This page has only limited features, please log in for full access.
We propose a scalable agent-based crime simulation model based on the routine activity theory. It uses census data and time geography to create a synthetic population with residences and job locations, commuting schedules, and daily routines constrained by disposable time that are more representative than existing models. The time and location of crime incidents in this model are determined by random encounters between vulnerable targets and motivated offenders when they travel or carry out scheduled activities on a road network. This model is applied to simulate robberies in January 2011 for Baton Rouge, Louisiana. Three scenarios are simulated to demonstrate its value for crime theory development and shed light on modeling issues in need of improvement before it can reliably assist policymaking or inform the public. Major findings from this study include the model's ability to replicate prominent robbery hotspots in the study area with various degrees of success and the consistent effects of target definition and offender strategy on model performance. The study also suggests missing model components to effectively constrain the displacement of crime opportunities under hotspot policing, which can be the key to resolving contradiction between our simulation results and other empirical researches and crime simulations.
Haojie Zhu; Fahui Wang. An agent-based model for simulating urban crime with improved daily routines. Computers, Environment and Urban Systems 2021, 89, 101680 .
AMA StyleHaojie Zhu, Fahui Wang. An agent-based model for simulating urban crime with improved daily routines. Computers, Environment and Urban Systems. 2021; 89 ():101680.
Chicago/Turabian StyleHaojie Zhu; Fahui Wang. 2021. "An agent-based model for simulating urban crime with improved daily routines." Computers, Environment and Urban Systems 89, no. : 101680.
Spatial behavior of patients in utilizing health care reflects their travel burden or mobility, accessibility for medical service, and subsequently outcomes from treatment. This paper derives the best-fitting distance decay function to capture the spatial behaviors of cancer patients in the Northeast region of the U.S., and examines and explains the spatial variability of such behaviors across sub-regions. (1) 46.8%, 85.5%, and 99.6% of cancer care received was within a driving time of 30, 60, and 180 min, respectively. (2) The exponential distance decay function is the best in capturing the travel behavior of cancer patients in the region and across most sub-regions. (3) The friction coefficient in the distance decay function is negatively correlated with the mean travel time. (4) The best-fitting function forms are associated with network structures. (5) The variation of the friction coefficient across sub-regions is related to factors such as urbanicity, economic development level, and market competition intensity. The distance decay function offers an analytic metric to capture a full spectrum of travel behavior, and thus a more comprehensive measure than average travel time. Examining the geographic variation of travel behavior needs a reliable analysis unit such as organically defined “cancer service areas,” which capture relevant health care market structure and thus are more meaningful than commonly-used geopolitical or census area units.
Changzhen Wang; Fahui Wang; Tracy Onega. Spatial behavior of cancer care utilization in distance decay in the Northeast region of the U.S. Travel Behaviour and Society 2021, 24, 291 -302.
AMA StyleChangzhen Wang, Fahui Wang, Tracy Onega. Spatial behavior of cancer care utilization in distance decay in the Northeast region of the U.S. Travel Behaviour and Society. 2021; 24 ():291-302.
Chicago/Turabian StyleChangzhen Wang; Fahui Wang; Tracy Onega. 2021. "Spatial behavior of cancer care utilization in distance decay in the Northeast region of the U.S." Travel Behaviour and Society 24, no. : 291-302.
Constructing service areas is an important task for evaluating geographic variations of health care markets. This study uses cancer care as an example to illustrate the methodology, with the nine‐state Northeast Region of the USA as the study area. Two recent algorithms of network community detection are implemented to account for additional constraints such as spatial connectivity and threshold region size. The refined methods are termed “spatially constrained Louvain” (ScLouvain) and “spatially constrained Leiden” (ScLeiden) algorithms, corresponding to their predecessors the Louvain and Leiden algorithms, respectively. Both are network optimization methods that maximize flows within delineated communities while minimizing inter‐community flows. The service areas derived by the methods, termed “cancer service areas”, are more favorable than the commonly used comparable unit, hospital referral regions, for evaluating cancer‐specific variations in care. Between the two, the ScLeiden performs better than the ScLouvain in terms of modularity, localization index and computational efficiency, and thus is recommended as an effective and efficient approach for defining functional regions.
Changzhen Wang; Fahui Wang; Tracy Onega. Network optimization approach to delineating health care service areas: Spatially constrained Louvain and Leiden algorithms. Transactions in GIS 2020, 25, 1065 -1081.
