基于加权信息量模型的油松毛虫灾害发生危险性评价
|
摘要
【目的】充分考虑影响灾害发生及灾害等级的气象、地形地貌等多种因素,实现多因子灾害发生危险性评价和制图,以期为灾前的防控和预警提供依据。【方法】以辽宁省西部的油松人工林为研究区,基于Landsat影像提取油松分布范围,以高程、坡向、坡度、降雨量、活动积温、日照时数、上一年灾害程度和距离上一年重灾区远近8个危险性评价因子,采用层次分析法确定各因子权重,建立加权信息量模型,结合GIS空间分析方法,将油松的受灾危险性划分为5个等级:极低危险区、低危险区、中危险区、高危险区和极高危险区,实现危险区划制图,并与实际灾害程度监测结果对比进行精度验证。【结果】1)根据信息量法原理,信息量值越大代表发生灾害的危险性越大。本文计算得到的各因子类别信息量值均与油松毛虫的生物学特性相吻合。2)研究区2017年虫灾极高和高危险区主要分布在建平县北部,中危险区主要分布在北部部分地区和建平县与凌源市交汇处,其他地区发生虫灾危险性较低,与实际调查结果相吻合。3)最终划分等级中的中低危险区和实际受灾油松失叶率大小对应关系明显,实际成灾油松林地中有90.32%被划分至高危险区和极高危险区。【结论】基于加权信息量模型的油松毛虫灾害发生危险性评价充分考虑了不同评价因子对灾害发生影响程度的差异,得到的风险区划结果较为准确,具有应用价值,可为大区域的森林病虫害危险性评价及风险评估提供技术依据。
【Objective】The pine caterpillar, Dendrolimus tabulaeformis(Lepidoptera: Lasiocampidae) is a serious defoliator in the stands of Pinus tabulaeformis in China. In this study, a multi-factor disaster risk assessment method is proposed for prevention and early warning before the pest disaster, which is based on climate, topography and other factors that affect disaster occurrence and disaster grade. 【Method】 The distribution range of P. tabulaeformis was extracted from Landsat data in Western Liaoning Province. The eight risk assessment factors, including elevation, aspect, slope, rainfall, accumulated temperature, sunshine hours, disaster degree in the previous year and the distance from the disaster area in the previous year, were collected, and then the weight of each factor was determined by analytic hierarchy process. Finally, a weighted information model was established. Combining with the spatial analysis method of GIS, the disaster risk of P. tabulaeformis was classified into five levels: extremely low-risk area, low-risk area, medium-risk area, high-risk area and extremely high-risk area. A hazard zone map was made with the above information and the accuracy is verified by comparing with the monitoring result of actual disaster degree. 【Result】 1) According to the principle of information quantity method, the greater the amount of information, the greater the risk of disaster. The information values of each factor classification calculated in this paper coincided with the biological characteristics of D. tabulaeformis. 2) The mapping results showed that in 2017 high-risk area and the extremely high-area in the study area was mainly distributed in the northern part of Jianping county. Medium-risk areas were mainly located in the northern part of Jianping County and the interchange between Jianping and Lingyuan. The risk of the insect pest in other areas was low. The mapping results were consistent with the actual survey results. 3) The relationship between the finally classified middle-low risk areas and the actual defoliation rate of P. tabulaeformis is obvious. Around 90.32% of the actual infested P. tabulaeformis forests are classified into high risk areas and extremely high areas. 【Conclusion】Based on the weighted information model, the risk assessment of pine caterpillar disaster comprehensively considers the difference of the impact of different evaluation factors on the disaster occurrence. The result of risk zoning is accurate and has certain application value. It can provide technical basis for the risk assessment of forest pests and diseases in large areas.
