An Integrated GIS Approach to Accessibility Analysis

Accessibility is an important element in evaluating existing land‐use patterns and transportation services, predicting travel demands and programming transportation investments in urban transportation planning. This paper presents an integrated GIS approach to accessibility analysis, which provides a general framework for integrated use of GIS, travel impedance measurement tools and accessibility measures to support the accessibility analysis process, including formulating the concept of accessibility, selecting or developing accessibility measures, specifying the accessibility measures, deriving the accessibility values using the selected or developed accessibility measures, and presenting and interpreting the accessibility values. An integrated GIS tool, ACCESS, designed for implementing the integrated approach is also described and illustrated.     

Understanding the interplay between bus,metro, and cab ridership dynamics in Shenzhen,China

The most common mass transit modes in metropolitan cities include buses, subways, and taxicabs, each of which contribute to an interconnected complex network that delivers urban dwellers to their destinations. Understanding the intertwined usages of these three transit modes at different places and time allows for better sensing of urban mobility and the built environment. In this article, we leverage a comprehensive data collection of bus, metro, and taxicab ridership from Shenzhen, China to unveil the spatio‐temporal interplay between different mass transit modes. To achieve this goal, we develop a novel spectral clustering framework that imposes spatio‐temporal similarities between mass transit mode usage in urban space and differentiates urban spaces associated with distinct ridership patterns of mass transit modes. Five resulting categories of urban spaces are identified and interpreted with auxiliary knowledge of the city's metro network and land‐use functionality. In general, different categorized urban spaces are associated with different accessibility levels (such as high‐, medium‐, and low‐ranked) and different urban functionalities (such as residential, commercial, leisure‐dominant, and home–work balanced). The results indicate that different mass transit modes cooperate or compete based on demographic and socioeconomic attributes of the underlying urban environments. Our proposed analytical framework provides a novel and effective way to explore the mass transit system and the functional heterogeneity in cities. It demonstrates great potential for assisting policymakers and municipal managers in optimizing public transportation facility allocation and city‐wide daily commuting distribution.     

Accessibility tradeoffs in public transit planning

 Spatial accessibility is a critical consideration in the provision of services, both public and private. In public transit planning, accessibility is comprised of access and geographic coverage. Interestingly, these two considerations are somewhat at odds with each other. Access is important because it is the process associated with getting to and departing from the service. Such access is typically perceived of in spatial terms as the physical proximity to transit stops or stations. Additional stops along a route usually mean greater access, because a stop is more likely to be within an acceptable walking/driving standard for a larger number of people. On the other hand, more stops and greater access slow transit travel speeds, thereby decreasing the area of service reachable given a travel time budget. More stops along a route translate to greater service interruption and longer travel times. The faster the travel time, the more desirable the service. Further, if travel times become excessive, then user demand for service will decrease. All of this means that stop spacing along a route is central to accessibility, as it is a tradeoff of access (more stops) and geographic coverage (service efficiency through less stops). This paper details modeling approaches for addressing accessibility concerns in an integrated fashion. Bus-based transit service in Columbus, Ohio will be utilized to illustrate the usefulness of these approaches in transit planning. Received: September 2002 / Accepted: January 2003 This research was supported in part by an Ohio State University seed grant.     

Multi‐temporal transport network models for accessibility studies

Vehicle tracking is a spatio‐temporal source of high‐granularity travel time information that can be used for transportation planning. However, it is still a challenge to combine data from heterogeneous sources into a dynamic transport network, while allowing for network modifications over time. This article uses conceptual modeling to develop multi‐temporal transport networks in geographic information systems (GIS) for accessibility studies. The proposed multi‐temporal network enables accessibility studies with different temporal granularities and from any location inside the city, resulting in a flexible tool for transport and urban planning. The implemented network is tested in two case studies that focus on socially excluded people in a large global city, São Paulo, Brazil, including accessibility analyses from slum areas. It explores variations within a day and differences between transport modes across time. Case study results indicate how the accessibility is heterogeneous in low‐income regions.     

基于高分辨率影像的道路交通可达性分析

基于完善的交通规划理论和模型,以某市为例,借助RS技术的空间数据获取能力和GIS技术的空间分析能力,综合考虑最短出行距离、最短出行时间以及网络节点人口密度3个因素,研究分析某市的道路交通可达性,并对现有的道路交通网络进行评价,为未来城市道路交通规划以及城市建设提供科学可靠的参考依据。     

Exploring the link between urban form and work related transportation using combined satellite image and census information: Case of the Great lakes region

