scholarly journals Spatiotemporal analysis of bubonic plague in Pernambuco, northeast of Brazil: Case study in the municipality of Exu

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249464
Author(s):  
Diego Leandro Reis da Silva Fernandes ◽  
Elainne Christine de Souza Gomes ◽  
Matheus Filgueira Bezerra ◽  
Ricardo José de Paula Souza e Guimarães ◽  
Alzira Maria Paiva de Almeida
Keyword(s):  
Spatial Data ◽  
Statistical Significance ◽  
Control Program ◽  
Spatiotemporal Analysis ◽  
Northeastern Brazil ◽  
Spatial Data Analysis ◽  
Maximum Entropy Modeling ◽  
Software Packages ◽  
Study Case

Along with other countries in America, plague reached Brazil through the sea routes during the third pandemic. A brief ports phase was followed by an urban phase that took place in smaller inland cities and finally, it attained the rural area and established several foci where the ecological conditions were suitable for its continued existence. However, the geographic dispersion of plague in Brazil is still poorly studied. To better understand the disease dynamics, we accessed satellite-based data to trace the spatial occurrence and distribution of human plague cases in Pernambuco, Northeastern Brazil and using the municipality of Exu as study case area. Along with the satellite data, a historical survey using the Plague Control Program files was applied to characterize the spatial and temporal dispersion of cases in the period of 1945–1976. Kernel density estimation, spatial and temporal clusters with statistical significance and maximum entropy modeling were used for spatial data analysis, by means of the spatial analysis software packages. The use of geostatistical tools allowed evidencing the shift of the infection from the urban to the wild-sylvatic areas and the reemergence of cases after a period of quiescence, independent of the reintroduction from other plague areas.

Assessing Spatial Equity: An Evaluation of Measures of Accessibility to Public Playgrounds

1998 ◽  
Vol 30 (4) ◽  
pp. 595-613 ◽  
Author(s):  
E Talen ◽  
L Anselin
Keyword(s):  
Spatial Data ◽  
Empirical Studies ◽  
Spatial Association ◽  
Spatial Data Analysis ◽  
Socioeconomic Indicators ◽  
Model Average ◽  
Urban Service ◽  
Spatial Equity ◽  
Analytical Perspective

Geographical and political research on urban service delivery—who benefits and why—has proliferated during the past two decades. Overall, this literature is not characterized by a particular attention to the importance of method in drawing conclusions about spatial equity based on empirical studies. Specifically, there has been scant interest in the effect of geographic methodology on assessing the relationship between access and socioeconomic characteristics that are spatially defined. In this paper we take a spatial analytical perspective to evaluate the importance of methodology in assessing whether or not, or to what degree the distribution of urban public services is equitable. We approach this issue by means of an empirical case study of the spatial distribution of playgrounds in Tulsa, Oklahoma, relative to that of the targeted constituencies (children) and other socioeconomic indicators. In addition to the ‘traditional’ measure (count of facilities in an areal unit), we consider a potential measure (based on the gravity model), average travel distance, and distance to the nearest playground as indicators of accessibility. We find significant differences between the spatial patterns in these measures that are suggested by local indicators of spatial association and other techniques of exploratory spatial data analysis. The choice of access measure not only implies a particular treatment of spatial externalities but also affects conclusions about the existence of spatial mismatch and inequity.

Landslide Susceptibility Models Utilising Spatial Data Analysis Techniques. A Case Study from the Lower Deba Valley, Guipuzcoa (Spain)

2003 ◽  
Vol 30 (3) ◽  
pp. 267-279 ◽  
Author(s):  
Juan Remondo ◽  
Alberto González-Díez ◽  
José Ramón Díaz De Terán ◽  
Antonio Cendrero
Keyword(s):  
Data Analysis ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Spatial Data Analysis ◽  
Analysis Techniques

scholarly journals Identifying Spatial Relationships between Built Heritage Resources and Short-Term Rentals before the Covid-19 Pandemic: Exploratory Perspectives on Sustainability Issues

2020 ◽  
Vol 12 (11) ◽  
pp. 4533 ◽  
Author(s):  
Irene Rubino ◽  
Cristina Coscia ◽  
Rocco Curto
Keyword(s):  
Spatial Data ◽  
Spatial Data Analysis ◽  
Spatial Relationships ◽  
Short Term ◽  
Historic Center ◽  
Built Heritage ◽  
Socio Economic Variables ◽  
City Relations

Built heritage resources (BHRs) are multidimensional assets that need to be conceived under a sustainability and circular economy framework. Whereas it is essential that their conservation, management, and enjoyment are sustainable, it is also necessary that the environmental, cultural, and socio-economic contexts in which they are integrated are sustainable too. Like other amenities, BHRs can improve the quality of the urban environment and generate externalities; additionally, they may influence sectors such as real estate, hospitality, and tourism. In this framework, this contribution aims to identify spatial relationships occurring between BHRs and short-term rentals (STRs), i.e., a recent economic phenomenon facilitated by platforms such as Airbnb. Through the application of Exploratory Spatial Data Analysis techniques and taking Turin (Italy) as a case study, this article provides evidence that spatial correlation patterns between BHRs and STRs exist, and that the areas most affected by STRs are the residential neighborhoods located in the proximity of the historic center of the city. Relations with other sets of socio-economic variables are highlighted too, and conclusions suggest that future studies are essential not only to monitor sustainability issues and reflect on new housing models and sustainable uses of buildings, but also to understand the evolution of the phenomenon in light of the pandemic Covid-19.

