scholarly journals Hotspot Analysis of Structure Fires in Urban Agglomeration: A Case of Nagpur City, India

Fire ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 38
Author(s):  
Priya P. Singh ◽  
Chandra S. Sabnani ◽  
Vijay S. Kapse
Keyword(s):  
Population Density ◽  
Fire Risk ◽  
Temporal Analysis ◽  
Fire Service ◽  
Sustainable Urban Development ◽  
Hotspot Analysis ◽  
Peak Period ◽  
Civic Service ◽  
Risk Zones ◽  
Resilient Infrastructure

Fire Service is the fundamental civic service to protect citizens from irrecoverable, heavy losses of lives and property. Hotspot analysis of structure fires is essential to estimate people and property at risk. Hotspot analysis for the peak period of last decade, using a GIS-based spatial analyst and statistical techniques through the Kernel Density Estimation (KDE) and Getis-Ord Gi* with Inverse Distance Weighted (IDW) interpolation is performed, revealing fire risk zones at the city ward micro level. Using remote sensing, outputs of hotspot analysis are integrated with the built environment of Land Use Land Cover (LULC) to quantify the accurate built-up areas and population density of identified fire risk zones. KDE delineates 34 wards as hotspots, while Getis-Ord Gi* delineates 17 wards within the KDE hotspot, the central core areas having the highest built-up and population density. A temporal analysis reveals the maximum fires on Thursday during the hot afternoon hours from 12 noon to 5 p.m. The study outputs help decision makers for effective fire prevention and protection by deploying immediate resource allocations and proactive planning reassuring sustainable urban development. Furthermore, updating the requirement of the National Disaster Management Authority (NDMA) to build urban resilient infrastructure in accord with the Smart City Mission.

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 COVID-19 Risk Assessment: Contributing to Maintaining Urban Public Health Security and Achieving Sustainable Urban Development

2021 ◽  
Vol 13 (8) ◽  
pp. 4208
Author(s):  
Jun Zhang ◽  
Xiaodie Yuan
Keyword(s):  
Public Health ◽  
Population Density ◽  
Prevention And Control ◽  
Floating Population ◽  
Sustainable Urban Development ◽  
Risk Level ◽  
Health Security ◽  
Main Factors ◽  
And Control ◽  
Epidemic Risk

As the most infectious disease in 2020, COVID-19 is an enormous shock to urban public health security and to urban sustainable development. Although the epidemic in China has been brought into control at present, the prevention and control of it is still the top priority of maintaining public health security. Therefore, the accurate assessment of epidemic risk is of great importance to the prevention and control even to overcoming of COVID-19. Using the fused data obtained from fusing multi-source big data such as POI (Point of Interest) data and Tencent-Yichuxing data, this study assesses and analyzes the epidemic risk and main factors that affect the distribution of COVID-19 on the basis of combining with logistic regression model and geodetector model. What’s more, the following main conclusions are obtained: the high-risk areas of the epidemic are mainly concentrated in the areas with relatively dense permanent population and floating population, which means that the permanent population and floating population are the main factors affecting the risk level of the epidemic. In other words, the reasonable control of population density is greatly conducive to reducing the risk level of the epidemic. Therefore, the control of regional population density remains the key to epidemic prevention and control, and home isolation is also the best means of prevention and control. The precise assessment and analysis of the epidemic conducts by this study is of great significance to maintain urban public health security and achieve the sustainable urban development.

scholarly journals Fire risk assessment, spatiotemporal clustering and hotspot analysis in the Luki biosphere reserve region, Western DR Congo

2021 ◽  
pp. 100104
Author(s):  
Nadège CIREZI CIZUNGU ◽  
Elvis TSHIBASU ◽  
Eric LUTETE ◽  
Arsene MUSHAGALUSA ◽  
Yannick MUGUMAARHAHAMA ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Biosphere Reserve ◽  
Fire Risk ◽  
Dr Congo ◽  
Hotspot Analysis ◽  
Fire Risk Assessment ◽  
Spatiotemporal Clustering

What drives forest fire in Fujian, China? Evidence from logistic regression and Random Forests

2016 ◽  
Vol 25 (5) ◽  
pp. 505 ◽  
Author(s):  
Futao Guo ◽  
Guangyu Wang ◽  
Zhangwen Su ◽  
Huiling Liang ◽  
Wenhui Wang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Random Forest ◽  
Regional Scale ◽  
Fire Risk ◽  
Driving Factors ◽  
Fire Season ◽  
Fire Occurrence ◽  
Climate Factors ◽  
Local Factors ◽  
Risk Zones