Aspects of urban transportation have significant implications for resource consumption and environmental quality. The level of travel activity, the viability of various modes of transportation and hence the level of transportation-related emissions are influenced by the structure of cities, i.e., their urban forms. While it is widely recognized that satellite remote sensing can provide spatial information on urban land cover and land use, its effective use for understanding impacts of urban form on issues such as transportation requires that this information be integrated with relevant demographic information. A comprehensive bi-national urban database, the Great Lakes Urban Survey (GLUS), comprising all cities with populations in excess of 200,000 has been created from Landsat imagery and national census and transportation survey information from Canada and the United States. A suite of analysis tools are proposed to utilize information sets such as GLUS to investigate the link between urban form and work-related travel. A new indicator, the Employment Deficit Measure (EDM), is proposed to quantify the balance between employment and worker availability at different transit horizons and hence to assess the viability of alternate modes of transportation. It is argued that the high degree of residential and commercial/industrial land uses greatly impact travel to work mode options as well as commute distance. A spatial interaction model is developed and found to accurately predict travel distance aggregated at the census tract level. We argue that this model could also be used to explore the relative levels of travel activity associated with different urban forms.     

Incorporating sprawl and adjacency measures in land‐use forecasting model: A case study of Collin County,TX

Sprawl measures have largely been neglected in land‐use forecasting models. The current approach for land‐use allocation using optimization mostly utilizes objective functions and constraints that are non‐spatial in nature. Application of spatial constraints could take care of the contiguity and compactness of land uses and can be utilized to address urban sprawl. Because a land‐use model is used as an input to transportation modeling, a better spatial allocation strategy for more compact land‐use projections will promote better transportation planning and sustainable development. This study formulates a scenario‐based approach to normative modeling of urban sprawl. In doing so, it seeks to improve the land‐use projections by employing a spatial optimization model with contiguity and compactness consideration. This study incorporates urban sprawl measures based on smart growth principles together with a mixed‐use factor, and adjacency consideration of nearby land uses. The objective function used in the study maximizes net suitability based on imposed constraints. These constraints are based on smart growth principles that enhance walkability in neighborhoods, promote better health for residents, and encourage mixed‐use development. The formulated model has been applied to Collin County, TX, a fast‐developing suburban county located to the north of the Dallas–Fort Worth metroplex. The suitability of land cells indicates the probability of conversion, which is calculated using spatial discrete choice analysis with Moran eigenvector spatial filtering for vacant cells at a resolution of 150 × 150 m employing factors of the built environment, and socioeconomic and demographic characteristics. This study demonstrates how spatial proximity between land uses, which has been ignored to date, can be used to control sprawl, resulting in better mixing of different land uses based on constraints imposed in a spatial optimization problem.     

A spatiotemporal analysis of metro-stop based accessibility to bus services in Shanghai,China

Ground-level bus offers flexible services with relatively inexpensive fares and high-level accessibility, thus is the dominant feeder mode for metro in the majority of metropolitan areas in China. Intermodal transfer between the metro and bus networks is therefore a crucial element in the successful operation of an integrated transit system. In this circumstance, a key challenge is lack of appropriate methodologies to evaluate the spatial–temporal disparities of intermodal transfers between metro and bus. To address this issue, this research aims to promote an existing two-step floating catchment area (2SFCA) model by incorporating the temporal variability of service supply, demand, and travel time to provide a more realistic estimation of accessibility using smart card data and automatic vehicle location data. The proposed methodology was applied in a case study of the metropolitan area of Shanghai in the specific context of metro-stop based accessibility to bus services. The results of the case study show that the daily fluctuations in output metro-to-bus transfer accessibility values are highly sensitive to temporal dynamics of transfer time, service supply, and demand. It is hoped the results output here could give planners and policymakers greater insight into spatiotemporal dynamics on transfer accessibility, and help to establish an effective and efficient integrated transit system.     

Estimating the Vehicle‐Miles‐Traveled Implications of Alternative Metropolitan Growth Scenarios: A Boston Example

This study demonstrates the potential value, and difficulties, in utilizing large‐scale, location aware, administrative data together with urban modeling to address current policy issues in a timely fashion. We take advantage of a unique dataset of millions of odometer readings from annual safety inspections of all private passenger vehicles in Metropolitan Boston to estimate the vehicle‐miles‐traveled (VMT) implication of alternative metropolitan growth scenarios: a sprawl‐type “let‐it‐be” scenario and a smart‐growth‐type “winds‐of‐change” scenario. The data are georeferenced to 250 × 250 m grid cells developed by MassGIS. We apply a greedy algorithm to assign Traffic Analysis Zone (TAZ) level household growth projections to grid cells and then use spatial interpolation tools to estimate VMT‐per‐vehicle surfaces for the region. If new growth households have similar VMT behavior as their neighbors, then the let‐it‐be scenario will generate 12–15% more VMT per household compared to the winds‐of‐change scenario. However, even the “wind‐of‐change” scenario, will result in new households averaging higher VMT per household than the Metro Boston average observed in 2005. The implication is that urban growth management can significantly reduce GHG but, by itself, will not be sufficient to achieve the GHG emission reduction targets set by the State for the transportation sector.     

