中文
Old Website

WE ARE COMMITTED TO REPORTING THE LATEST FORESTRY ACADEMIC ACHIEVEMENTS

Advanced Search
Volume 40 Issue 6
Dec.  2019
Article Contents
Turn off MathJax
Article Navigation >  Journal of Sichuan Forestry Science and Technology  > 2019  >  40(6): 6-12,18

LIU Qian, QIN Xian-lin, LI Xiao-tong, HOU Ya-nan. A Study of Spatiotemporal Characteristics of Forest Fires in Sichuan Province Based on Point Pattern's Method[J]. Journal of Sichuan Forestry Science and Technology, 2019, 40(6): 6-12,18. doi: 10.16779/j.cnki.1003-5508.2019.06.002
Citation: LIU Qian, QIN Xian-lin, LI Xiao-tong, HOU Ya-nan. A Study of Spatiotemporal Characteristics of Forest Fires in Sichuan Province Based on Point Pattern's Method[J]. Journal of Sichuan Forestry Science and Technology, 2019, 40(6): 6-12,18. doi: 10.16779/j.cnki.1003-5508.2019.06.002
shu

A Study of Spatiotemporal Characteristics of Forest Fires in Sichuan Province Based on Point Pattern's Method


doi: 10.16779/j.cnki.1003-5508.2019.06.002
More Information

  • Research Institute of Forest Resource Information Technology, Chinese Academy of Forestry, Beijing 100084, China

  • Received Date: 2019-09-04
  • The forest fire is an important factor of disturbing forest growth. Sichuan province was located in the southwest forest area with a high occurrence density area of forest fires.It could contribute to the forest fire prevention work by analyzing the distribution characteristics of fire occurrence in Sichuan province. Based on the MODIS fire product (MOD14A2/MYD14A2), Ripley K function, center point, standard deviational ellipse method and Kerne1 Density method were employed and the data clock was used to explore the spatial-temporal distribution of forest fires in Sichuan province from 2001 to 2012. The results showed that the annual forest fires fluctuated greatly in Sichuan province. The peak periods of forest fires were in January, February, March, April and May, and the number of forest fires continued to rise every year. On smaller spatial scale (less than 528 km), the spatial pattern of forest fires was clustering. The median center of forest fires occurred in Panzhihua city in 12 years, which was the area with highest fire density. The hot spots of forest fires were also located at Liangshan Yi Autonomous Prefecture and Ganzi Tibetan Autonomous Prefecture. The overall spread trend was to extend northwest to Ganzi Tibetan Autonomous Prefecture.
  • 加载中
  • [1] 丁青.基于遥感的欧亚北方森林林火扰动变化分析[D].北京:中国科学院大学,2013.
    [2] 徐盛基. 南方十省区卫星林火监测热点趋势分析[J]. 森林防火, 2011(1

