Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have dev...Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.展开更多
Forest fires caused by natural forces or human activities are one of the major natural risks in Northeast China.The incidence and spatial distribution of these fires vary over time and across the forested areas in Jil...Forest fires caused by natural forces or human activities are one of the major natural risks in Northeast China.The incidence and spatial distribution of these fires vary over time and across the forested areas in Jilin Province,Northeast China.In this study,the incidence and distribution of 6519 forest fires from 1969 to 2013 in the province were investigated.The results indicated that the spatiotemporal distribution of the burnt forest area and the fire frequency varied significantly by month,year,and region.Fire occurrence displayed notable temporal patterns in the years after forest fire prevention measures were strictly implemented by the provincial government.Generally,forest fires in Jilin occurred in months when stubble and straw were burned and human activities were intense during traditional Chinese festivals.Baishan city,Jilin city,and Yanbian were defined as fire-prone regions for their high fire frequency.Yanbian had the highest frequency,and the fires tended to be large with the highest burned area per fire.Yanbian should thus be listed as the key target area by the fire management agency in Jilin Province for better fire prevention.展开更多
We evaluated the spatial and temporal patterns of forest fires in two fire seasons(March to June and September to November) from 1996 to 2010 in Jilin Province,China,using the Canadian Forest Fire Weather Index System...We evaluated the spatial and temporal patterns of forest fires in two fire seasons(March to June and September to November) from 1996 to 2010 in Jilin Province,China,using the Canadian Forest Fire Weather Index System.Fire data were obtained from the Provincial Fire Agency,and historical climate records of daily weather observations were collected from 36 weather stations in Jilin and its neighboring provinces.A linear regression model was used to analyze linear trends between climate and fire weather indices with time treated as an independent variable.Correlation analysis was used to detect correlations between fire frequency,areas burned,and fire weather indices.A thin-plate smooth spline model was used to interpolate the point data of 36 weather stations to generate a surface covering the whole province.Our analyses indicated fire frequency and areas burned were significantly correlated with fire weather indices.Overall,the Canadian Forest Fire Weather Index System appeared to be work well for determining the fire danger rating in Jilin Province.Also,our analyses indicated that in the forthcoming decades,the overall fire danger in March and April should decrease across the province,but the chance of a large fire in these months would increase.The fire danger in the fall fire season would increase in the future,and the chance of large fire would also increase.Historically,because most fires have occurred in the spring in Jilin Province,such a shift in the future fire danger between the two fire seasons would be beneficial for the province's fire management.展开更多
Fire-induced forest loss has substantially increased worldwide over the last decade.In China,the connection between forest loss and frequent fi res on a national scale remains largely unexplored.In this study,we used ...Fire-induced forest loss has substantially increased worldwide over the last decade.In China,the connection between forest loss and frequent fi res on a national scale remains largely unexplored.In this study,we used a data set for a time-series of forest loss from the Global Forest Watch and for a MODIS-derived burned area for 2003–2015 to ascertain variations in forest loss and to explore its relationship with forest fi res(represented by burned areas)at the country-and forest-zone levels.We quantifi ed trends in forest loss during 2003–2015 using linear regression analysis and assessed the relation between forest loss and burned areas using Spearman’s correlation.Forest loss increased signifi cantly(264.8 km 2 a−1;R 2=0.54,p<0.01)throughout China,with an average annual increase of 11.4%during 2003–2015.However,the forest loss trend had extensive spatial heterogeneity.Forest loss increased mainly in the subtropical evergreen broadleaf forest zone(315.0 km 2 a−1;R 2=0.69,p<0.01)and tropical rainforest zone(38.8 km 2 a−1;R 2=0.66,p<0.01),but the loss of forest decreased in the cold temperate deciduous coniferous forest zone(−70.8 km 2 year−1;R 2=0.75,p<0.01)and the temperate deciduous mixed broadleaf and coniferous forest zone(−14.4 km 2 a−1;R 2=0.45,p<0.05).We found that 1.0%of China’s area had a signifi cant positive correlation(r≥0.55,p<0.05)with burned areas and 0.3%had a signifi cant negative correlation(r≤−0.55,p<0.05).In particular,forest loss had a signifi cant positive relationship with the burned area in the cold temperate deciduous coniferous forest zone(16.9% of the lands)and the subtropical evergreen broadleaf forest zone(7.8%).These results provide a basis for future predictions of fi re-induced forest loss in China.展开更多