We applied logistic regression and Random Forest to evaluate drivers of fire occurrence on a provincial scale. Potential driving factors were divided into two groups according to scale of influence: ‘climate factors’, which operate on a regional scale, and ‘local factors’, which includes infrastructure, vegetation, topographic and socioeconomic data. The groups of factors were analysed separately and then significant factors from both groups were analysed together. Both models identified significant driving factors, which were ranked in terms of relative importance. Results show that climate factors are the main drivers of fire occurrence in the forests of Fujian, China. Particularly, sunshine hours, relative humidity (fire seasonal and daily), precipitation (fire season) and temperature (fire seasonal and daily) were seen to play a crucial role in fire ignition. Of the local factors, elevation, distance to railway and per capita GDP were found to be most significant. Random Forest demonstrated a higher predictive ability than logistic regression across all groups of factors (climate, local, and climate and local combined). Maps of the likelihood of fire occurrence in Fujian illustrate that the high fire-risk zones are distributed across administrative divisions; consequently, fire management strategies should be devised based on fire-risk zones, rather than on separate administrative divisions.

scholarly journals Land Surface Heterogeneity Signature in Tornado Climatology? An Illustrative Analysis over Indiana, 1950–2012*

2014 ◽  
Vol 18 (10) ◽  
pp. 1-32 ◽  
Author(s):  
Olivia Kellner ◽  
Dev Niyogi
Keyword(s):  
Land Use ◽  
Population Density ◽  
Land Cover ◽  
Land Surface ◽  
Strong Relationship ◽  
Surface Heterogeneity ◽  
Temporal Analysis ◽  
Antecedent Rainfall ◽  
Land Surface Heterogeneity ◽  
Tornado Climatology

Abstract Land surface heterogeneity affects mesoscale interactions, including the evolution of severe convection. However, its contribution to tornadogenesis is not well known. Indiana is selected as an example to present an assessment of documented tornadoes and land surface heterogeneity to better understand the spatial distribution of tornadoes. This assessment is developed using a GIS framework taking data from 1950 to 2012 and investigates the following topics: temporal analysis, effect of ENSO, antecedent rainfall linkages, population density, land use/land cover, and topography, placing them in the context of land surface heterogeneity. Spatial analysis of tornado touchdown locations reveals several spatial relationships with regard to cities, population density, land-use classification, and topography. A total of 61% of F0–F5 tornadoes and 43% of F0–F5 tornadoes in Indiana have touched down within 1 km of urban land use and land area classified as forest, respectively, suggesting the possible role of land-use surface roughness on tornado occurrences. The correlation of tornado touchdown points to population density suggests a moderate to strong relationship. A temporal analysis of tornado days shows favored time of day, months, seasons, and active tornado years. Tornado days for 1950–2012 are compared to antecedent rainfall and ENSO phases, which both show no discernible relationship with the average number of annual tornado days. Analysis of tornado touchdowns and topography does not indicate any strong relationship between tornado touchdowns and elevation. Results suggest a possible signature of land surface heterogeneity—particularly that around urban and forested land cover—in tornado climatology.

scholarly journals Forest fire risk mapping using analytical hierarchy process (AHP) and earth observation datasets: a case study in the mountainous terrain of Northeast India

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Ridalin Lamat ◽  
Mukesh Kumar ◽  
Arnab Kundu ◽  
Deepak Lal
Keyword(s):  
High Risk ◽  
Forest Fire ◽  
Analytical Hierarchy Process ◽  
Fire Risk ◽  
Control Measures ◽  
Fire Control ◽  
Risk Zones ◽  
Hierarchy Process ◽  
Forest Fire Risk ◽  
Very High

AbstractThis study presents a geospatial approach in conjunction with a multi-criteria decision-making (MCDM) tool for mapping forest fire risk zones in the district of Ri-Bhoi, Meghalaya, India which is very rich in biodiversity. Analytical hierarchy process (AHP)-based pair-wise comparison matrix was constructed to compare the selected parameters against each other based on their impact/influence (equal, moderate, strong, very strong, and extremely strong) on a forest fire. The final output delineated fire risk zones in the study area in four categories that include very high-risk, high-risk, moderate-risk, and low-risk zones. The delineated fire risk zones were found to be in close agreement with actual fire points obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) fire data for the study area. Results indicated that Ri-Bhoi’s 804.31 sq. km. (32.86%) the area was under ‘very high’ fire susceptibility. This was followed by 583.10 sq. km. (23.82%), 670.47 sq. km. (27.39%), and 390.12 sq. km. (15.93%) the area under high, moderate, and low fire risk categories, respectively. These results can be used effectively to plan fire control measures in advance and the methodology suggested in this study can be adopted in other areas too for delineating potential fire risk zones.

scholarly journals Cartographie Des Zones À Risque D’incendies De Forêts À L'aide Du SIG Et La Télédétection Dans L'arrière-Pays Du Port Tanger Med

2017 ◽  
Vol 13 (32) ◽  
pp. 205 ◽  
Author(s):  
Abderrahim Maktite ◽  
Ali Faleh
Keyword(s):  
Remote Sensing ◽  
Population Density ◽  
Fire Risk ◽  
Weather Conditions ◽  
Natural Environments ◽  
Strong Wind ◽  
High Population Density ◽  
Risk Map ◽  
Gis And Remote Sensing ◽  
Considerable Degradation

