited type(8)

Other cited types(4)

Catalog

Export File

Citation

Format

Content