scholarly journals Spatial distribution of grassland fires at the regional scale based on the MODIS active fire products

2017 ◽  
Vol 26 (3) ◽  
pp. 209 ◽  
Author(s):  
Zhengxiang Zhang ◽  
Zhiqiang Feng ◽  
Hongyan Zhang ◽  
Jianjun Zhao ◽  
Shan Yu ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Regional Scale ◽  
Kernel Density ◽  
Fire Risk ◽  
Fire Prevention ◽  
Distance Method ◽  
Fire Risk Analysis ◽  
Active Fire ◽  
The Mean ◽  
Grassland Fire

Grassland fires are major disturbances to ecosystems and economies around the world. Therefore, research on the spatial patterns of grassland fires is important for understanding the dynamics of fire occurrence and providing evidence for fire prevention and management. One of the problems in grassland fire risk analysis is that historically observed fire data are generally in the point format, with imprecise positions, whereas other influencing factors are often expressed in continuous areal units. To minimise the influences of inaccurate locations and grid size, density estimates can be produced using kernel density estimation (KDE) – a nonparametric statistical method for estimating probability densities. This method has been widely used to convert historical fire data into continuous surfaces. In this study, KDE was applied to grassland fire events in the eastern Inner Mongolia of China, based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua daily active fire data from 2001 to 2014. The bandwidth choice was based on the mean random distance method. Annual and seasonal kernel density maps were produced, showing that the spatial patterns of grassland fire events remained temporally consistent. These results were used to create grassland fire risk zones on the basis of the mean density values in the study area. Grassland fire prevention and planning may focus on high-risk areas identified using this method.

scholarly journals Fire Temperature Based on the Time and Resistance of Buildings—Predicting the Adoption of Fire Safety Measures

Fire ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 19 ◽  
Author(s):  
Luciano Santarpia ◽  
Simone Bologna ◽  
Virgilio Ciancio ◽  
Iacopo Golasi ◽  
Ferdinando Salata
Keyword(s):  
Heat Flux ◽  
Fire Risk ◽  
Fire Prevention ◽  
Time Interval ◽  
Fire Load ◽  
Safety Measures ◽  
Fire Temperature ◽  
Fire Risk Analysis ◽  
Opening Factor

During a fire in enclosed spaces, having structures with a good level of resistance is very important. The post flashover fire time interval, during which rescue squads operate, is important to verify if the structure can still resist fire for an acceptable time interval. This can be determined through the REI value. Hence, the way the fire develops must be examined together with the trend of the temperature that might guarantee that the structure will resist the heat flux released during the combustion. This article examines and compares, through a case study, the most important methods for analysis of the fire risk: the prescriptive approach and the simplified performance-based approach. The performance-based method (more suitable for the actual planning demand with respect to the more cautious prescriptive approach) is affected by the parameters influencing its development. The goal of this article is to provide a graph (based on parameters like the type of building, opening factor “O” and fire load “q”) that might be used by designers and architects to carry out the planning phase and adopt fire prevention systems before dealing with the assessments required by the engineering field for the fire risk analysis.

Dynamic Spatial-Distributed Fire Risk Analysis

2020 ◽  
pp. 101-120
Author(s):  
Maryna Vitalievna Zharikova
Keyword(s):  
Real Time ◽  
Forest Fire ◽  
Object Representation ◽  
Fire Risk ◽  
Distributed Model ◽  
Fire Risk Analysis ◽  
Active Fire ◽  
Three Stages ◽  
Time Systems ◽  
Forest Fire Risk

The chapter develops a dynamic spatial-distributed model of forest fire risk. The structure of forest fire risk is represented by two interrelated groups of components describing a potential of forest fire and describing valuable objects being under fire influence. The concept of fire risk which contains the probability of forest fire occurrence, its intensity, and effect, is extended using the threat as the additional prognostic spatial-temporal component that has a predictive property and allows forecasting the possibility of losses at any time. The model of fire risk is based on three stages: potential risk, the source of which is described by fire danger; risk of threat of active forest fire which hasn't covered valuable object yet; risk of destruction when the active fire has covered valuable object. Representation of risk as a process based on three stages allows describing the dynamics of risk in real-time systems, getting insight into risk nature, as well as diagnosing the situation in real time.

