Welcome to Chinese Journal of Ecology! Today is Share:

cje

Previous Articles    

Forest fire danger factors and their division in Shandong based on GIS and RS.

HUANG Bao-hua1,2,3,4, ZHANG Hua1**, SUN Zhi-jun4, ZHOU Li-xia5   

  1. (1Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, Shandong, China; 2Geographic Information Center of Yantai City, Yantai 264003, Shandong, China; 3University of Chinese Academy of Sciences, Beijing 100049, China; 4China Agricultural University (Yantai), Yantai 264670, Shandong, China; 5Yantai Museum of Natural History, Yantai 264000, Shandong, China)
  • Online:2015-05-10 Published:2015-05-10

Abstract: Forest fire is one of the serious environmental problems in Shandong forest areas. MOD14A1 daily temperature anomaly/fire L3 level products of 2001-2010 and topography, vegetation, weather, anthropogenic and accessibility data in Shandong were used to evaluate fire causes. The spatial data of 15 variables that relate to forest fire/no fire were collected, and the functions of these variables and fire probability were estimated by using binomial Logistic regression model.
that high fire risk areas are mainly concentrated in Yellow River delta, Shandong northwest plain,include Heze, Jining, Zaozhuang south, Linyi southeast; moderate fire risk areas are mainly concentrated in Liaocheng, Binzhou south, Jinan north, Zibo northwest, Weifang east, Taian, Rizhao and Qingdao most areas (including Meng mountain forest region, Yi mountain forest region, Wulian mountain forest region, Culai mountain forest region, Ni mountain forest region, Tailai mountain forest region); Low fire risk areas mainly concentrated in Jinan south, Zibo south, Laiwu, Qingdao south and Shandong peninsula (including Jinan mountain forest area, Tai lai mountain forest area, Laoshan mountain forest area, Lu mountain forest area, Kunyu mountain forest region, Ya mountain forest region). Logistic regression results showed that factors influencing the fires were in order of annual average temperature, CTI, TPI, population density, vegetation type, annual precipitation, vegetation coverage, distance from the road, aspect, distance from the residents, farmers’ net income index, slope, annual average relative humidity, DEM, annual evaporation. The EXP (B) values of the top seven factors were greater than 1, having great contributions to forest fires. These results can be used as a strategic planning tool to better predict forest fire, and also be used as a tactical guide to help forest management personnel for fire protection area design.

Key words: ecosystem service flow, spatial and temporal scale, distributed ecosystem model, abiotic flow, big data