Spatial-temporal analysis of urban environmental quality of Tehran, Iran

Javanbakht, Mohammad; Boloorani, Ali Darvishi; Kiavarz, Majid; Samany, Najmeh Neisany; Zebardast, Lobat; Zangiabadi, Mahdieh

doi:10.1016/j.ecolind.2020.106901

Cited by 21 publications

(10 citation statements)

References 66 publications

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“…Then all the criteria maps are obtained using spatial analysis and normalized based on Eq. 1 ( Neysani Samany et al, 2014 , Boloorani et al, 2021 , Naghdizadegan Jahromi et al, 2021 , Javanbakht et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

The most places at risk surrounding the COVID-19 treatment hospitals in an urban environment- case study: Tehran city

et al. 2021

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Investigations on the spatial patterns of COVID-19 spreading indicate the possibility of the virus transmission by moving infected people in an urban area. Hospitals are the most susceptible locations due to the COVID-19 contaminations in metropolises. This paper aims to find the riskiest places surrounding the hospitals using an MLP-ANN. The main contribution is discovering the influence zone of COVID-19 treatment hospitals and the main spatial factors around them that increase the prevalence of COVID-19. The innovation of this paper is to find the most relevant spatial factors regarding the distance from central hospitals modeling the risk level of the study area. Therefore, eight hospitals with two service areas for each of them are computed with [0-500] and [500-1000] meters distance. Besides, five spatial factors have been considered, consist of the location of patients’ financial transactions, the distance of streets from hospitals, the distance of highways from hospitals, the distance of the non-residential land use from the hospitals, and the hospital patient number. The implementation results revealed a meaningful relation between the distance from the hospitals and patient density. The RMSE and R measures are 0.00734 and 0.94635 for [0-500 m] while these quantities are 0.054088 and 0.902725 for [500-1000 m] respectively. These values indicate the role of distance to central hospitals for COVID-19 treatment. Moreover, a sensitivity analysis demonstrated that the number of patients’ transactions and the distance of the non-residential land use from the hospitals are two dominant factors for virus propagation. The results help urban managers to begin preventative strategies to decrease the community incidence rate in high-risk places.

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Section: Methodsmentioning

confidence: 99%

The most places at risk surrounding the COVID-19 treatment hospitals in an urban environment- case study: Tehran city

et al. 2021

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“…It is challenging to model and predict the interaction of diverse factors because these variables have different units. Recently, remotely sensed imagery is an effective data source for modeling urban environmental quality (UEQ) because the imagery can provide continuous Earth observation images of the urban environment at different spatial, spectral, and temporal resolutions (Du et al, 2014;Javanbakht et al, 2021). Assessing the UEQ is an effective tool in urban planning and management since it provides more specific information about urban conditions, it may also be a powerful tool for informing the public about the quality of the environment in which they live.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Urban Environmental Quality: A Case Study of Casablanca, Morocco

Malah

Bahi

Radoine

et al. 2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. By 2050, Most of the world’s population will live in cities, this demographic explosion will lead to significant urban development at the expanse of natural land which may harm the environmental quality. Consequently, assessing and modeling the urban environmental quality (UEQ) is requisite for efficient urban sprawl control and better city planning and management. The present study proposes a methodology to model and assess the environment of the urban system by developing the urban environmental quality index (UEQI) based on remote sensing data. Five environmental indicators were derived from the Landsat OLI image namely, Modified Normalized Difference Impervious Surface Index (MNDISI), Modified Normalized Difference, Water Index (MNDWI), Normalized difference vegetation Index (NDVI), Normalized difference built-up Index (NDBI) and Soil adjusted vegetation index (SAVI). Using the Principal Component Analysis (PCA) the urban environmental quality index was computed for the 17 communes of Casablanca city. The UEQI values were spatially mapped under three classes (good, moderate, and poor). The results obtained from the analysis showed a significant difference in the term of UEQI values among the communes. In addition, the environmental quality is inadequate in communes with fewer green spaces and more impervious surfaces. The outcomes of this work can serve as an efficient tool to determine the most critical interventions to be made by the authority for current and future urban planning and land/resource management.

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“…Moreover, data fusion visualisation of hazardous chemical disaster scenarios and disaster analysis results can provide more information for emergency rescue decision-making. The GIS technology can efficiently visualise multi-source spatio-temporal data and has been widely used in urban construction and planning, meteorology and hydrology, natural ecological environment, and other fields (Widener et al 2017, Othman et al 2020, Javanbakht et al 2021. Therefore, we posit that it is necessary to leverage GIS technology to investigate the spatio-temporal dynamic derivation of hazardous chemical leakage disasters.…”

Section: Introductionmentioning

confidence: 99%

Construction and spatio-temporal derivation of hazardous chemical leakage disaster chain

Zheng

Wang

Zheng

et al. 2021

International Journal of Image and Data Fusion

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Hazardous chemicals are indispensable substances for the development of modern industries. However, improper storage, transportation, or handling of hazardous chemicals can cause chain disasters such as leakage and explosion, seriously threatening the safety of people's lives, society, economy, and natural environment. In this study, we analysed the occurrence and evolution process of various disaster events caused by hazardous chemical leakage based on the disaster system theory, and constructed a hazardous chemical leakage disaster chain from the aspects of disastercausing factors, disaster-pregnant environment, hazard-affected bodies, and post-disaster losses. Taking a methane leakage accident as a case study, we conducted numerical simulation and spatiotemporal dynamic derivation on the hazardous chemical leakage disaster chain in a three-dimensional (3-D) geographic scene. This study can provide support on handling hazardous chemical leakage disasters and assist informed decision-making, including monitoring, pre-warning, disaster forecast and prevention, emergency preparedness, and post-disaster response, further improving the efficiency of emergency response and urban safety management.

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Spatial-temporal analysis of urban environmental quality of Tehran, Iran

Cited by 21 publications

References 66 publications

The most places at risk surrounding the COVID-19 treatment hospitals in an urban environment- case study: Tehran city

The most places at risk surrounding the COVID-19 treatment hospitals in an urban environment- case study: Tehran city

Assessment of Urban Environmental Quality: A Case Study of Casablanca, Morocco

Construction and spatio-temporal derivation of hazardous chemical leakage disaster chain

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