The devastating effects of wildland fire are an unsolved problem,resulting in human losses and the destruction of natural and economic resources.Convolutional neural network(CNN)is shown to perform very well in the ar...The devastating effects of wildland fire are an unsolved problem,resulting in human losses and the destruction of natural and economic resources.Convolutional neural network(CNN)is shown to perform very well in the area of object classification.This network has the ability to perform feature extraction and classification within the same architecture.In this paper,we propose a CNN for identifying fire in videos.A deep domain based method for video fire detection is proposed to extract a powerful feature representation of fire.Testing on real video sequences,the proposed approach achieves better classification performance as some of relevant conventional video based fire detection methods and indicates that using CNN to detect fire in videos is efficient.To balance the efficiency and accuracy,the model is fine-tuned considering the nature of the target problem and fire data.Experimental results on benchmark fire datasets reveal the effectiveness of the proposed framework and validate its suitability for fire detection in closed-circuit television surveillance systems compared to state-of-the-art methods.展开更多
Over the last two decades wildfire activity, damage, and management cost within the US have increased substantially. These increases have been associated with a number of factors including climate change and fuel accu...Over the last two decades wildfire activity, damage, and management cost within the US have increased substantially. These increases have been associated with a number of factors including climate change and fuel accumulation due to a century of active fire suppression. The increased fire activity has occurred during a time of significant ex-urban development of the Wildland Urban Interface （WUI） along with increased demand on water resources originating on forested landscapes. These increased demands have put substantial pressure on federal agencies charged with wildfire management to continue and expand the century old policy of aggressive wildfire suppression. However, aggressive wildfire suppression is one of the major factors that drive the increased extent, intensity, and damage associated with the small number of large wildfires that are unable to be suppressed. In this paper we discuss the positive feedback loops that lead to demands for increasing suppression response while simultaneously increasing wildfire risk in the future. Despite a wealth of scientific research that demonstrates the limitations of the current management paradigm pressure to maintain the existing system are well entrenched and driven by the existing social systems that have evolved under our current management practice. Interestingly, US federal wildland fire policy provides considerable discretion for managers to pursue a range of management objectives however, societal expectations and existing management incentive structures result in policy implementation that is straining the resilience of fire adapted ecosystems and the communities that reside in and adjacent to them.展开更多
As human populations become concentrated in larger,more intensely urbanized areas connected through glob-alization,the relationships of cities to their surrounding landscapes are open to social,ecological,and economic...As human populations become concentrated in larger,more intensely urbanized areas connected through glob-alization,the relationships of cities to their surrounding landscapes are open to social,ecological,and economic reinterpretation.In particular,the value of access to nature in the form of nearby undeveloped wildland to ur-ban populations implies a relatively novel type of synergistic city-region relationship.We develop a robust and replicable metric-the urban-wildland juxtaposition(UWJ)-that quantifies critical dimensions of the juxtapo-sition of the urbanicity of cities with the quantity of nearby unbuilt wildlands,based on the spatial proximity and relative intensities of these two contrasting system types.Using a distance-decay gravity model,this analysis provides documentation on the calculation of the UWJ and its component metrics,urbanicity(U)and wildland(W)and then presents U,W,and UWJ metrics for 36 urbanized areas representing all regions of the U.S.,pro-viding the basis for comparisons and analysis.We explore the potential of the metric by testing correlations with“creative class”employment and public health measures.The UWJ has implications and potential applications for demographic,economic,social,and quality-of-life trends across the U.S.and internationally.展开更多
基金National Natural Science Foundation of China(No.61573095)Natural Science Foundation of Shanghai,China(No.6ZR1446700)
文摘The devastating effects of wildland fire are an unsolved problem,resulting in human losses and the destruction of natural and economic resources.Convolutional neural network(CNN)is shown to perform very well in the area of object classification.This network has the ability to perform feature extraction and classification within the same architecture.In this paper,we propose a CNN for identifying fire in videos.A deep domain based method for video fire detection is proposed to extract a powerful feature representation of fire.Testing on real video sequences,the proposed approach achieves better classification performance as some of relevant conventional video based fire detection methods and indicates that using CNN to detect fire in videos is efficient.To balance the efficiency and accuracy,the model is fine-tuned considering the nature of the target problem and fire data.Experimental results on benchmark fire datasets reveal the effectiveness of the proposed framework and validate its suitability for fire detection in closed-circuit television surveillance systems compared to state-of-the-art methods.
文摘Over the last two decades wildfire activity, damage, and management cost within the US have increased substantially. These increases have been associated with a number of factors including climate change and fuel accumulation due to a century of active fire suppression. The increased fire activity has occurred during a time of significant ex-urban development of the Wildland Urban Interface （WUI） along with increased demand on water resources originating on forested landscapes. These increased demands have put substantial pressure on federal agencies charged with wildfire management to continue and expand the century old policy of aggressive wildfire suppression. However, aggressive wildfire suppression is one of the major factors that drive the increased extent, intensity, and damage associated with the small number of large wildfires that are unable to be suppressed. In this paper we discuss the positive feedback loops that lead to demands for increasing suppression response while simultaneously increasing wildfire risk in the future. Despite a wealth of scientific research that demonstrates the limitations of the current management paradigm pressure to maintain the existing system are well entrenched and driven by the existing social systems that have evolved under our current management practice. Interestingly, US federal wildland fire policy provides considerable discretion for managers to pursue a range of management objectives however, societal expectations and existing management incentive structures result in policy implementation that is straining the resilience of fire adapted ecosystems and the communities that reside in and adjacent to them.
文摘As human populations become concentrated in larger,more intensely urbanized areas connected through glob-alization,the relationships of cities to their surrounding landscapes are open to social,ecological,and economic reinterpretation.In particular,the value of access to nature in the form of nearby undeveloped wildland to ur-ban populations implies a relatively novel type of synergistic city-region relationship.We develop a robust and replicable metric-the urban-wildland juxtaposition(UWJ)-that quantifies critical dimensions of the juxtapo-sition of the urbanicity of cities with the quantity of nearby unbuilt wildlands,based on the spatial proximity and relative intensities of these two contrasting system types.Using a distance-decay gravity model,this analysis provides documentation on the calculation of the UWJ and its component metrics,urbanicity(U)and wildland(W)and then presents U,W,and UWJ metrics for 36 urbanized areas representing all regions of the U.S.,pro-viding the basis for comparisons and analysis.We explore the potential of the metric by testing correlations with“creative class”employment and public health measures.The UWJ has implications and potential applications for demographic,economic,social,and quality-of-life trends across the U.S.and internationally.
