Table 1 - uploaded by Thomas Cova
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There is an increasing need for a quick, simple method to represent diurnal population change in metropolitan areas for effective emergency management and risk analysis. Many geographic studies rely on decennial U.S. Census data that assume that urban populations are static in space and time. This has obvious limitations in the context of dynamic g...
Contexts in source publication
Context 1
... the four hours of elapsed time from the chemical spill, a total of 64,726 people are potentially affected, and the plume reaches to 10 km away from the spill site. Table 1 includes the radius of the toxic plume and the potentially affected population at each hour. The potentially affected popula- tion begins relatively small, but by 6 p.m. more than 20,000 people are in danger, and the next two hours raise that number by approximately 20,000 more per hour. ...
Context 2
... block data are used to provide differ- ences between estimating affected populations in static and dynamic ways. In this example, a very close estimate of affected population is given by the block data and the interpolation method (see Table 1). The interpolated surface estimation calculated an average of 1,102 more people at each of the plume rings. ...
Citations
... Analysis of such data can reveal population trends in diverse temporal and spatial contexts, serving as a valuable resource for assessing population exposure levels, urban planning, business decisionmaking, and public safety (Freir, 2010;McKenzie et al., 2010). This approach includes several benefits, including low data collection costs, rapid updating, high spatio-temporal accuracy, and a large sample size, enabling more precise reflections of population behavior and needs (Kobayashi et al., 2011;Aubrecht et al., 2013). ...
Urban heat waves pose a significant risk to the health and safety of city dwellers, with urbanization potentially
amplifying the health impact of extreme heat. Accurate assessments of population heat exposure hinge on the
interplay between temperature, population spatial dynamics, and the epidemiological effects of temperature on
health. Yet, many past studies have over-simplified the matter by assuming static populations, leading to substantial
inaccuracies in heat exposure assessments. To address these issues, this study integrates dynamic population
data, fluctuating temperature, and the exposure-response relationship between temperature and health to
construct an advanced heat exposure assessment framework predicated on a population dynamic model. We
analyzed urban heat island characteristics, population dynamics, and heat exposure during heat wave conditions
in Beijing, a major city in China. Our findings highlight significant intra-day population movement between
urban and suburban areas during heat wave conditions, with spatial population flow patterns showing clear
scale-dependent characteristics. These population flow dynamics intensify heat exposure levels, and the disparity
between dynamic population-weighted temperature and average temperature is most pronounced at night. Our
research provides a more comprehensive understanding of real urban population heat exposure levels and can
furnish city administrators with more scientifically rigorous evidence.
... Second, to demonstrate demand, we used LandScan, a database of estimated global population distribution data (Rose et al. 2020). The dataset would enhance the accuracy of measurements given its finer spatial resolution (1 km × 1 km) (Luo and Qi 2009;Kobayashi, Medina, and Cova 2011). As LandScan data were provided as points, we aggregated the population with 2,000-acre hexagons (i.e., the average size of the census block group in the study area) to incorporate them into the accessibility measurement. ...
Sufficient and reliable health care access is necessary for people to be able to maintain good health. Hence, investigating the uncertainty embedded in the temporal changes of inputs would be beneficial for understanding their impact on spatial accessibility. However, previous studies are limited to implementing only the uncertainty of mobility, while health care resource availability is a significant concern during the coronavirus disease (COVID‐19) pandemic. Our study examined the stochastic distribution of spatial accessibility under the uncertainties underlying the availability of intensive care unit (ICU) beds and ease of mobility in the Greater Houston area of Texas. Based on the randomized supply and mobility from their historical changes, we employed Monte Carlo simulation to measure ICU bed accessibility with an enhanced two‐step floating catchment area (E2SFCA) method. We then conducted hierarchical clustering to classify regions of adequate (sufficient and reliable) accessibility and inadequate (insufficient and unreliable) accessibility. Lastly, we investigated the relationship between the accessibility measures and the case fatality ratio of COVID‐19. As result, locations of sufficient access also had reliable accessibility; downtown and outer counties, respectively, had adequate and inadequate accessibility. We also raised the possibility that inadequate health care accessibility may cause higher COVID‐19 fatality ratios.
... In other words, it reflects the nature of the daily activities of people who travel and conduct various activities across regions within a day. In these studies, researchers took advantage of census data [12,66] or GPS-enabled mobile phone usage data [13,15,59] to incorporate floating populations into the measurements. Thirdly, we grouped studies in which researchers furnished temporal dynamics in mobility from taxi trajectory data [61,63,64] or sophisticated transportation databases [13,62]. ...