Moroccan natural environments, in recent decades, have undergone considerable degradation which is related primarily to the development of populations and the pressure they have exerted on natural resources. One aspect of this degradation is forest fire that has accelerated alarmingly. The study area belongs to the forest area of Tangier which covers an area of 42.000ha. The latter is known for its sensitivity to heat, especially because of the nature of the vegetation cover, weather conditions (frequent and strong wind), and high population density. The present work aims to prioritize the plot study area according to the degree of fire risk of forests using the model established by Dagorne Y. Duche in 1994. To achieve this goal, the application of GIS and Remote Sensing is required to develop a fire risk map in the hinterland of Tangier Mediterranean port.

scholarly journals Comparative analyses on epidemiological characteristics of dengue fever in Guangdong and Yunnan, China, 2004-2018

2020 ◽  
Author(s):  
Yujuan Yue ◽  
Qiyong Liu ◽  
Xiaobo Liu ◽  
Haixia Wu
Keyword(s):  
Dengue Fever ◽  
Mainland China ◽  
Temporal Analysis ◽  
Prevention Measures ◽  
Pearl River Delta Region ◽  
Peak Period ◽  
Guangzhou City ◽  
Male Predominance ◽  
Imported Cases ◽  
Epidemiological Characteristics

Abstract Background Guangdong and Yunnan were the two provinces with the toughest dengue epidemic in China. It was to compare epidemiological characteristics of dengue fever there, 2004-2018. Methods Epidemiological method and spatial-temporal analysis were used to explore time-series, spatial and demographic features of dengue fever.Results 93.7% of indigenous cases and 65.9 % of imported cases in mainland China, 2004-2018 occurred in Guangdong and Yunnan. 55,970 and 5,938 indigenous cases occurred in 108 counties of Guangdong and 8 counties of Yunnan, respectively. 1,146 and 3,050 imported cases occurred in 84 counties of Guangdong and 72 counties of Yunnan, respectively. Guangdong and Yunnan had similar seasonal characteristics for dengue fever, and Guangdong had a longer peak period. 85.1% of indigenous cases in Yunnan were located in Ruili City and Jinghong City along the southwestern border. Most dengue cases in Guangdong occurred in the Pearl River Delta region, and especially more than 70.0% of dengue cases in Guangdong occurred in Guangzhou City. 93.9% of imported cases in Guangdong and Yunnan were imported from 9 countries of Southeast Asia. Thailand, Cambodia and Malaysia were the main imported origins in Guangdong. Myanmar and Laos were the main imported origins in Yunnan. There was a strong male predominance among imported cases and an almost equal gender distribution among indigenous cases. Most dengue cases were from individuals in 21-50 years old, accounting for 57.3% and 62.8% of indigenous cases and 83.2% and 62.6% of imported cases in Guangdong and Yunnan, respectively. There were similar major occupations as housework or unemployment, retiree and businessman for indigenous cases, and businessman for imported cases. However, farmers accounted for a larger proportion of dengue cases in Yunnan.Conclusions The findings of epidemiological characteristics and differences of dengue fever in Guangdong and Yunnan are helpful to formulate targeted, strategic plans and implement effective public health prevention measures in China.

scholarly journals Reduction of territorial fire risks based on methods of active systems theory

2018 ◽  
Vol 251 ◽  
pp. 06010
Author(s):  
Vladimir Minaev ◽  
Alexander Faddeev ◽  
Tuan Dao ◽  
Phan Tuan Anh
Keyword(s):  
Human Resources ◽  
Systems Theory ◽  
Construction Industry ◽  
Human Resources Management ◽  
Target Function ◽  
Fire Risk ◽  
Fire Service ◽  
Risk Indicators ◽  
Active Systems ◽  
Risks Assessment

Subject of the study: Models of relationships between specific index for the number of deaths and injuries in fires and specific load by fires are studied. A complex specific indicator (the number of deaths and injuries in fires) is formed. Thereupon, based on the principles of active systems theory, a target function for optimal territorial distribution of human resources of fire service in clusters – groups of homogeneous provinces in terms of fire risks – is constructed. Goal of the study: The article is aimed at justifying and constructing complex criteria for optimal management of the human resources of the fire service. Materials and methods: Methodological basis for fire risks assessment is the integral fire risks theory, and human resources management is the theory of active systems. The dynamics of fire risk indicators in Vietnam from 2006 to 2016 is considered. Results: The optimal distribution of human resources allows a 10-12% reduction in the complex specific indicator of risks. Conclusions: The obtained solutions make it possible to develop practical recommendations for authorities, industries, including construction industry, and fire service, on improving management of territorial human resources taking into account fire risks, enhancing legal and regulatory support for insurance in construction industry.

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