scholarly journals Fire Hazard in Chattogram City Corporation Area: A Critical Analysis of Its Causes and Mitigation Measures

2021 ◽  
Vol 3 ◽  
Author(s):  
Muhammad Rashidul Hasan ◽  
Md. Rakibul Hasan Kauser ◽  
Jihan Ibrahim
Keyword(s):  
Geographical Information Systems ◽  
Fire Hazard ◽  
Geographical Information ◽  
Mitigation Measures ◽  
Primary Data ◽  
Fire Intensity ◽  
Short Period ◽  
Fire Stations ◽  
Fire Accidents ◽  
Over Time

Fire can have its origin either in natural or human activities resulting in death and/or property damage in a very short period of time. To develop fire hazard-resilient cities proper attention should be given to all possible sections of development to facilitate the service. Chattogram City is the second largest city of Bangladesh. Due to rapid rate of urbanization and unplanned growth of urban centers; hazards like fire have become a menace for the Chattogram City Corporation (CCC) area. So, the main objective of this research is to identify the nature of the fire hazard by analyzing frequency and intensity over time through different checklists and analyzing the existing firefighting capacity. In addition to past fire incident records, a direct questionnaire survey was utilized and expert opinion was solicited for primary data collection. Using geographical information systems (GIS) techniques, this study found that nine fire stations in the CCC area exhibited different frequency and intensity in different categories such as type of structure, land use, source of fire, damage, and losses in last 5 years. The number of fire incidents increased from 200 to 675 which indicates that the frequency increased over time. Among 2,514 fire accidents, 47% occurred in residential areas and 27% occurred in commercial areas. Fire intensity also varied with seasonal variation over a year. Within the last 5 years, the Chattogram City Corporation dealt with a 179,091,200 BDT financial loss and 83 people were injured, of which 15 were due to fire accidents. One the other hand, only nine fire stations serve the ~155 sq.km area and ~6 million people live in the CCC area which is 17 and 19 times larger than that of Bangkok and Oklahoma City. Finally, this data-driven approach and findings could help emergency planners to take necessary steps for improving firefighting capability to ensure better fire safety and resiliency.

scholarly journals Rationale and design of the violence, injury and trauma observatory (VITO): the Cape Town VITO pilot studies protocol

BMJ Open ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. e016485 ◽  
Author(s):  
Ardil Jabar ◽  
Tolu Oni ◽  
Mark E Engel ◽  
Nemanja Cvetkovic ◽  
Richard Matzopoulos
Keyword(s):  
Violence Prevention ◽  
Geographical Information Systems ◽  
Cape Town ◽  
Integrated System ◽  
Geographical Information ◽  
Local Context ◽  
Pilot Studies ◽  
Targeted Interventions ◽  
Clinical Databases ◽  
Short Period

The establishment of violence and injury observatories elsewhere has been found to reduce the burden within a relatively short period. Currently no integrated system exists in South Africa to provide collated data on violence, to allow for targeted interventions and routine monitoring and evaluation.This research seeks to identify if bringing multiple data sources, including but not limited to data from the South African Police Service (SAPS), Forensic Pathology Services (FPS), Emergency Medical Services (EMS) and local hospital clinical databases, together are (1) feasible; (2) able to generate data for action, that is valid, reliable and robust and (3) able to lead to interventions.The violence, injury and trauma observatory (VITO) is a planned collaborative, multicentre study of clinical, police and forensic data for violence and injury in the City of Cape Town, where a local context exists of access to multiple source of health and non-health data. The VITO will initially be piloted in Khayelitsha, a periurban community characterised by increased rates of violence, where fatal and non-fatal injury data will be sourced from within the community for the period 2012–2015 and subjected to descriptive statistics and time-trend analyses. Analysed data will be visualised using story maps, data clocks, web maps and other geographical information systems-related products.This study has been approved by the University of Cape Town’s Human Research Ethics Committee (HREC 861/2016). We intend to disseminate our findings among stakeholders within the local government safety cluster, non-governmental organisations working within the violence prevention sector and the afflicted communities through the SAPS and violence prevention through urban upgrading community forums. Findings from this work will serve to identify important issues and trends, influence public policy and develop evidence-based interventions.

