Model and zoning of forest fire risk in Heilongjiang province based on spatial Logistic

被引：0
作者：
Deng, Ou [1 ,2 ]
Li, Yiqiu [2 ,3 ]
Feng, Zhongke [1 ]
Zhang, Dongyou [4 ]
机构：
[1] Institute of Geomatics and Geographic Information System, Remote Sensing and Global Positioning System, Beijing Forestry University
[2] Department of Resource and Environment, Mianyang Normal University
[3] Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences
[4] Department of Life and Environment, Harbin Normal University
来源：
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2012年 / 28卷 / 08期
关键词：
Forest fire; Heilongjiang province; Logistics; Risks; Zoning;
D O I：
10.3969/j.issn.1002-6819.2012.08.031
中图分类号：
学科分类号：
摘要：
Forest fire risk analysis and forest fire risk zoning are important parts of the forest fire management. MODIS burn scars of remote sensing data sets MCD45A1 of Heilongjiang Province in 2000-2010 was used to build the spatial logistic forest fire risk model based on the spatial distribution of forest fire and forest fire impact factor by using geographic information system technology. Forest fire risk zoning study was conducted in a larger temporal scale and provincial spatial scale. Logistic model of forest fire risk built by spatial sampling between the distribution of forest fires and forest fire impact factor fit well (p<0.05). The relative operating characteristic value was 0.753 and the probability distribution map of forest fire was gotten by layer computing. Forest fire area of Heilongjiang province was divided into none, low, moderate, high, and extremely high fire risk zones. Extremely high and high fire risk zone were located at Great Xing'an Mountain, while high or moderate fire risk area at Xiaoxing'an Mountain basically. Small parts of the eastern mountain were in moderate fire risk, and other areas in low or none fire risk. Quantitative and positioning evaluation of the forest fire in Heilongjiang province provides scientific basis for the prevention of forest fire fighting and rescue work.
引用
收藏
页码：200 / 205
页数：5
相关论文
共 24 条
  • [11] Guan W., Han D., Comprehensive fuzzy evaluation on forestry fire-danger scale, Forest Engineering, 20, 3, pp. 17-19, (2004)
  • [12] Liu Z., Study on forest fire risk zone mapping based on geomatics, pp. 4-6, (2008)
  • [13] Li F., Forest fire monitoring model and application research based on EOS/MODIS, pp. 8-12, (2005)
  • [14] Boles S.H., Verbyla D.L., Comparison of three AVHRR-based fire detection algorithms for interior Alaska, Remote Sensing of Environment, 72, 1, pp. 1-16, (2000)
  • [15] Tang J., Zhang X., Study on the division of forest fire danger in the forestry bureau by using remote sensing and geographical information system, Journal of Beijing Forestry University, 18, 1, pp. 1-5, (1996)
  • [16] Jaiswal R.K., Mukherjee S., Raju K.D., Et al., Forest fire risk zone mapping from satellite imagery and GIS, International Journal of Applied Earth Observation and Geoinformation, 4, 1, pp. 1-10, (2002)
  • [17] Zhang G., Liu F., Yang Z., Study of Guangzhou's forest fire hazardous areas based on RS and GIS, Journal of Central South Forestry University, 23, 4, pp. 62-65, (2003)
  • [18] Liu Z., Liu J., Yu K., Et al., Classification of forest fire risk rank based on RS and GIS, Journal of Fujian Agriculture and Forestry University, 37, 6, pp. 606-609, (2008)
  • [19] Liu Z., Yang J., He H., Et al., Spatial point analysis of fire occurrence and its influence factor in Huzhong forest area of the Great Xing'an Mountains in Heilongjiang Province, China, Acta Ecologica Sinica, 31, 6, pp. 1669-1677, (2011)
  • [20] Wang M., Shu L., Tian X., Et al., Influences of ENSO events on forest fires in Heilongjiang Province, Forestry Research, 23, 5, pp. 644-648, (2010)
123