    ).
    [3] 王鑫,王锐婷.四川省林火的时空分布特征及其气候背景分析[J].中国农学通报, 2014, (29):155~160.
    [4] 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.
    [5] 田晓瑞, 舒立福, 王明玉,等. 西藏森林火灾时空分布规律研究[J]. 火灾科学, 2007(1):10-14.
    [6] 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.
    [7] Orozco C D V. Point Pattern Analysis of forest fires occurrences in Canton Ticino (Switzerland)[A]. ICFBR 2011 International Conference on forest fire behaviour and risk focus on wildland urban interface[C]. Alghero (Sardinia),2011.
    [8] 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.
    [9] 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.
    [10] 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.
    [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.
    [12] Zhu Q J, Rong T Z, Sun R. A case study on fractal simulation of forest fire spread[J]. Science in China Series E:Technological Sciences, 2000, 43(S1):104~112.
    [13] Tian X R, Mcrae D J, Shu L F, et al. Satellite remote-sensing technologies used in forest fire management[J]. Journal of Forestry Research, 2005, 16(1):73~78.
    [14] 高懋芳,覃志豪,刘三超. MODIS数据在林火监测中的应用研究[J]. 国土资源遥感, 2005, 16(2):60-63.
    [15] 胡庆华,李兵.基于MODIS卫星数据的黑龙江省生物质燃烧火点时空分布[J].草业科学, 2018, 35(8):2049-2057.
    [16] 顾先丽,吴志伟,张宇婧,等.基于MODIS数据的2001-2015年江西省林火时空特征分析[J].广东农业科学, 2018, 45(6):129-134.
    [17] 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.
    [18] Liu W L, Wang L T, Zhou Y, et al. A comparison of forest fire burned area indices based on HJ satellite data[J]. Natural Hazards, 2016, 81(2):971~980.
    [19] 崔学明,王林和,周梅,等.MODIS及ASTER卫星数据在林火面积估算中的应用[J].干旱区资源与环境, 2008, 22(1):198~200.
    [20] 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.
    [21] Qin X L, Yan H, Zhan Z H, et al. Characterising vegetative biomass burning in China using MODIS data[J]. International Journal of Wildland Fire, 2014,23(1):69~77.
    [22] 李顺,吴志伟,梁宇,等.大兴安岭林火发生的时空聚集性特征[J].生态学杂志, 2017, 36(1):198~204.
    [23] 邓忠坚,李晓娜,周汝良,等.云南省卫星热点与林火格局的关系研究[J].西南林业大学学报, 2016, 36(4):132~137.
    [24] 阙华斐,谭三清,周璀,等.基于卫星监测的湖南省林火时空分布规律研究[J].中南林业科技大学学报, 2018, 38(6):61~65.
    [25] 覃先林.林火卫星遥感监测[M].北京:中国林业出版社,2016:7.
    [26] 吴升,黄智函.基于点模式的盗窃犯罪空间分布规律分析——以福州市主城区为例[J].福州大学学报:自然科学版, 2015(5):631~635.
    [27] Ripley BD. 1981. Spacial Statistics. Chichester:John Wiley.
    [28] Besag J E. Comments on Ripley's paper. Journal of Royal Statistic Society:Series B,1977,39:193~195
    [29] Kuhn H W, Kuenne R E. An efficient algorithm for the numerical solution of the Generalized Weber Problem in spatial economics. Journal of Regional Science, 1962,4(2):21~33.
    [30] Burt J E, Barber G.1996. Elementary statistics for geographers. Guilford, New York.
    [31] Eck J,Chainey S,Cameron J,et al. Mapping crime:understanding hotspots[M]. Washington D C:National Institute ofJustice,2005.
    [32] 肖金香,叶蕾,叶清,等. 冰雪冻害对森林火灾的影响及防御措施[J]. 江西农业大学学报, 2005, 31(3):433-436.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Get Citation
PDF
XML

Article views(572) PDF downloads(27) Cited by()

Related
Proportional views

A Study of Spatiotemporal Characteristics of Forest Fires in Sichuan Province Based on Point Pattern's Method

doi: 10.16779/j.cnki.1003-5508.2019.06.002
  • Research Institute of Forest Resource Information Technology, Chinese Academy of Forestry, Beijing 100084, China
  • Received Date: 2019-09-04

Abstract: The forest fire is an important factor of disturbing forest growth. Sichuan province was located in the southwest forest area with a high occurrence density area of forest fires.It could contribute to the forest fire prevention work by analyzing the distribution characteristics of fire occurrence in Sichuan province. Based on the MODIS fire product (MOD14A2/MYD14A2), Ripley K function, center point, standard deviational ellipse method and Kerne1 Density method were employed and the data clock was used to explore the spatial-temporal distribution of forest fires in Sichuan province from 2001 to 2012. The results showed that the annual forest fires fluctuated greatly in Sichuan province. The peak periods of forest fires were in January, February, March, April and May, and the number of forest fires continued to rise every year. On smaller spatial scale (less than 528 km), the spatial pattern of forest fires was clustering. The median center of forest fires occurred in Panzhihua city in 12 years, which was the area with highest fire density. The hot spots of forest fires were also located at Liangshan Yi Autonomous Prefecture and Ganzi Tibetan Autonomous Prefecture. The overall spread trend was to extend northwest to Ganzi Tibetan Autonomous Prefecture.

    HTML

Reference (32)

Catalog

    Back Issue Browsing

    Wechat

    《四川林业科技》编辑部版权所有 蜀ICP备19031520号-2  ssl证书签章   百度统计

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return