Exposure Assessment of PM2.5 Using Spatial Analysis Model in Mexico City

Epidemiology ◽  
2008 ◽  
Vol 19 (1) ◽  
pp. S218-S219
Author(s):  
J L Texcalac ◽  
A Barraza ◽  
L Hernandez ◽  
C Escamilla ◽  
M Jerrett ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Exposure Assessment ◽  
Mexico City ◽  
Analysis Model

scholarly journals Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area

2017 ◽  
Vol 14 (7) ◽  
pp. 734 ◽  
Author(s):  
Alejandro Aguirre-Salado ◽  
Humberto Vaquera-Huerta ◽  
Carlos Aguirre-Salado ◽  
Silvia Reyes-Mora ◽  
Ana Olvera-Cervantes ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Mexico City ◽  
Metropolitan Area ◽  
Hierarchical Model

Investigating the Potential of Urban Land Uses to Support Sustainable Energy Principles Using a Spatial Analysis Model

2015 ◽  
Author(s):  
Sherika Gibson
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Urban Areas ◽  
Sustainable Energy ◽  
Global Scale ◽  
Economic Security ◽  
Sustainable Communities ◽  
Renewable Energy Resources ◽  
Analysis Model ◽  
Essential Components

The underpinning elements of sustainable communities are centered on economic security, renewable energy resources, reliable infrastructure, and ecological protection. The geomorphology of urban areas is altered due to human activity leading to change in land use characteristics and resources availability. Research has shown that global population has increased drastically over the last three decades resulting in depleted efficiency of regional resources. Because of this, obtaining sustainable energy platforms is a world-wide concern. In evaluating the ability of urban communities to support sustainable elements, both spatial and temporal influences must be considered. As a result a spatial analysis model will be used to assess the geomorphological and land use aspects of urban watersheds to support sustainable communities’ platform. These data will provide insight in essential components in need of environmental restoration that contribute to future renewable resources which can then be applied on a global scale.

Geocoding Tweets Approach Based on Conceptual Representations in the Context of the Knowledge Society

2016 ◽  
Vol 12 (1) ◽  
pp. 44-61 ◽  
Author(s):  
Imelda Escamilla ◽  
Miguel Torres-Ruiz ◽  
Marco Moreno-Ibarra ◽  
Rolando Quintero ◽  
Giovanni Guzmán ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Mexico City ◽  
Spatial Patterns ◽  
Knowledge Society ◽  
Spatial Relationships ◽  
Visualization Method ◽  
Urban Context ◽  
Conceptual Representations ◽  
The Core ◽  
Application Ontology

In this paper, an approach to geocode tweets published in Spanish is proposed. The tweets are related to traffic events within an urban context of the Mexico City. They are generated by a particular phenomenon for knowing the behavior of the involved geographic entities. In order to disambiguate and verify the consistency of information, an application ontology was defined. Thus, the core goal is to identify location as well as spatial relationships between entities presented in the events, using semantic and spatial analysis of the collected dataset. In consequence, a visualization method for presenting the results was also proposed. The paper describes the methodology for enabling the discovery of spatial patterns within traffic tweets and provides useful information to make timely decisions and contribute in the context of Knowledge Society.

scholarly journals An exploratory factor analysis model for slum severity index in Mexico City

Urban Studies ◽  
2019 ◽  
Vol 57 (4) ◽  
pp. 789-805 ◽  
Author(s):  
Debraj Roy ◽  
David Bernal ◽  
Michael Lees
Keyword(s):  
Factor Analysis ◽  
International Development ◽  
Mexico City ◽  
Exploratory Factor Analysis ◽  
Urban Areas ◽  
Informal Settlements ◽  
Severity Index ◽  
Development Planning ◽  
Analysis Model ◽  
Factor Analysis Model