scholarly journals Analysis on spatial distribution pattern of football fields: A case study in Wuhan, China

2021 ◽  
Vol 293 ◽  
pp. 02051
Author(s):  
Yuwei Wang ◽  
Kaicheng Wu ◽  
Wang Gao
Keyword(s):  
Spatial Data ◽  
Global Scale ◽  
Spatial Data Analysis ◽  
Wuhan City ◽  
The Sustainable Development ◽  
Aggregation Pattern ◽  
Per Capita ◽  
Football Field ◽  
Global And Local

In order to promote the sustainable development of sports facilities, the statistical data of football fields in 13 districts of Wuhan city were selected. Based on geographic information system (GIS) and exploratory spatial data analysis (ESDA) technology, this paper analyzed the global and local autocorrelation of the number of football fields per capita in Wuhan city. The results indicate that: (1) Comparing to the new districts in Wuhan, the number of football fields per capita in the central districts was relatively few. (2) In the global scale, the number of football fields per capita in Wuhan presented a spatial aggregation pattern. (3) In the local scale, the regional discrepancy and spatial clusters were confirmed in the local spatial autocorrelation analysis for football fields in Wuhan. At the same time, the research results could provide reasonable references for the planning of football field facilities.

scholarly journals Analisis Penggunaan Lahan Basah Eksisting Berdasarkan Rencana Tata Ruang Wilayah (RTRW) di Kawasan Peri Urban Kota Banda Aceh (Studi Kasus: Kecamatan Darul Imarah Kabupaten Aceh Besar)

2017 ◽  
Vol 2 (4) ◽  
pp. 528-535
Author(s):  
Desra Sahputra ◽  
Muhammad Rusdi ◽  
Sugianto Sugianto
Keyword(s):  
Land Use ◽  
Spatial Data ◽  
Spatial Planning ◽  
Agricultural Land ◽  
Spatial Data Analysis ◽  
Suburban Areas ◽  
Survey Technique ◽  
Descriptive Method ◽  
Banda Aceh

Abstrak. Penyimpangan penggunaan lahan sangat sering terjadi terhadap rencana tata ruang wilayah (RTRW). Daerah pinggiran kota merupakan wilayah yang banyak mengalami perubahan penggunaan lahan terutama perubahan penggunaan lahan pertanian menjadi non pertanian. Adapun tujuan penelitian untuk menganalisis tingkat keselarasan penggunaan lahan basah eksisting di Kecamatan Darul Imarah berdasarkan RTRW. Metode yang digunakan dalam penelitian ini adalah metode deskriptif dengan teknik survai. Sedangkan analisis data spasial menggunakan SIG dengan konsep extract, overlay dan reclassify. Hasil kajian menunjukkan sebesar 583,94 ha (86,68%) sawah eksisting di kawasan kajian telah selaras dengan RTRW dan yang tidak selaras yaitu sebesar 0,15 ha (0,02%). Sementara 89,57 ha (13,3%) sawah eksisting lainnya ditemukan belum selaras dengan RTRW Kabupaten Aceh Besar tahun 2012-2032.The Use of Existing Wetland Analysis Based On Spatial Planning in Peri Urban Area in Banda Aceh (Case study: Darul Imarah Subdistrict Aceh Besar Regency)Abstract. The deviation of land use is very frequent happened to spatial planning. Suburban areas are areas which undergo many changes in land use, especially changes in the use of agricultural land to non-agricultural. The purpose of the research is to analyze the aligned level of the existing wetland use in Darul Imarah sub-district based on spatial planning. The method used in this research was descriptive method with survey technique. While the spatial data analysis was using GIS with extract, overlay and reclassify concept. The result of the study showed that 583.94 ha (86.68%) of the existing fields in the study area were aligned with the RTRW and the non-aligned ones were 0.15 ha (0.02%). Meanwhile, 89.57 ha (13.3%) of other existing rice fields had not been aligned with the spasial planning of Aceh Besar Regency in 2012-2032.