AMA StyleChangzhen Wang, Fahui Wang, Tracy Onega. Network optimization approach to delineating health care service areas: Spatially constrained Louvain and Leiden algorithms. Transactions in GIS. 2020; 25 (2):1065-1081.
Chicago/Turabian StyleChangzhen Wang; Fahui Wang; Tracy Onega. 2020. "Network optimization approach to delineating health care service areas: Spatially constrained Louvain and Leiden algorithms." Transactions in GIS 25, no. 2: 1065-1081.
This study examines what socio-demographic and spatial factors explain the variation of public transit ridership in a medium-size city in southern U.S. – Baton Rouge, Louisiana. In order to gain a sharper spatial resolution in the analysis, the ecological inference method is used to disaggregate socio-demographic data from the census block group level to the census block level. Monte Carlo simulation and transit schedule data are used to improve the estimation of travel time by private vehicle and public transit, respectively, also at the census block level. The semi-parametric geographically-weighted regression (SGWR) is used to identify, among significant variables, what are global factors and what are local factors. The results indicate that neighborhoods with higher concentrations of non-White minorities, recent immigrants and carless households have positive global effects on public transit ridership. The effects by neighborhood median income, public transit to private vehicle commuting time ratio, and accessibility to employment via public transit are localized or vary across the study area, and some of these variables even show opposite effects in specific pockets in contrast to their area-wide average effects.
Xuan Kuai; Fahui Wang. Global and localized neighborhood effects on public transit ridership in Baton Rouge, Louisiana. Applied Geography 2020, 124, 102338 .
AMA StyleXuan Kuai, Fahui Wang. Global and localized neighborhood effects on public transit ridership in Baton Rouge, Louisiana. Applied Geography. 2020; 124 ():102338.
Chicago/Turabian StyleXuan Kuai; Fahui Wang. 2020. "Global and localized neighborhood effects on public transit ridership in Baton Rouge, Louisiana." Applied Geography 124, no. : 102338.
Uneven distributions of population and service providers lead to geographic disparity in access for residents and varying workload for staff in facilities. The former can be captured by spatial accessibility in the traditional two-step floating catchment area (2SFCA) method; and the latter can be measured by potential crowdedness in the newly developed inverted 2SFCA (or i2SFCA) method. Residents-based accessibility and facility crowdedness are two sides of the same coin in examining the geographic variability of resource allocation. This short research note derives the formulations of both methods to solidify their theoretical foundation and uses a case study to validate both. By doing so, the 2SFCA and i2SFCA are fully integrated into one conceptual framework, derived with extensions to the Huff model, and validated by empirical data.
Fahui Wang. From 2SFCA to i2SFCA: integration, derivation and validation. International Journal of Geographical Information Science 2020, 35, 628 -638.
AMA StyleFahui Wang. From 2SFCA to i2SFCA: integration, derivation and validation. International Journal of Geographical Information Science. 2020; 35 (3):628-638.
Chicago/Turabian StyleFahui Wang. 2020. "From 2SFCA to i2SFCA: integration, derivation and validation." International Journal of Geographical Information Science 35, no. 3: 628-638.
This research attempts to build a unified framework for distinguishing the spatiotemporal visit patterns of urban places by different social groups using mobile phone data in Harbin, China. Social groups are detected by their social ties in the ego‐to‐ego mobile phone call network and are embedded in physical space according to their home locations. Popular urban places are detected from user‐generated content as the basic spatial analysis unit. Coupling subscribers’ footprints and urban places in physical space, the spatiotemporal visit patterns of urban places by distinct social groups are uncovered and interpreted by non‐negative matrix factorization. The proposed framework enables us to answer several critical questions from three perspectives: (1) How to model popular urban places in terms of vague boundary, land use, and semantic features based on crowdsourcing data?; (2) How to evaluate interaction between individuals for inspecting the relationship between spatial proximity and social ties based on spatiotemporal co‐occurrence?; and (3) How to distinguish urban place visit preferences for social groups associated with different socio‐demographic characteristics? Our research could assist urban planners and municipal managers to identify critical urban places frequented by different population groups according to their roles and social/cultural characteristics for improvement of urban facility allocation.
Chaogui Kang; Li Shi; Fahui Wang; Yu Liu. How urban places are visited by social groups? Evidence from matrix factorization on mobile phone data. Transactions in GIS 2020, 24, 1504 -1525.