scholarly journals Hospital-Based Back Surgery: Geospatial-Temporal, Explanatory, and Predictive Models

10.2196/14609 ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. e14609 ◽  
Author(s):  
Lawrence Fulton ◽  
Clemens Scott Kruse
Keyword(s):  
Time Series ◽  
Random Forests ◽  
Geographical Information Systems ◽  
The United States ◽  
Practice Variation ◽  
Geographical Information ◽  
Federal State ◽  
Test Set ◽  
Back Surgery ◽  
Over Time

Background Hospital-based back surgery in the United States increased by 60% from January 2012 to December 2017, yet the supply of neurosurgeons remained relatively constant. During this time, adult obesity grew by 5%. Objective This study aimed to evaluate the demand and associated costs for hospital-based back surgery by geolocation over time to evaluate provider practice variation. The study then leveraged hierarchical time series to generate tight demand forecasts on an unobserved test set. Finally, explanatory financial, technical, workload, geographical, and temporal factors as well as state-level obesity rates were investigated as predictors for the demand for hospital-based back surgery. Methods Hospital data from January 2012 to December 2017 were used to generate geospatial-temporal maps and a video of the Current Procedural Terminology codes beginning with the digit 63 claims. Hierarchical time series modeling provided forecasts for each state, the census regions, and the nation for an unobserved test set and then again for the out-years of 2018 and 2019. Stepwise regression, lasso regression, ridge regression, elastic net, and gradient-boosted random forests were built on a training set and evaluated on a test set to evaluate variables important to explaining the demand for hospital-based back surgery. Results Widespread, unexplained practice variation over time was seen using geographical information systems (GIS) multimedia mapping. Hierarchical time series provided accurate forecasts on a blind dataset and suggested a 6.52% (from 497,325 procedures in 2017 to 529,777 in 2018) growth of hospital-based back surgery in 2018 (529,777 and up to 13.00% by 2019 [from 497,325 procedures in 2017 to 563,023 procedures in 2019]). The increase in payments by 2019 are estimated to be US $323.9 million. Extreme gradient-boosted random forests beat constrained and unconstrained regression models on a 20% unobserved test set and suggested that obesity is one of the most important factors in explaining the increase in demand for hospital-based back surgery. Conclusions Practice variation and obesity are factors to consider when estimating demand for hospital-based back surgery. Federal, state, and local planners should evaluate demand-side and supply-side interventions for this emerging problem.

scholarly journals Hospital-Based Back Surgery: Geospatial-Temporal, Explanatory, and Predictive Models (Preprint)

2019 ◽  
Author(s):  
Lawrence Fulton ◽  
Clemens Scott Kruse
Keyword(s):  
Time Series ◽  
Random Forests ◽  
Geographical Information Systems ◽  
The United States ◽  
Practice Variation ◽  
Geographical Information ◽  
Federal State ◽  
Test Set ◽  
Back Surgery ◽  
Over Time

BACKGROUND Hospital-based back surgery in the United States increased by 60% from January 2012 to December 2017, yet the supply of neurosurgeons remained relatively constant. During this time, adult obesity grew by 5%. OBJECTIVE This study aimed to evaluate the demand and associated costs for hospital-based back surgery by geolocation over time to evaluate provider practice variation. The study then leveraged hierarchical time series to generate tight demand forecasts on an unobserved test set. Finally, explanatory financial, technical, workload, geographical, and temporal factors as well as state-level obesity rates were investigated as predictors for the demand for hospital-based back surgery. METHODS Hospital data from January 2012 to December 2017 were used to generate geospatial-temporal maps and a video of the Current Procedural Terminology codes beginning with the digit 63 claims. Hierarchical time series modeling provided forecasts for each state, the census regions, and the nation for an unobserved test set and then again for the out-years of 2018 and 2019. Stepwise regression, lasso regression, ridge regression, elastic net, and gradient-boosted random forests were built on a training set and evaluated on a test set to evaluate variables important to explaining the demand for hospital-based back surgery. RESULTS Widespread, unexplained practice variation over time was seen using geographical information systems (GIS) multimedia mapping. Hierarchical time series provided accurate forecasts on a blind dataset and suggested a 6.52% (from 497,325 procedures in 2017 to 529,777 in 2018) growth of hospital-based back surgery in 2018 (529,777 and up to 13.00% by 2019 [from 497,325 procedures in 2017 to 563,023 procedures in 2019]). The increase in payments by 2019 are estimated to be US $323.9 million. Extreme gradient-boosted random forests beat constrained and unconstrained regression models on a 20% unobserved test set and suggested that obesity is one of the most important factors in explaining the increase in demand for hospital-based back surgery. CONCLUSIONS Practice variation and obesity are factors to consider when estimating demand for hospital-based back surgery. Federal, state, and local planners should evaluate demand-side and supply-side interventions for this emerging problem.