Underground fires are characterized by smouldering combustion with a slow rate of spread rate and without flames.Although smouldering combustion releases large amounts of gaseous pollutants,it is difficult to discover...Underground fires are characterized by smouldering combustion with a slow rate of spread rate and without flames.Although smouldering combustion releases large amounts of gaseous pollutants,it is difficult to discover by today's forest fire monitoring technologies.Carbon monoxide(CO),nitrogen oxides(NO_(x))and sulfur dioxide(SO_(2))were identified as high concentration marker gases of smouldering combustion-easily-be monitored.According to a two-way ANOVA,combustion time had a significant impact on CO and NO_(x) emissions;smoldering-depth also had a significant impact on NO_(x) emissions but not on CO emissions.Gas emission equations were established by multiple linear regression,C_(co)=156.989-16.626 t and C_(NOx)=3.637-0.252 t-0.039 h.展开更多
Forest fires are influenced by several factors,including forest location,species type,age and density,date of fire occurrence,temperatures,and wind speeds,among others.This study investigates the quantitative effects ...Forest fires are influenced by several factors,including forest location,species type,age and density,date of fire occurrence,temperatures,and wind speeds,among others.This study investigates the quantitative effects of these factors on the degree of forest fire disaster using nonparametric statistical methods to provide a theoretical basis and data support for forest fire management.Data on forest fire damage from 1969 to 2013 was analyzed.The results indicate that different forest locations and types,fire occurrence dates,temperatures,and wind speeds were statistically significant.The eastern regions of the study area experienced the highest fire occurrence,accounting for 85.0%of the total number of fires as well as the largest average forested area burned.April,May,and October had more frequent fires than other months,accounting for 78.9%,while September had the most extensive forested area burned(63.08 ha)and burnt area(106.34 ha).Hardwood mixed forest and oak forest had more frequent fires,accounting for 31.9%and 26.0%,respectively.Hardwood-conifer mixed forest had the most forested area burned(50.18 ha)and burnt area(65.09 ha).Temperatures,wind speeds,and their interaction had significant impacts on forested area burned and area burnt.展开更多
Underground fires are a smoldering combustion with a slow spread rate, low temperatures and no flame. They can last from days to several months, and can even become overwintering fires. They are difficult to find, lea...Underground fires are a smoldering combustion with a slow spread rate, low temperatures and no flame. They can last from days to several months, and can even become overwintering fires. They are difficult to find, leading to considerable damage to the forests. The moisture content of combustible fuels is an important factor in the occurrence and persistence of underground forest fires. The Daxing’an Mountains are a hot spot for underground fires in China. This paper looks at the influence of different moisture contents on underground fire characteristics using simulation combustion experiments in the laboratory. The study showed that peak temperature and spread rate fluctuation of humus at different moisture levels increased with humus depth. Peak temperature and spread rate fluctuation of humus at different depths decreased with increased moisture;moisture content and depth of humus had a significant effect on peak temperature and spread rate fluctuation;peak temperature at different depths decreased with increased moisture;the spread rate in upper layers increased with moisture content, while the spread rate in the lower layers decreased with increased moisture content.展开更多
Underground fires are slow spreading,long-lasting and low temperature smoldering combustion without flames,mainly occurring in peatlands and wetlands with rich organic matter.The spread of the smoldering is maintained...Underground fires are slow spreading,long-lasting and low temperature smoldering combustion without flames,mainly occurring in peatlands and wetlands with rich organic matter.The spread of the smoldering is maintained by heat released during combustion and monitoring this is an important approach to detect underground fires.The Daxing'an Mountains region is a hotspot for underground fires in northeast China.This study examined a L arix gmelinii plantation in the Tatou wetlands of the Daxing'an Mountains and determined the maximum temperature variation of humus of varying particle sizes,and the temperature rising process based on non-linear mixed effects models by an indoor combustion experiment.Maximum combustion temperatures up to 897.5°C,increased with humus depth;among the three models tested,Richard's equations were best for characterizing temperature variations;a non-linear equation with three parameters had the highest accuracy in fitting the combustion temperature variations with varying humus particle sizes.These results are informative for predicting temperature variations and provide technical support for underground fire monitoring.展开更多
基金This research was funded by the National Natural Science Foundation of China(grant no.32271881).