【Objective】The pine caterpillar, Dendrolimus tabulaeformis(Lepidoptera: Lasiocampidae) is a serious defoliator in the stands of Pinus tabulaeformis in China. In this study, a multi-factor disaster risk assessment method is proposed for prevention and early warning before the pest disaster, which is based on climate, topography and other factors that affect disaster occurrence and disaster grade. 【Method】 The distribution range of P. tabulaeformis was extracted from Landsat data in Western Liaoning Province. The eight risk assessment factors, including elevation, aspect, slope, rainfall, accumulated temperature, sunshine hours, disaster degree in the previous year and the distance from the disaster area in the previous year, were collected, and then the weight of each factor was determined by analytic hierarchy process. Finally, a weighted information model was established. Combining with the spatial analysis method of GIS, the disaster risk of P. tabulaeformis was classified into five levels: extremely low-risk area, low-risk area, medium-risk area, high-risk area and extremely high-risk area. A hazard zone map was made with the above information and the accuracy is verified by comparing with the monitoring result of actual disaster degree. 【Result】 1) According to the principle of information quantity method, the greater the amount of information, the greater the risk of disaster. The information values of each factor classification calculated in this paper coincided with the biological characteristics of D. tabulaeformis. 2) The mapping results showed that in 2017 high-risk area and the extremely high-area in the study area was mainly distributed in the northern part of Jianping county. Medium-risk areas were mainly located in the northern part of Jianping County and the interchange between Jianping and Lingyuan. The risk of the insect pest in other areas was low. The mapping results were consistent with the actual survey results. 3) The relationship between the finally classified middle-low risk areas and the actual defoliation rate of P. tabulaeformis is obvious. Around 90.32% of the actual infested P. tabulaeformis forests are classified into high risk areas and extremely high areas. 【Conclusion】Based on the weighted information model, the risk assessment of pine caterpillar disaster comprehensively considers the difference of the impact of different evaluation factors on the disaster occurrence. The result of risk zoning is accurate and has certain application value. It can provide technical basis for the risk assessment of forest pests and diseases in large areas.
引文
白雪琪,张晓丽,张凝,等.2016.基于高光谱遥感的油松毛虫危害程度监测模型.北京林业大学学报,38(11):16-22.(Bai X Q,Zhang X L,Zhang N,et al.2016.Monitoring model of dendrolimus tabulaeformis disaster using hyperspectral remote sensing technology.Journal of Beijing Forestry University,38(11):16-22.[in Chinese])
曾菊平,戈峰,苏建伟,等.2010.我国林业重大害虫松毛虫的灾害研究进展.昆虫知识,47(3):451-459.(Zeng J P,Ge F,Su J W,et al.2010.Researches on the occurrences of major forest insect pests of pine caterpillar Dendrolimus spp.in China.Chinese Bulletin of Entomology,47(3):451-459.[in Chinese])
陈昌洁.1990.松毛虫综合管理.北京:中国林业出版社.(Chen C J.1990.Integrated management of Dendrolimus.Beijing:China Forestry Publishing House.[in Chinese])
陈福海.2012.马尾松毛虫害遥感监测及其影响因子分析.福建:福建农林大学硕士学位论文.(Chen F H.2012.Dendrolimus punctatus damage remote sensing monitoring and influence factors analysis.Fujian:MS thesis of Fujian Agriculture and Forestry University.[in Chinese])