Today, over half of the world’s population lives in urban areas and it is projected that, by 2050, two out of three people will live in a city. This increased rural–urban migration, coupled with housing poverty, has led to the growth and formation of informal settlements, commonly known as slums. In Mexico, 25% of the urban population now live in informal settlements with varying degrees of deprivation. Although some informal neighbourhoods have contributed to the upward mobility of the inhabitants, the majority still lack basic services. Mexico City and the conurbation around it form a mega city of 21million people that has been growing in a manner qualified as ‘highly unproductive, (that) deepens inequality, raises pollution levels’ (available at:   https://www.smartcitiesdive.com/ex/sustainablecitiescollective/making-way-urban-reform-mexico/176466/ ) and contains the largest slum in the world: Neza-Chalco-Izta. Urban reforms are now aiming to improve the conditions in these slums and therefore it is very important to have reliable tools to measure the changes that are underway. In this paper, we use exploratory factor analysis to define an index of shelter deprivation in Mexico City, namely the Slum Severity Index (SSI), based on the UN-HABITAT’s definition of slum. We apply this novel approach to the Census survey of Mexico and measure the shelter deprivation levels of households from 1990 to 2010. The analysis highlights high variability in housing conditions within Mexico City. We find that the SSI decreased significantly between 1990 and 2000 as a result of several policy reforms but increased between 2000 and 2010. We also show correlations of the SSI with other social factors such as education, health and fertility. We present a validation of the SSI using Grey Level Co-occurrence Matrix (GLCM) features extracted from Very-High Resolution (VHR) remote-sensed satellite images. Finally, we show that the SSI can present a cardinally meaningful assessment of the extent of deprivation compared with a similar index defined by Connolly (Connolly P (2009) Observing the evolution of irregular settlements: Mexico city’s colonias populares, 1990 to 2005. International Development Planning Review 31: 1–35) that studies shelter deprivation in Mexico.

scholarly journals Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)

2018 ◽  
Vol 149 ◽  
pp. 02081
Author(s):  
RFIFI Mohamed ◽  
AIT BRAHIM Lahsen
Keyword(s):  
Spatial Analysis ◽  
Local Scale ◽  
Landslide Risk ◽  
Risk Map ◽  
Analysis Model ◽  
Analysis Techniques ◽  
Probabilistic Mapping ◽  
Three Stages ◽  
Urban Project ◽  
Al Hoceima

The present study is consecrated to the probabilistic mapping of the landslide risk at the local scale of an area that belongs to Al Hoceima city in the western Rif of Morocco. The study focuses mainly on the spatial analysis of multi sources data by using an environment GIS (Geographic Information Systems), and the application of the bivariate probabilistic model to qualify the risk susceptibility. The employed methodology is based on three stages. First, the evaluation of landslide susceptibility (S) by the analysis model cited before. Second, the identification and the estimation of the potential consequences (C) for the existing issues. Finally, the landslide risk (R) is evaluated by combining the susceptibility and the potential consequences map. This study requires the use of spatial analysis techniques. It also refers to the risk maps scale, generally reduced and being inappropriate at the urban project area. The obtained risk map defines four risk intensities with a spatial resolution of two meters.

scholarly journals Where you Live Matters: A Spatial Analysis of COVID-19 Mortality

2021 ◽  
Author(s):  
Behzad Javaheri
Keyword(s):  
Spatial Analysis ◽  
Mexico City ◽  
Spatial Relationship ◽  
Disease Process ◽  
State Level ◽  
Health Conditions ◽  
Choropleth Mapping ◽  
Age Related ◽  
Level Data ◽  
Mortality Ratio

The COVID-19 pandemic has caused ~ 2 million fatalities. Significant progress has been made in advancing our understanding of the disease process, one of the unanswered questions, however, is the anomaly in the case/mortality ratio with Mexico as a clear example. Herein, this anomaly is explored by spatial analysis and whether mortality varies locally according to local factors. To address this, hexagonal cartogram maps (hexbin) used to spatially map COVID-19 mortality and visualise association with patient-level data on demographics and pre-existing health conditions. This was further interrogated at local Mexico City level by choropleth mapping. Our data show that the use of hexagonal cartograms is a better approach for spatial mapping of COVID-19 data in Mexico as it addresses bias in area size and population. We report sex/age-related spatial relationship with mortality amongst the Mexican states and a trend between health conditions and mortality at the state level. Within Mexico City, there is a clear south, north divide with higher mortality in the northern municipalities. Deceased patients in these northern municipalities have the highest pre-existing health conditions. Taken together, this study provides an improved presentation of COVID-19 mapping in Mexico and demonstrates spatial divergence of the mortality in Mexico.

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