AMA StyleChaogui Kang, Li Shi, Fahui Wang, Yu Liu. How urban places are visited by social groups? Evidence from matrix factorization on mobile phone data. Transactions in GIS. 2020; 24 (6):1504-1525.
Chicago/Turabian StyleChaogui Kang; Li Shi; Fahui Wang; Yu Liu. 2020. "How urban places are visited by social groups? Evidence from matrix factorization on mobile phone data." Transactions in GIS 24, no. 6: 1504-1525.
Yujie Hu; Changzhen Wang; Ruiyang Li; Fahui Wang. Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach. Journal of Transport Geography 2020, 86, 1 .
AMA StyleYujie Hu, Changzhen Wang, Ruiyang Li, Fahui Wang. Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach. Journal of Transport Geography. 2020; 86 ():1.
Chicago/Turabian StyleYujie Hu; Changzhen Wang; Ruiyang Li; Fahui Wang. 2020. "Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach." Journal of Transport Geography 86, no. : 1.
This study uses six censuses (1953, 1964, 1982, 1990, 2000, and 2010) at the county level since the foundation of the People’s Republic of China to examine the changes of population density pattern in mainland China over time. Based on the Gini coefficient, the change of disparity in population density followed a “U-shaped” trend, i.e., decreasing during 1953–1982 and increasing during 1982–2010. The shrinking disparity in the pre-reform periods was largely attributable to various ill-conceived political movements, and the enlarging gap in population growth rates in the post-reform era reflected a natural outcome of urbanization, which will continue in the foreseeable future. In addition, this research employs a GIS-automated regionalization method, REDCAP, to uncover a natural demarcation line like the classic “Hu Line” that divides China into two regions of similar area sizes but a strong contrast in population. The results show that the regionalization-derived lines were largely consistent with the Hu Line over time. Therefore, the disparity between the high-density southeast and low-density northwest regions is likely due to differing physical environments that form a natural barrier. Any public policy to overcome this barrier at a large scale is destined to be a vain attempt.
Cuiling Liu; Yaping Xu; Fahui Wang. Population distribution patterns and changes in China 1953–2010. Journal of Geographical Sciences 2019, 29, 1908 -1922.
AMA StyleCuiling Liu, Yaping Xu, Fahui Wang. Population distribution patterns and changes in China 1953–2010. Journal of Geographical Sciences. 2019; 29 (11):1908-1922.
Chicago/Turabian StyleCuiling Liu; Yaping Xu; Fahui Wang. 2019. "Population distribution patterns and changes in China 1953–2010." Journal of Geographical Sciences 29, no. 11: 1908-1922.
This study examines spatial accessibility of primary care in the Baton Rouge Metropolitan Statistical Area, Louisiana. Two popular accessibility measures are used: the proximity method focuses on the travel time from the nearest facility and the two-step floating catchment area (2SFCA) method considers the match ratio between providers and population as well as the complex spatial interaction between them. The two methods capture different elements of spatial accessibility: one being physically close to a facility and another adding availability of service. Both properties can be valuable for residents. In the study area, residents in urban areas generally enjoy shorter travel time from their nearest service providers as well as higher accessibility scores measured by the 2SFCA method (i.e., physicians per 1000 residents) than rural residents. Overall, disproportionally higher percentages of African Americans are in areas with shorter travel time to the nearest primary care providers and higher accessibility scores; so are residents in areas of higher poverty rates. This “reversed racial advantage” in spatial accessibility does not capture nonspatial obstacles related to financial and other socioeconomic factors for African Americans (and population in poverty) and nevertheless represents one fewer battle to fight in reducing healthcare disparities for various disadvantaged population groups. Such an advantage disappears or is even reversed in remote rural areas with high concentration of African Americans, who suffer from double disadvantages in both spatial and nonspatial access to primary care.
Fahui Wang; Michael Vingiello; Imam M. Xierali. Serving a Segregated Metropolitan Area: Disparities in Spatial Access to Primary Care Physicians in Baton Rouge, Louisiana. Ecology of Tuberculosis in India 2019, 75 -94.
AMA StyleFahui Wang, Michael Vingiello, Imam M. Xierali. Serving a Segregated Metropolitan Area: Disparities in Spatial Access to Primary Care Physicians in Baton Rouge, Louisiana. Ecology of Tuberculosis in India. 2019; ():75-94.
