OpenStreetMap Data Use Cases During the Early Months of the COVID-19 Pandemic

Mooney, Peter; Grinberger, A. Yair; Minghini, Marco; Coetzee, Serena; Juhász, Levente; Yeboah, Godwin

doi:10.1201/9781003181590-15

Cited by 16 publications

(12 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…WebGIS platforms for the dissemination of information to the public and data accessibility have already been addressed in other previous works (Boulos & Geraghty, 2020; Franch‐Pardo et al., 2020; Koller et al., 2020; Zúñiga et al., 2020). Some papers explain the technical operations of the web platform (Ghilardi et al., 2020; Graves & He, 2020; Hohl, Delmelle, Desjardins, & Lan, 2020; Mooney et al., 2020; Peddireddy et al., 2020; Sarfo & Karuppannan, 2020). Here we present a specific example in Mexico and briefly explain the operation of the university‐based platform maintained by the National Autonomous University of Mexico (https://covid19.ciga.unam.mx/).…”

Section: Resultsmentioning

confidence: 99%

A review of GIS methodologies to analyze the dynamics of COVID‐19 in the second half of 2020

Franch-Pardo

Desjardins

Barea-Navarro

et al. 2021

Transactions in GIS

View full text Add to dashboard Cite

COVID‐19 has infected over 163 million people and has resulted in over 3.9 million deaths. Regarding the tools and strategies to research the ongoing pandemic, spatial analysis has been increasingly utilized to study the impacts of COVID‐19. This article provides a review of 221 scientific articles that used spatial science to study the pandemic published from June 2020 to December 2020. The main objectives are: to identify the tools and techniques used by the authors; to review the subjects addressed and their disciplines; and to classify the studies based on their applications. This contribution will facilitate comparisons with the body of work published during the first half of 2020, revealing the evolution of the COVID‐19 phenomenon through the lens of spatial analysis. Our results show that there was an increase in the use of both spatial statistical tools (e.g., geographically weighted regression, Bayesian models, spatial regression) applied to socioeconomic variables and analysis at finer spatial and temporal scales. We found an increase in remote sensing approaches, which are now widely applied in studies around the world. Lockdowns and associated changes in human mobility have been extensively examined using spatiotemporal techniques. Another dominant topic studied has been the relationship between pollution and COVID‐19 dynamics, which enhance the impact of human activities on the pandemic's evolution. This represents a shift from the first half of 2020, when the research focused on climatic and weather factors. Overall, we have seen a vast increase in spatial tools and techniques to study COVID‐19 transmission and the associated risk factors.

show abstract

Section: Resultsmentioning

confidence: 99%

A review of GIS methodologies to analyze the dynamics of COVID‐19 in the second half of 2020

Franch-Pardo

Desjardins

Barea-Navarro

et al. 2021

Transactions in GIS

View full text Add to dashboard Cite

show abstract

“…We use OSM to obtain the parks within each city. While OSM data is collected via crowdsourcing, it is ubiquitous, making it an appealing spatial data source [ 33 ]. Spatial objects in OSM are tagged under various categories [ 34 ], based on the uses they have.…”

Section: Methodsmentioning

confidence: 99%

Exposure to parks through the lens of urban mobility

et al. 2022

View full text Add to dashboard Cite

This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city’s information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday.We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities’ distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities’ tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city.

show abstract

“…Therefore, studies analyzing map viewing behavior (see e.g. Mooney et al (2021)) should be aware of this and not mistake increased data volume (e.g. at Null Island) with increased activity.…”

Section: Geospatial Technologymentioning

confidence: 99%

'I think I discovered a military base in the middle of the ocean' -- Null Island, the most real of fictional places

Juhasz,

Mooney

2022

Preprint

Self Cite

View full text Add to dashboard Cite

This paper explores Null Island, a fictional place located at 0°latitude and 0°longitude in the WGS84 geographic coordinate system. Null Island is erroneously associated with large amounts of geographic data in a wide variety of location-based services, place databases, social media and web-based maps. While it was originally considered a joke within the geospatial community, this article will demonstrate implications of its existence, both technological and social in nature, promoting Null Island as a fundamental issue of geographic information that requires more widespread awareness. The article summarizes error sources that lead to data being associated with Null Island. We identify four evolutionary phases which help explain how this fictional place evolved and established itself as an entity reaching beyond the geospatial profession to the point of being discovered by the visual arts and the general population. After providing an accurate account of data that can be found at (0, 0), geospatial, technological and social implications of Null Island are discussed. Guidelines to avoid misplacing data to Null Island are provided. Since data will likely continue to appear at this location, our contribution is aimed at both GIScientists and the general population to promote awareness of this error source.

show abstract

OpenStreetMap Data Use Cases During the Early Months of the COVID-19 Pandemic

Cited by 16 publications

References 30 publications

A review of GIS methodologies to analyze the dynamics of COVID‐19 in the second half of 2020

A review of GIS methodologies to analyze the dynamics of COVID‐19 in the second half of 2020

Exposure to parks through the lens of urban mobility

'I think I discovered a military base in the middle of the ocean' -- Null Island, the most real of fictional places

Contact Info

Product

Resources

About