scholarly journals Fire Risk Analysis and Optimization of Fire Prevention Management for Green Building Design and High Rise Buildings: Hong Kong Experience

2014 ◽  
Vol 3 (1) ◽  
pp. 41-54 ◽  
Author(s):  
Albert Yau ◽  
Samuel K. M. Ho
Keyword(s):  
Hong Kong ◽  
Fire Safety ◽  
Green Building ◽  
Fire Risk ◽  
Building Design ◽  
Fire Prevention ◽  
Green Building Design ◽  
Fire Risk Analysis ◽  
High Rise ◽  
Fire Prevention Management

Abstract There are many iconic high rise buildings in Hong Kong, for example, International Commercial Centre, International Financial Centre, etc. Fire safety issue in high rise buildings has been raised by local fire professionals in terms of occupant evacuation, means of fire-fighting by fire fighters, sprinkler systems to automatically put off fires in buildings, etc. Fire risk becomes an important issue in building fire safety because it relates to life safety of building occupants where they live and work in high rise buildings in Hong Kong. The aim of this research is to identify the fire risk for different types of high rise buildings in Hong Kong and to optimise the fire prevention management for those high rise buildings with higher level of fire risk and to validate the model and also to carry out the study of the conflict between the current fire safety building code and the current trend of green building design. Survey via the 7-point scale questionnaire was conducted through 50 participants and their responses were received and analysed via the statistical tool SPSS software computer program. A number of statistical methods of testing for significantly difference in samples were adopted to carry out the analysis of the data received. When the statistical analysis was completed, the results of the data analysis were validated by two Fire Safety Experts in this area of specialisation and also by quantitative fire risk analysis.

Fire Risk Analysis Using Geospatial Approach and Mitigation Measures for South-West Delhi

2018 ◽  
Vol 6 (8) ◽  
pp. 131
Author(s):  
S. K. Tomar ◽  
A. Kaur ◽  
H. K. Dangi ◽  
T. Ghawana ◽  
K. Sarma
Keyword(s):  
Risk Analysis ◽  
Fire Risk ◽  
Population Data ◽  
Fire Service ◽  
Capital City ◽  
Mitigation Measures ◽  
Fire Risk Analysis ◽  
South West ◽  
Geospatial Tools ◽  
Fire Stations

One of the major challenge from unplanned growth in the cities is the fire incidents posing a serious threat to life and property. Delhi, the capital city of India, has seen unplanned growth of colonies resulting in a serious concern for the relevant agencies. This paper investigates the relation between potential causes of fire incidents during 2013-2016 in South-West Delhi Division of Delhi Fire Services as part of risk analysis using the data about fire stations & their jurisdictions, incidents of fire, water reservoirs available, landuse and population data along with the divisional & sub-divisional boundaries of South-West Delhi division under Delhi Fire Service. Statistical and Geospatial tools have been used together to perform the risk analysis. The analysis reveals that difference in actual occupancy and defined landuse as a part of unplanned growth of settlements is found to be the main reason behind the major fire incidents. The suggested mitigation measures focus on legal, policy, physical & technological aspects and highlight the need to bring the systemic changes with changing scenario of demographics and infrastructure to accommodate more aspects of ground reality.

scholarly journals Identifying the density of grassland fire points with kernel density estimation based on spatial distribution characteristics

2021 ◽  
Vol 13 (1) ◽  
pp. 796-806
Author(s):  
Zhen Shuo ◽  
Zhang Jingyu ◽  
Zhang Zhengxiang ◽  
Zhao Jianjun
Keyword(s):  
Spatial Distribution ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Function Method ◽  
Kernel Density ◽  
Fire Occurrence ◽  
Distribution Characteristics ◽  
Fire Point ◽  
Spatial Distribution Characteristics ◽  
Grassland Fire