Chicago/Turabian StyleFahui Wang; Michael Vingiello; Imam M. Xierali. 2019. "Serving a Segregated Metropolitan Area: Disparities in Spatial Access to Primary Care Physicians in Baton Rouge, Louisiana." Ecology of Tuberculosis in India , no. : 75-94.
In developed countries with decreasing fertility rates, the provision of public daycare and kindergarten (PDK) is considered to be an important policy for boosting national birth rates. Since PDK is free, its spatial accessibility becomes the most critical factor for parents in choosing the service. The study uses the popular two-step floating catchment area model (2SFCA) to analyze the spatial accessibility of PDKs at a 100 m × 100 m cell level in Seoul, South Korea. A GIS-automated regionalization method, Mixed-Level Regionalization (MLR), is employed to divide the study area into homogenous regions based on a concentrated disadvantage index (CDI). The analysis then proceeds to examine the disparity of PDK accessibility across these constructed regions. The result empowers parents to be informed of the access of PDKs in their current neighborhoods or to look for neighborhoods with adequate access. Several policy measures are proposed for improving overall accessibility of PDKs and more so for underserved populations.
Hyunjoong Kim; Fahui Wang. Disparity in Spatial Access to Public Daycare and Kindergarten across GIS-Constructed Regions in Seoul, South Korea. Sustainability 2019, 11, 5503 .
AMA StyleHyunjoong Kim, Fahui Wang. Disparity in Spatial Access to Public Daycare and Kindergarten across GIS-Constructed Regions in Seoul, South Korea. Sustainability. 2019; 11 (19):5503.
Chicago/Turabian StyleHyunjoong Kim; Fahui Wang. 2019. "Disparity in Spatial Access to Public Daycare and Kindergarten across GIS-Constructed Regions in Seoul, South Korea." Sustainability 11, no. 19: 5503.
The famous ‘Hu Line’, proposed by Hu Huanyong in 1935, divided China into two regions (southeast and northwest) of comparable area size but drastically different in population. However, the classic Hu Line was derived manually in absence of reliable census data and computational technologies of modern days. It has been subject to criticism of lack of scientific rigor and accuracy. This research uses a GIS-automated regionalization method, termed REDCAP (Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning), to reconstruct the demarcation line based on the 2010 county-level census data in China. The results show that the logarithmic transformation of population density is a better measure of attributive homogeneity in derived regions than density itself, and produces two regions of nearly identical area size and greater contrast in population. Specifically, the revised Hu Line by Hu Huanyong in 1990 had the southeast region with 94.4% of total population and 42.9% of total land, and our delineation line yields a southeast region with 97.4% population and 50.8% land. Therefore, the population density ratio of the two regions is 27.1 by our line, much higher than the ratio of 22.4 by the Hu Line, and thus outperforms the Hu Line in deriving regions of maximum density contrast with comparable area size. Furthermore, more regions are delineated to further advance our understanding of population distribution disparity in China.
Fahui Wang; Cuiling Liu; Yaping Xu. Analyzing Population Density Disparity in China with GIS-automated Regionalization: The Hu Line Revisited. Chinese Geographical Science 2019, 29, 541 -552.
AMA StyleFahui Wang, Cuiling Liu, Yaping Xu. Analyzing Population Density Disparity in China with GIS-automated Regionalization: The Hu Line Revisited. Chinese Geographical Science. 2019; 29 (4):541-552.
Chicago/Turabian StyleFahui Wang; Cuiling Liu; Yaping Xu. 2019. "Analyzing Population Density Disparity in China with GIS-automated Regionalization: The Hu Line Revisited." Chinese Geographical Science 29, no. 4: 541-552.
Understanding patients’ travel behavior for seeking hospital care is fundamental for understanding healthcare market and planning for resource allocation. However, few studies examined the issue comprehensively across populations by geographical, demographic, and health insurance characteristics. Based on the 2011 State Inpatient Database in Florida, this study modeled patients’ travel patterns for hospital inpatient care across geographic areas (by average affluence, urbanicity) and calendar seasons, and across subpopulations (by age, gender, race/ethnicity, and health insurance status). Overall, travel patterns for all subpopulations were best captured by the log-logistic function. Patients in more affluent areas and rural areas tended to travel longer for hospital inpatient care, so did the younger, whites, and privately insured. Longer travel distances may be a necessity for rural patients to cope with lack of accessibility for local hospital care, but for the other population groups, it may indicate rather better mobility and more healthcare choices. The results can be used in various healthcare analyses such as accessibility assessment, hospital service area delineation, and healthcare resource planning.