董厚德.2010.辽宁植被与植被区划.沈阳:辽宁大学出版社.(Dong H D.2011.Vegetation and vegetation regionalization in Liaoning.Shenyang:Liaoning University Press.[in Chinese])
郭安红,王纯枝,李轩,等.2012.东北地区落叶松毛虫灾害气象风险区划初步研究.灾害学,27(2):24-28.(Guo A H,Wang C Z,Li X,et al.2012.Preliminary study on meteorological risk zoning of pine moth infestation in northeast China.Journal of Catastrophology,27(2):24-28.[in Chinese])
侯陶谦.1987.中国松毛虫.北京:科学出版社.(Hou T Q.1987.Chinese Dendrolimus.Beijing:Science Press.[in Chinese])
李燕.2013.油松毛虫的生物学特性及其防治.现代农业科技,21:165-167.(Li Y.2013.Biology characteristic and prevention of Chinese pine larva aculeata.Modern Agricultural Sciences and Technology,21:165-167.[in Chinese])
罗元华.1998.地质灾害风险评估方法.北京:地质出版社.(Luo Y H.1998.Geological hazard risk assessment method.Beijing:Geological Press.[in Chinese])
牛淑贤,罗科资,牛保忠.2008.油松毛虫对油松生长发育的影响及防治.陕西林业科技,(2):98-100,109.(Niu S X,Luo K Z,Niu B Z.2008.Impact of Chinese pine caterpillar on growth and development of Pinus tabulaeformis Carr.and corresponding measures for control.Shaanxi Forest Science and Technology,(2):98-100,109.[in Chinese])
宋雄刚.2015.油松毛虫发生林分因子分析及气候情景模式下的灾害趋势预测.北京:中国林业科学研究院硕士学位论文.(Song X G.2015.Analysis of Dendrolimus tabulaeformis occurrence with the stand parameters of Pinus tabulaeformis and prediction under climate scenarios.Beijing:MS thesis of Chinese Academy of Forestry.[in Chinese])
王文权.2007.辽宁森林资源.北京:中国林业出版社.(Wang W Q.2007.Forest resources in Liaoning.Beijing:Chinese Forestry Press.[in Chinese])
吴柳萍,纪志荣,连素兰,等.2017.福建省森林病虫害发生风险的概率分析.森林与环境学报,37(1):95-101.(Wu L P,Ji Z R,Lian S L,et al.2017.Probability analysis of forest pests occurring risk in Fujian Province.Journal of Forest and Environment,37(1):95-101.[in Chinese])
夏乃斌,屠泉洪,王玉兰.1987.油松毛虫发育起点温度和有效积温的研究.林业科学,23(3):314-319.(Xia N B,Tu Q H,Wang Y L.1987.A study of developmental threshold and effective accumulated temperature of Chinese-caterpillar (Dendrolimus Tabulaeformis).Scientia Silvae Sinicae,23(3):314-319.[in Chinese])
萧刚柔.1992.中国森林昆虫.北京:中国林业出版社.(Xiao G R.1992.Forest insects in China.Beijing:Chinese Forestry Press.[in Chinese])
张丽丽.2005.影响油松毛虫生长发育的几个因素的探讨.北京:北京林业大学硕士学位论文.(Zhang L L.2005.Study of influencing on growth and development of Dendrolimus punctatus tabulaeformis.Beijing:MS thesis of Beijing Forestry University.[in Chinese])
赵勇强,周国娜,李明,等.2005.松毛虫发生程度影响因素分析.河北林果研究,20(3):273-279.(Zhao Y Q,Zhou G N,Li M,et al.2005.Analysis of affecting factors on the incidence extent of Dendrolimus spp.Hebei Journal of Forestry and Orchard research,20(3):273-279.[in Chinese])
朱程浩,瞿帅,张晓丽.2016.油松毛虫灾害遥感监测及其影响因子分析.遥感学报,20(4):653-664.(Zhu C H,Qu S,Zhang X L.2016.Dendrolimus tabulaeformis disaster monitoring and analysis of its influencing factors through remote sensing technology.Journal of Remote Sensing,20(4):653-664.[in Chinese])
Christelle R,Nico V O,Richard B,et al.2011.Applying a spread model to identify the entry points from which the pine wood nematode,the vector of pine wilt disease,would spread most rapidly across Europe.Biological Invasions,13(12):2981-2995.
Huang M,Liang G,Gong J,et al.2013.Bayesian network and factor analysis for modeling pine wilt disease prevalence.Journal of Software Engineering & Applications,6 (3):13-17.
Kong X B,Liu K W,Wang H B,et al.2012.Identification and behavioral evaluation of sex pheromone components of the Chinese pine caterpillar moth,Dendrolimus tabulaeformis.PloS One,7(3):e33381.
Li D X.2008.Integrated control measures of Dendrolimus tabulaeformis Tsai et Liu.Sci-Tech Information Development & Economy,18:226-227.