Collaborating to Create Healthier Communities

2016 ◽  
Vol 37 (2) ◽  
pp. 129-133
Author(s):  
Amanda W. Scarbrough ◽  
Jack Hill ◽  
Jesus Rodriguez
Keyword(s):  
Geographical Information Systems ◽  
Well Being ◽  
Geographical Information ◽  
Montgomery County ◽  
United Way ◽  
Sam Houston State University ◽  
Short Period ◽  
The Creation ◽  
High Concentrations ◽  
Being There

The Montgomery County United Way and Sam Houston State University explored existing public health and community-based issues and associated assets and gaps within Montgomery County, Texas, through the integration of quantitative geospatial data, demographic information, and the application of geographical information systems. The intent of the initial results was to use maps to visually compare the magnitude of significant emerging health issues in Montgomery County with other counties across Texas in an effort to better educate and increase the awareness of the general public within Montgomery County. The second objective was to present an example of the visual effect and impact of the overall spatial analysis and mapping process with a focus on a specific community issue that could likely be addressed and potentially solved in a relatively short amount of time. This second and more spatially detailed aspect of the evaluation resulted in the creation of an asset map that presented high concentrations or densities of payday loan services in Montgomery County. Recognizing the potential risks of payday loans, Montgomery County United Way presented the asset maps to the effected community leaders. Upon review, leaders discovered there were dense clusters of payday loan sites in areas with high rates of poverty. Prior to the creation of this aggregated payday loan business location map, an individual in a community typically only saw one, or two at the most, payday loan business during a daily commute. Within a very short period and through a grassroots effort to improve community well-being, there were significant formal and positive changes made by the community.

Mapping wildland fuels for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling

2001 ◽  
Vol 10 (4) ◽  
pp. 301 ◽  
Author(s):  
Robert E. Keane ◽  
Robert Burgan ◽  
Jan van Wagtendonk
Keyword(s):  
Remote Sensing ◽  
Geographical Information Systems ◽  
Fire Management ◽  
Multiple Scales ◽  
Fire Hazard ◽  
Fire Behavior ◽  
Mapping Method ◽  
Geographical Information ◽  
Biophysical Modeling ◽  
Fuel Mapping

This paper was presented at the conference ‘Integrating spatial technologies and ecological principles for a new age in fire management’, Boise, Idaho, USA, June 1999 Fuel maps are essential for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, fuel mapping is an extremely difficult and complex process requiring expertise in remotely sensed image classification, fire behavior, fuels modeling, ecology, and geographical information systems (GIS). This paper first presents the challenges of mapping fuels: canopy concealment, fuelbed complexity, fuel type diversity, fuel variability, and fuel model generalization. Then, four approaches to mapping fuels are discussed with examples provided from the literature: (1) field reconnaissance; (2) direct mapping methods; (3) indirect mapping methods; and (4) gradient modeling. A fuel mapping method is proposed that uses current remote sensing and image processing technology. Future fuel mapping needs are also discussed which include better field data and fuel models, accurate GIS reference layers, improved satellite imagery, and comprehensive ecosystem models.

scholarly journals The impact of aging on laboratory fire behaviour in masticated shrub fuelbeds of California and Oregon, USA