Peng Jia; Fahui Wang; Imam Xierali. Differential effects of distance decay on hospital inpatient visits among subpopulations in Florida, USA. Environmental Monitoring and Assessment 2019, 191, 1 -16.
AMA StylePeng Jia, Fahui Wang, Imam Xierali. Differential effects of distance decay on hospital inpatient visits among subpopulations in Florida, USA. Environmental Monitoring and Assessment. 2019; 191 (2):1-16.
Chicago/Turabian StylePeng Jia; Fahui Wang; Imam Xierali. 2019. "Differential effects of distance decay on hospital inpatient visits among subpopulations in Florida, USA." Environmental Monitoring and Assessment 191, no. 2: 1-16.
The stunning disparity in population density between the southeast and northwest in China is highlighted by the “Hu Line,” a famous population demarcation line proposed by Huanyong Hu in 1935. This research seeks to uncover the underlying physical environment factors that shape such a contrast. Specifically, we propose a habitation environment suitability index (HESI) model to integrate topographic factors, climatic suitability, and hydrological condition into one comprehensive index, and then use a GIS‐automated regionalization method termed REDCAP (Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning) to derive two demarcation lines based on the HESI and population density values, respectively. The two lines that divide China into two regions are largely consistent with each other. The result indicates that the population distribution disparity between the southeast and northwest is largely attributable to the difference in physical environments, and the barrier defined by the Hu Line is here to stay. In addition, the research also explores the (in)consistency between population density and HESI distribution patterns in various regions.
Cuiling Liu; Fahui Wang; Yaping Xu. Habitation environment suitability and population density patterns in China: A regionalization approach. Growth and Change 2018, 50, 184 -200.
AMA StyleCuiling Liu, Fahui Wang, Yaping Xu. Habitation environment suitability and population density patterns in China: A regionalization approach. Growth and Change. 2018; 50 (1):184-200.
Chicago/Turabian StyleCuiling Liu; Fahui Wang; Yaping Xu. 2018. "Habitation environment suitability and population density patterns in China: A regionalization approach." Growth and Change 50, no. 1: 184-200.
Variability in spatial accessibility of emergency medical services has become a major concern in evaluating the quality of emergency medical services in China. Unlike some other public services, response time is critical in the provision of emergency medical services. Traffic congestion may significantly affect response time, especially in large cities. This study uses a transportation simulation model to estimate the travel time under free-flow and congested road conditions and measure the corresponding spatial accessibility of emergency medical services for various hours of a day in inner-city Shanghai. When traffic congestion is considered, the overall spatial accessibility is significantly reduced, and the effect is further magnified in certain congested areas. The results help policy makers in planning the emergency medical services resource that is sensitive to the spatiotemporal variation of its accessibility.
Wenyan Hu; Jinkai Tan; Mengya Li; Jun Wang; Fahui Wang. Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai. Environment and Planning B: Urban Analytics and City Science 2018, 47, 841 -854.
AMA StyleWenyan Hu, Jinkai Tan, Mengya Li, Jun Wang, Fahui Wang. Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai. Environment and Planning B: Urban Analytics and City Science. 2018; 47 (5):841-854.
Chicago/Turabian StyleWenyan Hu; Jinkai Tan; Mengya Li; Jun Wang; Fahui Wang. 2018. "Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai." Environment and Planning B: Urban Analytics and City Science 47, no. 5: 841-854.
Traditional census data are ill-suited for uncovering the true population patterns and underlying social and economic dynamics in China as the census relies on information of population with registered household status. A large number of migrant workers are registered rural residents but spend most of a year working in cities that are hundreds or even thousands of miles away. It is termed “annual spatial mismatch” here for the separation of registered residence and workplace in China, in contrast to “spatial mismatch” that is known in the urban commuting literature in the west but on a daily basis. Big geo-data, such as the mobile app data, afford us a rare opportunity to examine this unique phenomenon. Specifically, this research uses a mobile app dataset of two epochs, i.e., prior to and during the Chinese Spring Festival, to capture the population patterns before and after the migrant workers return home, respectively. The difference between them reflects distinctive roles of an area plays in labor market, termed “source-sink areas”. A GIS-automated regionalization method is used to delineate China into hierarchical “source-sink” areas, characterizing various urbanization levels or distinctive roles in labor market. The study demonstrates the value of using human mobility data in urban and regional analysis on issues that were previously infeasible, especially in study areas without reliable data.