Assessing Spatial Characteristics of Soil Lead Contamination in the Residential Neighborhoods Near the Exide Battery Smelter

2019 ◽  
Vol 3 (1) ◽  
pp. 1-9
Author(s):  
An-Min Wu ◽  
Jill Johnston
Keyword(s):  
Decision Making ◽  
Los Angeles ◽  
Spatial Data ◽  
Hot Spot ◽  
Lead Contamination ◽  
Spatial Data Analysis ◽  
Soil Lead ◽  
Industrial Activities ◽  
Lead Levels

The presence of hazardous chemicals such as lead (Pb) or other heavy metals in the environment poses significant threats to human health. Industrial activities can increase the concentrations of these toxic metals in the soil, water and air where people live, work and play. When exposed to lead, residents face a higher risk of neurological damage, anemia or developmental delays. Urban soil lead levels, for example, are usually higher than the natural background lead levels due to the historical usage of lead paint, leaded gasoline and proximity to industrial activities. We explored a case in southeastern Los Angeles County, where lead contamination in the soil has been a particular concern near a lead-acid battery smelter. In this case study, we investigated soil lead levels across the neighborhoods surrounding the smelter as a mean to support this clean-up decision making. We used a hot spot analysis to identify clusters of high soil lead levels at a neighborhood scale. This case study can be used to teach higher-division undergraduate and graduate students to incorporate spatial thinking and exploratory spatial analysis approaches into the decision-making process for remediation of environmental contamination. Through this case study, the students will develop the knowledge about soil lead contamination and associated health risks, learn how exploratory spatial data analysis can assist examining the distribution of soil lead contamination and discuss potential strategies to improve the environmental remediation process in the urban environment.

scholarly journals Urban Ageing in Europe—Spatiotemporal Analysis of Determinants

2020 ◽  
Vol 9 (7) ◽  
pp. 413 ◽  
Author(s):  
Karolina Lewandowska-Gwarda ◽  
Elżbieta Antczak
Keyword(s):  
Economic Development ◽  
Data Analysis ◽  
Spatial Data ◽  
Urban Areas ◽  
The Elderly ◽  
Spatiotemporal Analysis ◽  
Population Ageing ◽  
Spatial Data Analysis ◽  
Men And Women ◽  
Level Of Economic Development

The aim of this study was to identify determinants of the population ageing process in 270 European cities. We analyzed the proportion of older people: men and women separately (aged 65 or above) in city populations in the years 1990–2018. To understand territorially-varied relationships and to increase the explained variability of phenomena, an explanatory spatial data analysis (ESDA) and geographically weighted regression (GWR) were applied. We used ArcGIS and GeoDa software in this study. In our research, we also took into account the spatial interactions as well as the structure of cities by size and level of economic development. Results of the analysis helped to explain why some urban areas are ageing faster than others. An initial data analysis indicated that the proportion of the elderly in the population was spatially diversified and dependent on gender, as well as the size and economic development of a unit. In general, elderly individuals were more willing to live in larger and highly developed cities; however, women tended to live in large areas and men in medium-sized to large urban areas. Then, we conducted the urban ageing modelling for men and women separately. The application of GWR models enabled not only the specification of the city population ageing determinants, but also the analysis of the variability in the strength and direction of dependencies occurring between the examined variables in individual cities. Significant differences were noted in the analysis results for specific cities, which were often grouped due to similar parameter values, forming clusters that divided Europe into the eastern and western parts. Moreover, substantial differences in results were obtained for women and men.

scholarly journals Visualization of spatiotemporal data with different topology

2020 ◽  
Vol 2 ◽  
pp. 1-2
Author(s):  
Alena Vondráková ◽  
Vít Pászto
Keyword(s):  
Spatial Data ◽  
Spatiotemporal Analysis ◽  
Spatiotemporal Data ◽  
Identification Code ◽  
The Czech Republic ◽  
Advanced Technologies ◽  
Long Term Trends ◽  
Administrative Units

Abstract. The availability of advanced technologies, the time of information society, and also the development of geographic information systems, have brought a lot of spatial data in most disciplines, which are carefully stored in recent decades and allow us spatiotemporal analysis and visualization. However, for long-term analyses and the synthesis of analysed data, including cartographic synthesis processes, it is a big problem when spatiotemporal data have different topologies at different times. And this does not only mean the correction of borders in the sense of clarification or other distinction. The problem is when, for example, the small administrative units is subject to significant temporal changes. Municipalities are divided and merged, while data are always stored for the topology of a particular year or period.The contribution presents a way to solve such a situation on the example of the Czech Republic. Data from 25 years’ period are adjusted so that it is possible to calculate and visualize long-term trends and analyses. In the case of the case study, these are spatial data of more than 6,000 municipalities, with changes in more than 200 cases during the observed period. In addition to the spatial component, there were also changes in identifiers, which are a common means of joining data. For example, when the name of the municipality was changed and the newly "created" municipality also received new identification code. All these problems are solved by the so-called "super layer", which represents aggregation to the smallest possible extent so that the analyses performed are carried out on the most detailed possible scale without missing data in partial periods.The project goal is to explore various geodemographic processes at a very detailed level, specifically at NUTS (Nomenclature of Territorial Units for Statistics) local administrative units 2 (LAU2) commonly used in European Union for statistical purposes. Our presented dataset/approach unified municipal administrative units allowing analyses of data as they change over time. We used a principle of "common spatial denominator", i.e. we used data aggregation into larger units with stable boundary.

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