文摘Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.
基金financially supported by the National Key Research and Development Plan(2017YFD0600106)the National Natural Science Foundation of China under Grant31470497+1 种基金Project 2013-007,Jilin Provincial Forestry Departmentsupported by the Program for New Century Excellent Talents in University(NCET-12-0726)
文摘Forest fires caused by natural forces or human activities are one of the major natural risks in Northeast China.The incidence and spatial distribution of these fires vary over time and across the forested areas in Jilin Province,Northeast China.In this study,the incidence and distribution of 6519 forest fires from 1969 to 2013 in the province were investigated.The results indicated that the spatiotemporal distribution of the burnt forest area and the fire frequency varied significantly by month,year,and region.Fire occurrence displayed notable temporal patterns in the years after forest fire prevention measures were strictly implemented by the provincial government.Generally,forest fires in Jilin occurred in months when stubble and straw were burned and human activities were intense during traditional Chinese festivals.Baishan city,Jilin city,and Yanbian were defined as fire-prone regions for their high fire frequency.Yanbian had the highest frequency,and the fires tended to be large with the highest burned area per fire.Yanbian should thus be listed as the key target area by the fire management agency in Jilin Province for better fire prevention.
基金financially supported by the National Natural Science Foundation of China(31470497)Project 2013-158,Jilin Provincial Education Department+1 种基金Project 2013-007,Jilin Provincial Forestry Departmentsupported by the Program for New Century Excellent Talents in the University(NCET-12-0726)
文摘We evaluated the spatial and temporal patterns of forest fires in two fire seasons(March to June and September to November) from 1996 to 2010 in Jilin Province,China,using the Canadian Forest Fire Weather Index System.Fire data were obtained from the Provincial Fire Agency,and historical climate records of daily weather observations were collected from 36 weather stations in Jilin and its neighboring provinces.A linear regression model was used to analyze linear trends between climate and fire weather indices with time treated as an independent variable.Correlation analysis was used to detect correlations between fire frequency,areas burned,and fire weather indices.A thin-plate smooth spline model was used to interpolate the point data of 36 weather stations to generate a surface covering the whole province.Our analyses indicated fire frequency and areas burned were significantly correlated with fire weather indices.Overall,the Canadian Forest Fire Weather Index System appeared to be work well for determining the fire danger rating in Jilin Province.Also,our analyses indicated that in the forthcoming decades,the overall fire danger in March and April should decrease across the province,but the chance of a large fire in these months would increase.The fire danger in the fall fire season would increase in the future,and the chance of large fire would also increase.Historically,because most fires have occurred in the spring in Jilin Province,such a shift in the future fire danger between the two fire seasons would be beneficial for the province's fire management.
基金We are grateful to Zhihua Liu for his constructive comments to improve the manuscript.
文摘Fire-induced forest loss has substantially increased worldwide over the last decade.In China,the connection between forest loss and frequent fi res on a national scale remains largely unexplored.In this study,we used a data set for a time-series of forest loss from the Global Forest Watch and for a MODIS-derived burned area for 2003–2015 to ascertain variations in forest loss and to explore its relationship with forest fi res(represented by burned areas)at the country-and forest-zone levels.We quantifi ed trends in forest loss during 2003–2015 using linear regression analysis and assessed the relation between forest loss and burned areas using Spearman’s correlation.Forest loss increased signifi cantly(264.8 km 2 a−1;R 2=0.54,p<0.01)throughout China,with an average annual increase of 11.4%during 2003–2015.However,the forest loss trend had extensive spatial heterogeneity.Forest loss increased mainly in the subtropical evergreen broadleaf forest zone(315.0 km 2 a−1;R 2=0.69,p<0.01)and tropical rainforest zone(38.8 km 2 a−1;R 2=0.66,p<0.01),but the loss of forest decreased in the cold temperate deciduous coniferous forest zone(−70.8 km 2 year−1;R 2=0.75,p<0.01)and the temperate deciduous mixed broadleaf and coniferous forest zone(−14.4 km 2 a−1;R 2=0.45,p<0.05).We found that 1.0%of China’s area had a signifi cant positive correlation(r≥0.55,p<0.05)with burned areas and 0.3%had a signifi cant negative correlation(r≤−0.55,p<0.05).In particular,forest loss had a signifi cant positive relationship with the burned area in the cold temperate deciduous coniferous forest zone(16.9% of the lands)and the subtropical evergreen broadleaf forest zone(7.8%).These results provide a basis for future predictions of fi re-induced forest loss in China.