Ray D,Peace A,Moore1 R.2016.Improved prediction of the climate-driven outbreaks of Dendrolimus pini in Pinus sylvestris forests.Forestry,89(2):230-244.
Robinet C,Opstal N V,Barker R,et al.2011.Appling a spread model to identify the entry points from which the pine wood nematode,the vector of pine wilt disease,would spread most rapidly across Europe.Biological Invasions,13(12):2981-2995.
Shannon C E.1948.A mathematical theory of communication.Bell Labs Technical Journal,27(4):623-656.
Westen C J.2000.The modeling of landslide hazards using GIS.Surveys in Geophysics,21(2/3):241-255.
Zhang S F,Zhang Z,Wang H B,et al.2014.Molecular characterization,expression pattern,and ligand-binding property of three odorant binding protein genes from Dendrolimus tabulaeformis.Journal of Chemical Ecology,40:396-406.
Zhu C H,Zhang X L,Zhang N,et al.2018.Assessing the defoliation of pine forests in a long time-series and spatiotemporal prediction of the defoliation using Landsat data.Remote Sensing,10(3):360.
曾菊平,戈峰,苏建伟,等.2010.我国林业重大害虫松毛虫的灾害研究进展.昆虫知识,47(3):451-459.(Zeng J P,Ge F,Su J W,et al.2010.Researches on the occurrences of major forest insect pests of pine caterpillar Dendrolimus spp.in China.Chinese Bulletin of Entomology,47(3):451-459.[in Chinese])
陈昌洁.1990.松毛虫综合管理.北京:中国林业出版社.(Chen C J.1990.Integrated management of Dendrolimus.Beijing:China Forestry Publishing House.[in Chinese])
陈福海.2012.马尾松毛虫害遥感监测及其影响因子分析.福建:福建农林大学硕士学位论文.(Chen F H.2012.Dendrolimus punctatus damage remote sensing monitoring and influence factors analysis.Fujian:MS thesis of Fujian Agriculture and Forestry University.[in Chinese])
董厚德.2010.辽宁植被与植被区划.沈阳:辽宁大学出版社.(Dong H D.2011.Vegetation and vegetation regionalization in Liaoning.Shenyang:Liaoning University Press.[in Chinese])
郭安红,王纯枝,李轩,等.2012.东北地区落叶松毛虫灾害气象风险区划初步研究.灾害学,27(2):24-28.(Guo A H,Wang C Z,Li X,et al.2012.Preliminary study on meteorological risk zoning of pine moth infestation in northeast China.Journal of Catastrophology,27(2):24-28.[in Chinese])
侯陶谦.1987.中国松毛虫.北京:科学出版社.(Hou T Q.1987.Chinese Dendrolimus.Beijing:Science Press.[in Chinese])
李燕.2013.油松毛虫的生物学特性及其防治.现代农业科技,21:165-167.(Li Y.2013.Biology characteristic and prevention of Chinese pine larva aculeata.Modern Agricultural Sciences and Technology,21:165-167.[in Chinese])
罗元华.1998.地质灾害风险评估方法.北京:地质出版社.(Luo Y H.1998.Geological hazard risk assessment method.Beijing:Geological Press.[in Chinese])
牛淑贤,罗科资,牛保忠.2008.油松毛虫对油松生长发育的影响及防治.陕西林业科技,(2):98-100,109.(Niu S X,Luo K Z,Niu B Z.2008.Impact of Chinese pine caterpillar on growth and development of Pinus tabulaeformis Carr.and corresponding measures for control.Shaanxi Forest Science and Technology,(2):98-100,109.[in Chinese])
宋雄刚.2015.油松毛虫发生林分因子分析及气候情景模式下的灾害趋势预测.北京:中国林业科学研究院硕士学位论文.(Song X G.2015.Analysis of Dendrolimus tabulaeformis occurrence with the stand parameters of Pinus tabulaeformis and prediction under climate scenarios.Beijing:MS thesis of Chinese Academy of Forestry.[in Chinese])
王文权.2007.辽宁森林资源.北京:中国林业出版社.(Wang W Q.2007.Forest resources in Liaoning.Beijing:Chinese Forestry Press.[in Chinese])