Abstract Understanding the risk of grassland fire occurrence associated with historical fire point events is critical for implementing effective management of grasslands. This may require a model to convert the fire point records into continuous spatial distribution data. Kernel density estimation (KDE) can be used to represent the spatial distribution of grassland fire occurrences and decrease the influences historical records in point format with inaccurate positions. The bandwidth is the most important parameter because it dominates the amount of variation in the estimation of KDE. In this study, the spatial distribution characteristic of the points was considered to determine the bandwidth of KDE with the Ripley’s K function method. With high, medium, and low concentration scenes of grassland fire points, kernel density surfaces were produced by using the kernel function with four bandwidth parameter selection methods. For acquiring the best maps, the estimated density surfaces were compared by mean integrated squared error methods. The results show that Ripley’s K function method is the best bandwidth selection method for mapping and analyzing the risk of grassland fire occurrence with the dependent or inaccurate point variable, considering the spatial distribution characteristics.

scholarly journals Clustering of Maxima: Spatial Dependencies among Heavy Rainfall in France

2013 ◽  
Vol 26 (20) ◽  
pp. 7929-7937 ◽  
Author(s):  
Elsa Bernard ◽  
Philippe Naveau ◽  
Mathieu Vrac ◽  
Olivier Mestre
Keyword(s):  
Spatial Patterns ◽  
Extreme Value Theory ◽  
Heavy Rainfall ◽  
Spatial Clustering ◽  
Relevant Information ◽  
Value Theory ◽  
Research Field ◽  
Multivariate Extreme Value Theory ◽  
Spatial Dependencies ◽  
The Mean

Abstract One of the main objectives of statistical climatology is to extract relevant information hidden in complex spatial–temporal climatological datasets. To identify spatial patterns, most well-known statistical techniques are based on the concept of intra- and intercluster variances (like the k-means algorithm or EOFs). As analyzing quantitative extremes like heavy rainfall has become more and more prevalent for climatologists and hydrologists during these last decades, finding spatial patterns with methods based on deviations from the mean (i.e., variances) may not be the most appropriate strategy in this context of studying such extremes. For practitioners, simple and fast clustering tools tailored for extremes have been lacking. A possible avenue to bridging this methodological gap resides in taking advantage of multivariate extreme value theory, a well-developed research field in probability, and to adapt it to the context of spatial clustering. In this paper, a novel algorithm based on this plan is proposed and studied. The approach is compared and discussed with respect to the classical k-means algorithm throughout the analysis of weekly maxima of hourly precipitation recorded in France (fall season, 92 stations, 1993–2011).

scholarly journals City Fire Risk Analysis based on Coupling Fault Tree Method and Triangle Fuzzy Theory

2014 ◽  
Vol 84 ◽  
pp. 204-212 ◽  
Author(s):  
Wu Aiyou ◽  
Shi Shiliang ◽  
Li Runqiu ◽  
Tang Deming ◽  
Tang Xiafang
Keyword(s):  
Risk Analysis ◽  
Fuzzy Theory ◽  
Fault Tree ◽  
Fire Risk ◽  
Fire Risk Analysis ◽  
Coupling Fault ◽  
Tree Method

scholarly journals Transmetric Density Estimation

2016 ◽  
Vol 5 (2) ◽  
pp. 35
Author(s):  
Sigve Hovda
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Convergence Order ◽  
Graphical Display ◽  
Mean Integrated Squared Error ◽  
Squared Error ◽  
Integrated Squared Error ◽  
The Mean ◽  
Convergence Orders

<div>A transmetric is a generalization of a metric that is tailored to properties needed in kernel density estimation.  Using transmetrics in kernel density estimation is an intuitive way to make assumptions on the kernel of the distribution to improve convergence orders and to reduce the number of dimensions in the graphical display.  This framework is required for discussing the estimators that are suggested by Hovda (2014).</div><div> </div><div>Asymptotic arguments for the bias and the mean integrated squared error is difficult in the general case, but some results are given when the transmetric is of the type defined in Hovda (2014).  An important contribution of this paper is that the convergence order can be as high as $4/5$, regardless of the number of dimensions.</div>

scholarly journals Real Scale Fire Test for the Karaoke Fire Risk Analysis

2012 ◽  
Vol 12 (6) ◽  
pp. 1-6 ◽  
Author(s):  
Yong Ho Yoo ◽  
Young Hwa Choi ◽  
Oh Sang Kweon
Keyword(s):  
Risk Analysis ◽  
Fire Test ◽  
Fire Risk ◽  
Fire Risk Analysis ◽  
Real Scale
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