2016 ◽  
Vol 25 (9) ◽  
pp. 1002 ◽  
Author(s):  
Jesse K. Kreye ◽  
J. Morgan Varner ◽  
Jeffrey M. Kane ◽  
Eric E. Knapp ◽  
Warren P. Reed
Keyword(s):  
Tree Mortality ◽  
Management Practice ◽  
Fire Hazard ◽  
Woody Debris ◽  
Fuel Load ◽  
Fire Intensity ◽  
Fire Behaviour ◽  
Slow Combustion ◽  
The Impact ◽  
Over Time

Mastication of shrubs and small trees to reduce fire hazard has become a widespread management practice, yet many aspects of the fire behaviour of these unique woody fuelbeds remain poorly understood. To examine the effects of fuelbed aging on fire behaviour, we conducted laboratory burns with masticated Arctostaphylos spp. and Ceanothus spp. woody debris that ranged from 2 to 16 years since treatment. Masticated fuels that were 10 years or older burned with 18 to 29% shorter flame heights and 19% lower fireline intensities compared with the younger fuelbeds across three different fuel loads (25, 50 and 75 Mg ha–1). Older fuelbeds smouldered for almost 50% longer than the younger masticated fuelbeds. Fuel consumption was 96% in the two higher fuel load categories regardless of fuelbed age, whereas consumption was 77% in the lighter fuel load. Fire intensity in masticated fuels may decrease over time owing to particle degradation, but in dry environments where decomposition is slow, combustion of the remaining fuels may still pose risks for tree mortality and smoke production associated with protracted smouldering.

scholarly journals Forest Fire Risk Assessment Using Hotspot Analysis in GIS

2017 ◽  
Vol 11 (1) ◽  
pp. 786-801 ◽  
Author(s):  
Safwanah Ni’matullah Binti Mohd Said ◽  
El-Said Mamdouh Mahmoud Zahran ◽  
Shahriar Shams
Keyword(s):  
Forest Fire ◽  
Geographical Information Systems ◽  
Fire Risk ◽  
Geographical Information ◽  
Asian Countries ◽  
Hotspot Analysis ◽  
Brunei Darussalam ◽  
Fire Stations ◽  
Forest Fire Risk

Background: Present intensifying forest fire incidents are becoming a major concern as they pose threats to the environment, economy and human’s safety. This paper aims to identify forest fire hotspots using advanced hotspot analysis in the Geographical Information Systems (GIS), and suggest appropriate preventive measures. Objective: Brunei Darussalam is one of the Southeast Asian countries that is significantly affected by the increase in forest fire incidents in this region. Brunei Muara is the worst-hit district by forest fire in Brunei Darussalam, and hence it was selected as a case study for this research. Results and Conclusion: This research identified and prioritized forest fire hotspots, highlighted the shortage of fire stations within the identified hotspots and suggested the suitable locations for new fire stations in Brunei Muara district.

scholarly journals Pemanfaatan Sistem Informasi Geografis untuk Pemetaan Penyakit Periodontal Berdasarkan Faktor Lingkungan di Kecamatan Pundong, Kabupaten Bantul

2019 ◽  
Vol 18 (2) ◽  
pp. 98
Author(s):  
Prayudha Benni Setiawan ◽  
Bekti Nur'aini ◽  
Hartono Hartono ◽  
Regina Titi Christinawati Tandelilin
Keyword(s):  
Spatial Analysis ◽  
Environmental Factors ◽  
Periodontal Disease ◽  
Geographical Information Systems ◽  
Poisson Model ◽  
Geographical Information ◽  
Primary Data ◽  
P Value ◽  
Cross Sectional ◽  
Water Acidity