Spatial accessibility provides significant policy implications, describing the spatial disparity of access and supporting the decision-making process for placing additional infrastructure at adequate locations. Several previous reviews have covered spatial accessibility literature, focusing on empirical findings, distance decay functions, and threshold travel times. However, researchers have underexamined how spatial accessibility studies benefitted from the recently enhanced availability of dynamic variables, such as various travel times via different transportation modes and the finer temporal granularity of geospatial data in these studies. Therefore, in our review, we investigated methodological advancements in place-based accessibility measures and scrutinized two recent trends in spatial accessibility studies: multimodal spatial accessibility and temporal changes in spatial accessibility. Based on the critical review, we propose two research agendas: improving the accuracy of measurements with dynamic variable implementation and furnishing policy implications granted from the enhanced accuracy. These agendas particularly call for the action of geographers on the full implementation of dynamic variables and the strong linkage between accessibility and policymaking.
... Data from the 2011 UK census includes estimates of the usual resident population, mid-year population and workday population. These measures of the population are currently widely used for academic research and industrial purposes [7,8]. The usual resident population is the count of the number of individuals usually resident at a given address. ...
This paper will critically assess the utility of conventional and novel data sources for building fine-scale spatio-temporal estimates of the ambient population. It begins with a review of data sources employed in existing studies of the ambient population, followed by preliminary analysis to further explore the utility of each dataset. The identification and critiquing of data sources which may be useful for building estimates of the ambient population are novel contributions to the literature. This paper will provide a framework of reference for researchers within urban analytics and other areas where an accurate measurement of the ambient population is required. This work has implications for national and international applications where accurate small area estimates of the ambient population are crucial in the planning and management of urban areas, the development of realistic models and informing policy. This research highlights workday population estimates, in conjunction with footfall camera and Wi-Fi sensors data as potentially valuable for building estimates of the ambient population.
... Yet timely evacuation or rescue in hazards (e.g. earthquakes, flash floods) have remained a persistent difficultly due to the lack of real-time information on the number and location of impacted populations (Kobayashi et al. 2011). ...
... Temporary populations are estimated using data from various sources, such as census data, surveys, transportation, remote sensing, Wi-Fi, and mobile phone data. Census-based temporary populations are generally estimated by adjusting the original census data using a variety of temporal and spatial measures [48,50,63,64]. Census data have an advantage in estimating the temporary population, such as daytime population, in that they represent entire populations in a certain region. ...
This study aims to examine the gender gaps in the use of urban space in Seoul, Korea, to provide empirical evidence for urban planning for gender equality. We analyzed daily temporary populations that were estimated using mobile phone data. We used the total, women’s, and men’s temporary populations as well as the subtraction of the temporary population of men from that of women (SMW) as dependent variables. We first conducted a visual analysis on temporary population density using kernel density estimation and then conducted a further analysis using spatial autocorrelation indicators and spatial regression models. The results demonstrate that: (1) Temporary population patterns for women and men showed similarities in that both were larger in business areas than in residential areas, which means that a large number of women were engaged in economic activities like men; (2) the pattern for SMW showed the opposite, that is, women were more active in residential areas and areas where neighborhood retail shops, cultural facilities, parks, and department stores were easily accessible; and (3) both women’s temporary population and SMW had spatial autocorrelation and thus showed clustering patterns that can be helpful in urban planning for gender equality in Korea.
... For this study, this involved discretizing both the CTPP Part 1 (number of workers by time leaving homes) and Part 2 data (number of workers by time arriving jobs) into consistent representations in both time (hourly interval) and space (grid cells). In terms of time, CTTP counts of jobs and workers were either aggregated or disaggregated to hourly measures following Kobayashi et al. (2011)'s study. For data from 5:00 a.m. to 11:00 a.m., corresponding 15-min counts were summed to obtain hourly estimates. ...
Place-based accessibility measures, such as the gravity-based model, are widely applied to study the spatial accessibility of workers to job opportunities in cities. However, gravity-based measures often suffer from three main limitations: (1) they are sensitive to the spatial configuration and scale of the units of analysis, which are not specifically designed for capturing job accessibility patterns and are often too coarse; (2) they omit the temporal dynamics of job opportunities and workers in the calculation, instead assuming that they remain stable over time; and (3) they do not lend themselves to dynamic geovisualization techniques. In this paper, a new methodological framework for measuring and visualizing place-based job accessibility in space and time is presented that overcomes these three limitations. First, discretization and dasymetric mapping approaches are used to disaggregate counts of jobs and workers over specific time intervals to a fine-scale grid. Second, Shen (1998) gravity-based accessibility measure is modified to account for temporal fluctuations in the spatial distributions of the supply of jobs and the demand of workers and is used to estimate hourly job accessibility at each cell. Third, a four-dimensional volumetric rendering approach is employed to integrate the hourly job access estimates into a space-time cube environment, which enables the users to interactively visualize the space-time job accessibility patterns. The integrated framework is demonstrated in the context of a case study of the Tampa Bay region of Florida. The findings demonstrate the value of the proposed methodology in job accessibility analysis and the policy-making process.