吴柳萍,纪志荣,连素兰,等.2017.福建省森林病虫害发生风险的概率分析.森林与环境学报,37(1):95-101.(Wu L P,Ji Z R,Lian S L,et al.2017.Probability analysis of forest pests occurring risk in Fujian Province.Journal of Forest and Environment,37(1):95-101.[in Chinese])
夏乃斌,屠泉洪,王玉兰.1987.油松毛虫发育起点温度和有效积温的研究.林业科学,23(3):314-319.(Xia N B,Tu Q H,Wang Y L.1987.A study of developmental threshold and effective accumulated temperature of Chinese-caterpillar (Dendrolimus Tabulaeformis).Scientia Silvae Sinicae,23(3):314-319.[in Chinese])
萧刚柔.1992.中国森林昆虫.北京:中国林业出版社.(Xiao G R.1992.Forest insects in China.Beijing:Chinese Forestry Press.[in Chinese])
张丽丽.2005.影响油松毛虫生长发育的几个因素的探讨.北京:北京林业大学硕士学位论文.(Zhang L L.2005.Study of influencing on growth and development of Dendrolimus punctatus tabulaeformis.Beijing:MS thesis of Beijing Forestry University.[in Chinese])
赵勇强,周国娜,李明,等.2005.松毛虫发生程度影响因素分析.河北林果研究,20(3):273-279.(Zhao Y Q,Zhou G N,Li M,et al.2005.Analysis of affecting factors on the incidence extent of Dendrolimus spp.Hebei Journal of Forestry and Orchard research,20(3):273-279.[in Chinese])
朱程浩,瞿帅,张晓丽.2016.油松毛虫灾害遥感监测及其影响因子分析.遥感学报,20(4):653-664.(Zhu C H,Qu S,Zhang X L.2016.Dendrolimus tabulaeformis disaster monitoring and analysis of its influencing factors through remote sensing technology.Journal of Remote Sensing,20(4):653-664.[in Chinese])
Christelle R,Nico V O,Richard B,et al.2011.Applying a spread model to identify the entry points from which the pine wood nematode,the vector of pine wilt disease,would spread most rapidly across Europe.Biological Invasions,13(12):2981-2995.
Huang M,Liang G,Gong J,et al.2013.Bayesian network and factor analysis for modeling pine wilt disease prevalence.Journal of Software Engineering & Applications,6 (3):13-17.
Kong X B,Liu K W,Wang H B,et al.2012.Identification and behavioral evaluation of sex pheromone components of the Chinese pine caterpillar moth,Dendrolimus tabulaeformis.PloS One,7(3):e33381.
Li D X.2008.Integrated control measures of Dendrolimus tabulaeformis Tsai et Liu.Sci-Tech Information Development & Economy,18:226-227.
Ray D,Peace A,Moore1 R.2016.Improved prediction of the climate-driven outbreaks of Dendrolimus pini in Pinus sylvestris forests.Forestry,89(2):230-244.
Robinet C,Opstal N V,Barker R,et al.2011.Appling a spread model to identify the entry points from which the pine wood nematode,the vector of pine wilt disease,would spread most rapidly across Europe.Biological Invasions,13(12):2981-2995.
Shannon C E.1948.A mathematical theory of communication.Bell Labs Technical Journal,27(4):623-656.
Westen C J.2000.The modeling of landslide hazards using GIS.Surveys in Geophysics,21(2/3):241-255.
Zhang S F,Zhang Z,Wang H B,et al.2014.Molecular characterization,expression pattern,and ligand-binding property of three odorant binding protein genes from Dendrolimus tabulaeformis.Journal of Chemical Ecology,40:396-406.
Zhu C H,Zhang X L,Zhang N,et al.2018.Assessing the defoliation of pine forests in a long time-series and spatiotemporal prediction of the defoliation using Landsat data.Remote Sensing,10(3):360.