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Record W4385387804 · doi:10.18280/ijsse.130306

Evaluating and Improving the Spatial Distribution Using GIS to Avoid Environmental Risks and Achieve Safety for Petrol Stations in the Nile District Center in Mahaweel / Iraq

2023· article· en· W4385387804 on OpenAlexvenueno aff
Baydaa Abdul Hussein Bedewy, Marwan H. Abdulameer

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
Fundersnot available
KeywordsGeographic information systemCenter (category theory)Transport engineeringEnvironmental safetyEnvironmental scienceEnvironmental planningEnvironmental healthGeographyEngineeringRemote sensingMedicine

Abstract

fetched live from OpenAlex

The main objectives of this research are to analyze the spatial distribution of petroleum stations in the Nile City/Al-Mahaweel District using multi-criteria analysis based on Geographic Information Systems (ArcGIS 10.8).The study aims to provide a clear picture of station distribution and spatial variations, explain the underlying reasons for this distribution for each station, and assess the spatial compatibility with planning standards and site requirements.The research also aims to enhance safety and security by optimizing station locations and mitigating potential risks.However, a research problem indicates that the distribution of stations in the Nile City/Al-Mahaweel District needs to adhere to planning standards.Stations are primarily located outside the city center, resulting in a need for more service provision for residents and visitors.This distribution poses environmental risks and compromises spatial safety.The research hypothesis suggests that adopting sustainable and analytical planning standards can enhance station efficiency, achieve optimal distribution, ensure spatial safety, and mitigate risks.The study was conducted in the Nile City/Al-Mahaweel District, where three fuel stations are located outside the municipal boundaries, with no stations within the district.Various assessments were made concerning fuel stations, including detailed maps of the actual conditions, hypothetical geographic maps, standard distance distribution maps, directional distribution maps, allocation area maps, and petroleum stations in the city.By comparing the current status of petroleum refueling stations with the standards and site requirements, a multi-criteria spatial analysis was conducted using seven essential criteria: minimum distance between the station and service facilities, residential areas, population density, community services, road networks, accessibility distance, and distance from power lines.Key findings of the research indicate that station distribution in the study area adheres to the established standards, criteria, and regulations set by relevant official bodies concerning safety and security.However, some fuel stations only partially comply with all criteria, while others exceed certain parameters.Proposed locations for fuel stations (Station A with an area of 5000 m² and Station B with an area of 4500 m² ) were determined based on planning standards to enhance the spatial distribution efficiency of stations and improve service provision to meet demand.Particularly, the Nile City/Al-Mahaweel District, which lacks fuel stations, relies on stations outside the municipal boundaries due to administrative divisions from the main district, resulting in insufficient station distribution that caters to the population's needs.The multi-criteria approach proves highly effective in determining the optimal number and location of petroleum stations within the city and district.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.295
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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