... The surface generated through KDE is useful as a visual summary of the underlying point patterns and can be subjected to quantitative analysis (De Floriani et al. 1996,, Sadahiro 2001, Sadahiro and Masui 2004, Kobayashi et al. 2010. Quantitative surface measures can include altitude, slope and aspect at any given location. ...
Capabilities for collecting and storing data on mobile objects have increased dramatically over the past few decades. A persistent difficulty is summarizing large collections of mobile objects. This paper develops methods for extracting and analyzing hotspots or locations with relatively high levels of mobility activity. We use kernel density estimation (KDE) to convert a large collection of mobile objects into a smooth, continuous surface. We then develop a topological algorithm to extract critical geometric features of the surface; these include critical points (peaks, pits and passes) and critical lines (ridgelines and course-lines). We connect the peaks and corresponding ridgelines to produce a surface network that summarizes the topological structure of the surface. We apply graph theoretic indices to analytically characterize the surface and its changes over time. To illustrate our approach, we apply the techniques to taxi cab data collected in Shanghai, China. We find increases in the complexity of the hotspot spatial distribution during normal activity hours in the late morning, afternoon and evening and a spike in the connectivity of the hotspot spatial distribution in the morning as taxis concentrate on servicing travel to work. These results match with scientific and anecdotal knowledge about human activity patterns in the study area.
... These estimates were produced for England and Wales using data from the 2011 Census (Office for National Statistics 2013); see also related work in Supplementary Table 3 Census data have served as an input into a host of other population estimates. Census-based studies from the United States include the work from the Seattle City Planning Commission (1951), Fulton (1984), Gober and Mings (1984), Nelson and Nicholas (1992), McPherson and Brown (2003), Kobayashi et al. (2011), Swanson and Tayman (2011), Hodur and Bangsund (2015), Kim and Ahn (2017), Boeing (2018) and Esri (2018). These papers used a range of methods to adjust Census estimates at a variety of temporal and spatial scales, often accompanied by other data sources including place of work, transportation models or payroll data that helps to determine size and location of daytime or seasonal populations. ...
The estimation of temporary populations is a well-established field, but despite growing interest they are yet to form part of the standard suite of official population statistics. This systematic review seeks to review the empirical literature on temporary population estimation and identify the contemporary “state of the art”. We identify a total of 96 studies that attempt to estimate or describe a method of estimation. Our findings reveal strong growth in the number of studies in recent decades that in part has been driven by the rise in both the type and availability of new sources of information, including mobile phone data. What emerges from this systematic review is the lack of any “gold standard” data source or methodology for temporary population estimation. The review points to a number of important challenges that remain for estimating temporary populations, both conceptually and practically. What remains is the need for clear definitions along with identification of appropriate data and methods that are able to robustly capture and measure the diverse array of spatial behaviours that drive temporary population dynamics. To our knowledge, this is the first review on this topic that brings together literature from various disciplines and collates methods used for estimation.
... Residential population data from the census best describe the nighttime population distribution. The worker commute information, including where people live and commute to and from, when leaving for work and travel time, was extracted from the 2006-2010 Census Transportation Planning Products (CTPP) (https://ctpp.transportation.org/) to characterize the daytime population flow in addition to the resi-dential population (35). The CTPP data provide the bulk number of population flow in and out of a geographic zone within a time interval but do not contain adequate information on the mode of commuting (e.g., by subway or by car) or the exact path of urban travelers. ...
Exposure to extreme temperatures is one primary cause of weather-related human mortality and morbidity. Global climate change raises the concern of public health under future extreme events, yet spatiotemporal population dynamics have been long overlooked in health risk assessments. Here, we show that the diurnal intra-urban movement alters residents’ exposure to extreme temperatures during cold and heat waves. To do so, we incorporate weather simulations with commute-adjusted population profiles over 16 major U.S. metropolitan areas. Urban residents’ exposure to heat waves is intensified by 1.9° ± 0.7°C (mean ± SD among cities), and their exposure to cold waves is attenuated by 0.6° ± 0.8°C. The higher than expected exposure to heat waves significantly correlates with the spatial temperature variability and requires serious attention. The essential role of population dynamics should be emphasized in temperature-related climate adaptation strategies for effective and successful interventions.