基金supported financially by the National Key Research and Development Plan(2018YFD0600205)the National Natural Science Foundation of China(31971669)。
文摘Underground fires are characterized by smouldering combustion with a slow rate of spread rate and without flames.Although smouldering combustion releases large amounts of gaseous pollutants,it is difficult to discover by today's forest fire monitoring technologies.Carbon monoxide(CO),nitrogen oxides(NO_(x))and sulfur dioxide(SO_(2))were identified as high concentration marker gases of smouldering combustion-easily-be monitored.According to a two-way ANOVA,combustion time had a significant impact on CO and NO_(x) emissions;smoldering-depth also had a significant impact on NO_(x) emissions but not on CO emissions.Gas emission equations were established by multiple linear regression,C_(co)=156.989-16.626 t and C_(NOx)=3.637-0.252 t-0.039 h.
基金supported financially by the National Key Research and Development Plan(2018YFD0600205)China’s National Foundation of Natural Sciences(31470497)the Project of Jilin Province Department of Education(JJKH20180347KJ)
文摘Forest fires are influenced by several factors,including forest location,species type,age and density,date of fire occurrence,temperatures,and wind speeds,among others.This study investigates the quantitative effects of these factors on the degree of forest fire disaster using nonparametric statistical methods to provide a theoretical basis and data support for forest fire management.Data on forest fire damage from 1969 to 2013 was analyzed.The results indicate that different forest locations and types,fire occurrence dates,temperatures,and wind speeds were statistically significant.The eastern regions of the study area experienced the highest fire occurrence,accounting for 85.0%of the total number of fires as well as the largest average forested area burned.April,May,and October had more frequent fires than other months,accounting for 78.9%,while September had the most extensive forested area burned(63.08 ha)and burnt area(106.34 ha).Hardwood mixed forest and oak forest had more frequent fires,accounting for 31.9%and 26.0%,respectively.Hardwood-conifer mixed forest had the most forested area burned(50.18 ha)and burnt area(65.09 ha).Temperatures,wind speeds,and their interaction had significant impacts on forested area burned and area burnt.
基金financially supported by the National Natural Science Foundation of China (31971669)the Postgraduate Innovation Project of Beihua University (2021-013)
文摘Underground fires are a smoldering combustion with a slow spread rate, low temperatures and no flame. They can last from days to several months, and can even become overwintering fires. They are difficult to find, leading to considerable damage to the forests. The moisture content of combustible fuels is an important factor in the occurrence and persistence of underground forest fires. The Daxing’an Mountains are a hot spot for underground fires in China. This paper looks at the influence of different moisture contents on underground fire characteristics using simulation combustion experiments in the laboratory. The study showed that peak temperature and spread rate fluctuation of humus at different moisture levels increased with humus depth. Peak temperature and spread rate fluctuation of humus at different depths decreased with increased moisture;moisture content and depth of humus had a significant effect on peak temperature and spread rate fluctuation;peak temperature at different depths decreased with increased moisture;the spread rate in upper layers increased with moisture content, while the spread rate in the lower layers decreased with increased moisture content.
基金funded by the National Natural Science Foundation of China(Grant No.31971669)。
文摘Underground fires are slow spreading,long-lasting and low temperature smoldering combustion without flames,mainly occurring in peatlands and wetlands with rich organic matter.The spread of the smoldering is maintained by heat released during combustion and monitoring this is an important approach to detect underground fires.The Daxing'an Mountains region is a hotspot for underground fires in northeast China.This study examined a L arix gmelinii plantation in the Tatou wetlands of the Daxing'an Mountains and determined the maximum temperature variation of humus of varying particle sizes,and the temperature rising process based on non-linear mixed effects models by an indoor combustion experiment.Maximum combustion temperatures up to 897.5°C,increased with humus depth;among the three models tested,Richard's equations were best for characterizing temperature variations;a non-linear equation with three parameters had the highest accuracy in fitting the combustion temperature variations with varying humus particle sizes.These results are informative for predicting temperature variations and provide technical support for underground fire monitoring.
