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题名:
基于GIS与RS的山东森林火险因子及火险区划
其他题名: Forest fire danger factors and their division in Shandong based on GIS and RS.
作者: 黄宝华1,2,3,4; 张华1; 孙治军4; 周利霞5
刊名: 生态学杂志
ISSN号: 1000-4890
出版日期: 2015
卷号: 34, 期号:5, 页码:1464-1472
关键词: 人为因素 ; 可访问性因素 ; 火险 ; 二项Logistic回归
产权排序: 中国科学院烟台海岸带研究所;烟台市地理信息中心;中国科学院大学;中国农业大学(烟台);烟台市自然博物馆;
通讯作者: 张华.中国科学院烟台海岸带研究所 Email:hzhang@yic.ac.cn
作者部门: 中科院海岸带环境过程与生态修复重点实验室
中文摘要: 森林火灾是山东森林地区严重的环境问题之一。本研究采用山东2001—2010年MOD14A1每日1 km温度异常/火L3级产品与地形、植被、天气、人为和可访问性数据,分析评估了火灾发生原因;收集了林火发生/未发生相关的15个解释变量的空间数据,利用二项Logistic回归模型估计了解释变量的函数与林火存在的概率。结果表明,高火险区域主要集中在黄河三角洲、鲁西北平原,包括德州、菏泽、济宁、枣庄南部、临沂东南部;中火险主要在聊城、滨州、济南北部、淄博北部、潍坊东部、泰安、日照和青岛大部分地区(包括蒙山林区、沂山林区、五莲山林区、徂徕山林区、尼山林区、泰莱林区);低火险主要集中在济南南部、淄博南部、莱...
英文摘要: 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 lire 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 southeastmoderate lire risk areas are mainly concentrated in Liaocheng, Binzhou south, Jinan north, Zibo northwest, Weil'ang east, Taian, Rizhao and Qingdao most areas (including Meng mountain lorest region, Yi mountain forest region, Wulian mountain lorest region, Culai mountain lorest region,Ni mountain forest region,Tailai mountain lorest region)  Low lire risk areas mainly concentrated in Jinan south, Zibo south, Laiwu, Qingdao south and Shandong peninsula (including Jinan mountain lorest area, Tai lai mountain lorest area, Laoshan mountain lorest area, Lu mountain lorest area, Kunyu mountain lorest region, Ya mountain lorest region). Logistic regression results showed that lactors influencing the lires 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.
项目资助者: 烟台市科技发展计划项目(2009163,2013ZH084)资助
文章类型: 期刊论文
收录类别: EI
语种: 中文
内容类型: 期刊论文
URI标识: http://ir.yic.ac.cn/handle/133337/8442
Appears in Collections:中科院海岸带环境过程与生态修复重点实验室_期刊论文

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作者单位: 1.中国科学院烟台海岸带研究所
2.烟台市地理信息中心
3.中国科学院大学
4.中国农业大学( 烟台)
5.烟台市自然博物馆

Recommended Citation:
黄宝华,张华,孙治军,等. 基于GIS与RS的山东森林火险因子及火险区划[J]. 生态学杂志,2015,34(5):1464-1472.
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