A multi‐modal transportation data‐driven approach to identify urban functional zones: An exploration based on Hangzhou City,China

Recent urban studies have used human mobility data such as taxi trajectories and smartcard data as a complementary way to identify the social functions of land use. However, little work has been conducted to reveal how multi‐modal transportation data impact on this identification process. In our study, we propose a data‐driven approach that addresses the relationships between travel behavior and urban structure: first, multi‐modal transportation data are aggregated to extract explicit statistical features; then, topic modeling methods are applied to transform these explicit statistical features into latent semantic features; and finally, a classification method is used to identify functional zones with similar latent topic distributions. Two 10‐day‐long “big” datasets from the 2,370 bicycle stations of the public bicycle‐sharing system, and up to 9,992 taxi cabs within the core urban area of Hangzhou City, China, as well as point‐of‐interest data are tested to reveal the extent to which different travel modes contribute to the detection and understanding of urban land functions. Our results show that: (1) using latent semantic features delineated from the topic modeling process as the classification input outperforms approaches using explicit statistical features; (2) combining multi‐modal data visibly improves the accuracy and consistency of the identified functional zones; and (3) the proposed data‐driven approach is also capable of identifying mixed land use in the urban space. This work presents a novel attempt to uncover the hidden linkages between urban transportation patterns with urban land use and its functions.     

Transaction‐Based Intelligent Transportation System (TBITS) Using Stochastic User Utility Model

The problem of transportation management has many variables but its solution must be guided by societal needs based on expected benefits and ways of achieving them. Thus transport management can be immensely enhanced and simplified by the use of a geospatial information system. Lagos, the commercial center of Nigeria, has been suffering from traffic congestion for decades. The loss suffered as a result of this congestion cannot be easily quantified economically and socially. This article presents empirical solutions to transportation problems in the Lagos Metropolis using the “Bottom–Top” approach, from “Transaction‐Based” at local government level to “Multimodal” at the metropolitan level. The Stochastic User Utility Model was adopted to estimate the appropriate representation of human heterogeneity, flexibility and variability on mode choice relative to route travel times. The use of Assisted GPS Cameras provides some level of intelligence on the transportation routes. Results obtained include a travel demand survey (household‐based) within a Traffic Zone and Sampled Trip Production/Trip Attraction Analysis based on Modes of Transportation. Geospatial Analysis carried out included Proposed Multimodal Transportation Routes with Transfer Points (TPs) and Incident Facility Management analysis. The synergy of Multimodal and Intelligent Transportation System (MITS) to obtain an integrated Multimodal Transaction‐Based Intelligent Transportation System (MTBITS) will enhance efficient transportation systems for the Lagos Metropolis.     

Evaluation of Land Suitability for Urban Land‐Use Planning: Case Study Dhaka City

The aim of this research is evaluation of land suitability for urban land‐use planning. Four factors and fourteen criteria were selected for suitability analysis and land‐use planning. Factors and criteria were defined based on literature survey, experts’ opinions, local contexts and availability of data. GIS‐based Analytical Hierarchy Process (AHP) was used as a Multi‐criteria Decision Making model. The study was conducted on a selected area of Dhaka city, which is one of the fastest growing mega‐cities of the world. The research result shows that highly suitable area (13%) should be used for urban residential zone; moderately suitable area (35%) should be designated as mixed use zone; low suitable area (42%) should be reserved for agricultural use and open spaces; and not suitable area (10%) should be protected from any types of activities except agriculture. The research approached an urban land‐use planning at a regional scale.     

Trip making, induced travel demand, and accessibility

Traditional transportation planning practice rests on the premise that the demand for transportation is derived. On the other hand, economic theory advances that enhancement to the transportation system leads to lower travel cost and hence to induced demand. Such an argument lends support to the view that the rate at which trips are generated is linked to the ease of making trips to potential destinations. Rather conflicting evidence has so far come out of aggregate trip generation modeling applications. This paper revisits this issue with proper characterization of integral accessibility. Poisson regression models of automobile trip generation by trip purpose are estimated on travel survey data in Minneapolis–St. Paul, MN. Alternative measures of accessibility are tested for statistical significance. Conclusions are drawn on the role of accessibility in trip making and on the comparison of integral accessibility measures.The first author gratefully acknowledges the financial support of NSF grant SBR- 9308394. We are particularly indebted to Rick Gelbmann, Robert Paddock, and Mark Philippi at the Metropolitan Council, Minneapolis–St. Paul, and William Barrett at the Office of Transportation Data Analysis, Minnesota Department of Transportation for their availability to answer all our data-related questions.     