Yuxia Wang; Fahui Wang; Yi Zhang; Yu Liu. Delineating urbanization “source-sink” regions in China: Evidence from mobile app data. Cities 2018, 86, 167 -177.
AMA StyleYuxia Wang, Fahui Wang, Yi Zhang, Yu Liu. Delineating urbanization “source-sink” regions in China: Evidence from mobile app data. Cities. 2018; 86 ():167-177.
Chicago/Turabian StyleYuxia Wang; Fahui Wang; Yi Zhang; Yu Liu. 2018. "Delineating urbanization “source-sink” regions in China: Evidence from mobile app data." Cities 86, no. : 167-177.
Commuting is an essential part of urban life. Long commutes have negative impacts on individuals and society, such as stress, loss of productivity, traffic congestion and air pollution. However, researchers often face the challenge of lack of data such as commute distance, duration, departure/arrival time, and origins/destinations in countries such as China. This study uses points of interest (POIs) to estimate employment locations, and implements a gravity-based model to estimate interzonal commuting patterns in central Shanghai, China. The results reveal a “busy corridor” in the west of the central city, especially during the morning peak hours. This pattern corresponds well with reported real-time traffic conditions in Shanghai. Our methodology offers a promising alternative for studying commuting patterns when such data are limited.
Mengya Li; Mei-Po Kwan; Fahui Wang; Jun Wang. Using points-of-interest data to estimate commuting patterns in central Shanghai, China. Journal of Transport Geography 2018, 72, 201 -210.
AMA StyleMengya Li, Mei-Po Kwan, Fahui Wang, Jun Wang. Using points-of-interest data to estimate commuting patterns in central Shanghai, China. Journal of Transport Geography. 2018; 72 ():201-210.
Chicago/Turabian StyleMengya Li; Mei-Po Kwan; Fahui Wang; Jun Wang. 2018. "Using points-of-interest data to estimate commuting patterns in central Shanghai, China." Journal of Transport Geography 72, no. : 201-210.
Predictive hotspot mapping plays a critical role in hotspot policing. Existing methods such as the popular kernel density estimation (KDE) do not consider the temporal dimension of crime. Building upon recent works in related fields, this article proposes a spatio-temporal framework for predictive hotspot mapping and evaluation. Comparing to existing work in this scope, the proposed framework has four major features: (1) a spatio-temporal kernel density estimation (STKDE) method is applied to include the temporal component in predictive hotspot mapping, (2) a data-driven optimization technique, the likelihood cross-validation, is used to select the most appropriate bandwidths, (3) a statistical significance test is designed to filter out false positives in the density estimates, and (4) a new metric, the predictive accuracy index (PAI) curve, is proposed to evaluate predictive hotspots at multiple areal scales. The framework is illustrated in a case study of residential burglaries in Baton Rouge, Louisiana in 2011, and the results validate its utility.
Yujie Hu; Fahui Wang; Cecile Guin; Haojie Zhu. A spatio-temporal kernel density estimation framework for predictive crime hotspot mapping and evaluation. Applied Geography 2018, 99, 89 -97.
AMA StyleYujie Hu, Fahui Wang, Cecile Guin, Haojie Zhu. A spatio-temporal kernel density estimation framework for predictive crime hotspot mapping and evaluation. Applied Geography. 2018; 99 ():89-97.
Chicago/Turabian StyleYujie Hu; Fahui Wang; Cecile Guin; Haojie Zhu. 2018. "A spatio-temporal kernel density estimation framework for predictive crime hotspot mapping and evaluation." Applied Geography 99, no. : 89-97.
Most empirical studies indicate that the pattern of declining urban population density with distance from the city center is best captured by a negative exponential function. Such studies usually use aggregated data in census area units that are subject to several criticisms such as modifiable areal unit problem, unfair sampling, and uncertainty in distance measure. In order to mitigate these concerns associated, this paper uses Monte Carlo simulation to generate individual residents that are consistent with known patterns of population distribution. By doing so, we are able to aggregate population back to various uniform area units to examine the scale and zonal effects explicitly. The case study in Chicago area indicates that the best fitting density function remains exponential for data in census tracts or block groups, however, the logarithmic function becomes a better fit when uniform area units such as squares, triangles or hexagons are used. The study also suggests that the scale effect remain to some extent in all area units, and the zonal effect be largely mitigated by uniform area units of regular shape.