ABSTRAK Latar belakang: Penyakit periodontal merupakan salah satu penyakit gigi dan mulut yang banyak di jumpai di masyarakat dunia khususnya di Indonesia. Penyebab utama penyakit periodontal adalah faktor lokal yaitu bakteri plak dan kalkulus. Selain itu faktor geografis, lingkungan secara tidak langsung dapat mempengaruhi individu mengalami penyakit periodontal. Sistem Informasi Geografis (SIG) dapat digunakan untuk menganalisa perbedaan faktor-faktor tersebut, terutama yang berhubungan dengan perbedaan geografis dan lingkungan. Kecamatan Pundong memiliki variasi letak geografis dan lingkungan.Metode: Jenis penelitian ini adalah observasional analitik survei dengan disain cross-sectional. Subjek penelitian ditetapkan dengan pendekatan Regristry Based Study dimana Puskesmas Pundong sebagai sumber data dasar dalam penelitian ini. Variabel bebas adalah penyakit periodontal, sedangkan variable terikat adalah ketinggian tempat (geografis) dan pH air (lingkungan). Analisis spasial menggunakan Purely Spatial Poisson Model SatScan  dan ArcGIS. Distribusi frekuensi dan hubungan faktor lingkungan dengan penyakit periodontal dianalisis menggunakan univariat dan bivariate. Hasil: Variabel yang berhubungan secara signifikan dengan keparahan penyakit periodontal yaitu pH sumber air dan ketinggian tempat (p-value<0,05). Berdasarkan nalisis Purely Spatial Poisson Model didapatkan satu cluster, terjadi pada 49 penderita dengan radius 2.24 km terdapat di Desa Seloharjo. Memiliki annual cases 11.2/100000 penduduk, yang berarti dalam 100000 penduduk memiliki 11.2 mengalami kasus penyakit periodontal.Simpulan: Terdapat hubungan yang signifikan keparahan penyakit periodontal dengan pH sumber air dan ketinggian tempat. Berdasarkan analisis spasial terdapat klaster kejadian periodontal di Desa Seloharjo.   ABSTRACT Title: Using  Geographic Information System for Periodontal Disease Mapping  Based on Environmental Aspects in Pundong District, Bantul RegencyBackground: Periodontal disease is one of the most common oral diseases in the world, especially in Indonesia. The main causes of periodontal disease are local factors such as dental plaques and calculus. In addition, environmental factors can indirectly affect individuals experiencing periodontal disease. Geographical Information Systems (GIS) can be used to analyze differences in these factors, especially those related to geographical and environmental differences. Pundong district has geographical and socio-economic variation.Method: The type of study was an observational analytic survey with a cross-sectional design. The subject of research is determined by Registry Based Study approach where Pundong Community Health Center as the primary data source in this research. Independent variable is periodontal disease, while the dependent variable is a  altitude and water acidity. Spatial analysis using Purely Spatial Poisson SatScan and ArcGIS. The distribution and relationship of environmental factors with periodontal disease were analyzed using univariate and bivariateResult: The variables significantly associated with periodontal disease severity were altitude and water acidity(p-value <0.05). Spatial analysis to determine the cluster of incidence of periodontal disease, with Purely Spatial Poisson Model analysis obtained 1 cluster, occurred in 49 patients with radius 2.24 km in Seloharjo. It has annual cases of 11.2 / 100000 residents, which means that in 100000 the population has 11.2 cases of people. Conclusion: There is a significant relationship between the severity of periodontal disease and the water acidity and altitude. Based on the spatial analysis there were cluster periodontal events in Seloharjo 

Mapping the Way of St. James

2021 ◽  
Vol 101 (1) ◽  
pp. 3-32
Author(s):  
Sean T. Perrone ◽  
Carol Traynor
Keyword(s):  
Geographical Information Systems ◽  
Academic Research ◽  
Geographical Information ◽  
Santiago De Compostela ◽  
Spatial History ◽  
The Past ◽  
Mapping Technology ◽  
Research Questions ◽  
New Research ◽  
Over Time

Abstract Every year, more historians and scholars in related humanities disciplines are using Geographical Information Systems (GIS) and mapping technology in their research. The field of spatial history/spatial humanities is growing. Yet, many scholars are still unaware of the potential of using mapping technology to interpret the past and further their academic research. Mapping helps us to see the movement of people and ideas over time and thereby raises new research questions. This article seeks to introduce readers to the field of spatial history and to illustrate the potential of GIS by examining the medieval pilgrimage to Santiago de Compostela. In particular, the article uses spatial analysis to add further evidence that Aimeric Picaud, the author of the twelfth-century Pilgrim’s Guide to Santiago de Compostela, likely did not make the trip as described in his text.

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