Individual accessibility and distance from major employment centers: An examination using space-time measures

 Distance has often been assumed to be an influence on intraurban accessibility, whether in traditional proximity-based measures of accessibility, or through expectations about distance-minimizing travel behavior and the logic of the monocentric model. This paper examines the importance of distance from major employment centers to individual accessibility in Portland, Oregon, using space-time accessibility measures computed using GIS. The results of this research indicate that distance from these locations has mixed results on individual accessibility. This appears to reflect the importance of time, both the time of day activities are scheduled as well as time constraints, to individual activity patterns. Received: September 2002 / Accepted: January 2003 The author gratefully acknowledges the contributions of two anonymous reviewers, whose comments greatly improved the content of this paper     

高分辨率PS-InSAR在轨道交通形变特征探测中的应用

为了确保城市轨道交通的安全运营和可持续发展,将高分辨率PS-InSAR技术引入城市轨道交通的形变监测领域。以上海为例,分析了城市轨道交通网络专题的形变特征。首先,利用26景TerraSAR-X影像在上海开展高分辨率PS-InSAR沉降精细测量,得到轨道交通网络整体的沉降格局;然后,针对不同建成时期和建设形式的路段,分类探讨其形变特性及原因;最后,进行测量结果的精度验证。分析结果表明,快速的城市化发展建设已成为上海轨道交通沿线主要的沉降原因;不同建成时期和建设形式的路段表现出不同的形变特征,早期建设路段比晚期建设路段更稳定,高架路段比地下路段沉降速率更小;PS-InSAR与水准数据保持很好的一致性。证实了高分辨率PS-InSAR技术在城市轨道交通形变监测、管理维护和预警方面具有一定的可行性,可以为城市公共交通的规划和建设提供决策支持。通形变监测、管理维护和预警方面具有一定的可行性,可以为城市公共交通的规划和建设提供决策支持。     

Assessing the effect of temporal dynamics on urban growth simulation: Towards an asynchronous cellular automata

Time is a fundamental dimension in urban dynamics, but the effect of various definitions of time on urban growth models has rarely been evaluated. In urban growth models such as cellular automata (CA), time has typically been defined as a sequence of discrete time steps. However, most urban growth processes such as land‐use changes are asynchronous. The aim of this study is to examine the effect of various temporal dynamics scenarios on urban growth simulation, in terms of urban land‐use planning, and to introduce an asynchronous parcel‐based cellular automata (AParCA) model. In this study, eight different scenarios were generated to investigate the impact of temporal dynamics on CA‐based urban growth models, and their outputs were evaluated using various urban planning indicators. The obtained results show that different degrees of temporal dynamics lead to various patterns appearing in urban growth CA models, and the application of asynchronous (event‐driven) CA models achieves better simulation results than synchronous models.     

Spatio‐temporal land use multi‐objective optimization: A case study in Central China

Much effort has been applied to the study of land use multi‐objective optimization. However, most of these studies have focused on the final land use scenarios in the projected year, without considering how to reach the final optimized land use scenario. To fill this gap, a spatio‐temporal land use multi‐objective optimization (STLU‐MOO) model is innovatively proposed in this research to determine possible spatial land use solutions over time. The STLU‐MOO is an extension of a genetic land use multi‐objective optimization model (LU‐MOO) in which the LU‐MOO is generally carried out in different years, and the solutions at year T will affect the solutions at year T + 1. We used the Wuhan agglomeration (WHA) as our case study area. The STLU‐MOO model was employed separately for the nine cities in the WHA, and social, economic, and environmental objectives have been considered. The success of the experiments in the case study demonstrated the value and novelty of our proposed STLU‐MOO model. In addition, the results also indicated that the objectives considered in the case study were in conflict. According to the results, the optimal land use plan in 2050 can be traced back to 2040, 2030, and 2020, providing a series of Pareto solutions over the years which can provide spatio‐temporal land use multi‐objective optimization solutions to support the land use planning process.     

USE OF TRANSFORMED CARTOGRAPHIC IMAGES IN URBAN CONSTRUCTION STUDIES

The authors describe how maps compiled according to non-spatial “metrics” or systems of scaling can be used in the support of urban planning and construction efforts. In particular, maps scaled according to travel time instead of ordinary distance reveal inadequacies not only in urban mass transit, but permit assessment of the rationality of urban land use as a whole, by demonstrating the degree of effort that urban residents must expend to perform such basic activities as shopping, the journey to work, and access to essential services. A methodology for the compilation of such maps is described. Translated from: Izvestiya AN SSSR, seriya geograficheskaya, 1987, No. 1, pp. 100-105.