Fahui Wang; Cuiling Liu; Yaping Xu. Mitigating the zonal effect in modeling urban population density functions by Monte Carlo simulation. Environment and Planning B: Urban Analytics and City Science 2018, 46, 1061 -1078.
AMA StyleFahui Wang, Cuiling Liu, Yaping Xu. Mitigating the zonal effect in modeling urban population density functions by Monte Carlo simulation. Environment and Planning B: Urban Analytics and City Science. 2018; 46 (6):1061-1078.
Chicago/Turabian StyleFahui Wang; Cuiling Liu; Yaping Xu. 2018. "Mitigating the zonal effect in modeling urban population density functions by Monte Carlo simulation." Environment and Planning B: Urban Analytics and City Science 46, no. 6: 1061-1078.
The National Cancer Institute (NCI) Cancer Centers form the backbone of the cancer care system in the United States since their inception in the early 1970s. Most studies on their geographic accessibility used primitive measures, and did not examine the disparities across urbanicity or demographic groups. This research uses an advanced accessibility method, termed “2-step floating catchment area (2SFCA)” and implemented in Geographic Information Systems (GIS), to capture the degree of geographic access to NCI Cancer Centers by accounting for competition intensity for the services and travel time between residents and the facilities. The results indicate that urban advantage is pronounced as the average accessibility is highest in large central metro areas, declines to large fringe metro, medium metro, small metro, micropolitan and noncore rural areas. Population under the poverty line are disproportionally concentrated in lower accessibility areas. However, on average Non-Hispanic White have the lowest geographic accessibility, followed by Hispanic, Non-Hispanic Black and Asian, and the differences are statistically significant. The “reversed racial disadvantage” in NCI Cancer Center accessibility seems counterintuitive but is consistent with an influential prior study; and it is in contrast to the common observation of co-location of concentration of minority groups and people under the poverty line.
Yanqing Xu; Cong Fu; Tracy Onega; Xun Shi; Fahui Wang. Disparities in Geographic Accessibility of National Cancer Institute Cancer Centers in the United States. Journal of Medical Systems 2017, 41, 1 -11.
AMA StyleYanqing Xu, Cong Fu, Tracy Onega, Xun Shi, Fahui Wang. Disparities in Geographic Accessibility of National Cancer Institute Cancer Centers in the United States. Journal of Medical Systems. 2017; 41 (12):1-11.
Chicago/Turabian StyleYanqing Xu; Cong Fu; Tracy Onega; Xun Shi; Fahui Wang. 2017. "Disparities in Geographic Accessibility of National Cancer Institute Cancer Centers in the United States." Journal of Medical Systems 41, no. 12: 1-11.
Hospital service area (HSA) and hospital referral region (HRR), known as a hierarchical HSA system, have been used as analysis units in a growing body of large-scale studies of healthcare spending, utilization, and outcome in the United States. However, the popular Dartmouth HSAs and HRRs were produced more than two decades ago and are unable to represent contemporary healthcare markets. This research uses a revised Huff Model to delineate two levels of hospital service areas in Florida, resulting in sixty-four HSAs nested in twenty-one HRRs. Three elements distinguish our method from existing work. First, a best-fitting distance-decay function derived from the actual travel pattern of hospitalization is embedded in the Huff Model to strengthen the model's theoretical foundation in individual spatial behavior. Secondly, the hierarchal central place structure is supported by the differing travel-friction coefficients for general versus specialized patients; general patients experience a steeper gradient and thus a shorter average travel range that supports delineating more HSAs of smaller area size, and specialized patients exhibit a flatter gradient and thus a longer average travel range that leads to fewer HRRs of large-sized areas. Finally, the delineation method automated in geographic information systems (GIS) can be easily replicated in other regions to define large-scale and consistent hierarchical HSA systems.
Peng Jia; Fahui Wang; Imam Xierali. Delineating Hierarchical Hospital Service Areas in Florida. Geographical Review 2017, 107, 608 -623.
AMA StylePeng Jia, Fahui Wang, Imam Xierali. Delineating Hierarchical Hospital Service Areas in Florida. Geographical Review. 2017; 107 (4):608-623.
Chicago/Turabian StylePeng Jia; Fahui Wang; Imam Xierali. 2017. "Delineating Hierarchical Hospital Service Areas in Florida." Geographical Review 107, no. 4: 608-623.