High-speed rail in the United States: accessibility potential and spatial equity

There is renewed interest in developing high-speed intercity passenger rail (HSIPR) in the United States, revitalizing a transport mode that has long since lost most intercity travelers to competing modes of transportation such as automobile and airplane. For the construction of an HSIPR network to be successful, it is important to understand the locational benefits and disparities associated with this proposed network. This dissertation examines the potential impact of HSIPR in the United States using accessibility and equity measures at both the national and local scales with three broad goals: (1) project the impact of HSIPR in the United States using location-based accessibility measures at a national scale, (2) evaluate the locational effect of both the current railway upgrade plans and the full HSIPR plan along the southeast corridor of the United States, and (3) assess the spatial patterns of multimodal accessibility at the census-tract level via different intercity travel modes, using a social-equity perspective in the case of seven metropolitan statistical areas along the Southeast HSR corridor of North Carolina. Unlike most past research, accessibility to HSIPR is measured using a multimodal transportation network in ArcGIS through a combination of road, railway, and air travel, considering access/egress time to/from train stations or airports as well as waiting and transfer times. Overall, the findings of this dissertation suggest that HSIPR will significantly lead to nationwide and local accessibility gains, and it will contribute to lessening the spatial disparity of accessibility with intercity travel both from the perspectives of personal travel and economic development. While the highest travel-time accessibility gains will go to the central and eastern United States, the largest economic-potential accessibility gain is expected in the cities along the northeast rail corridor. The faster HSIPR service will compete with air mode by 34.3% more than current, specifically in the areas that are reachable within five hours by train. At the regional scale, there will be overall accessibility gains in the Southeast corridor from the upgraded speed of HSIPR, with more benefits concentrated in cities where the trains will stop, such as Raleigh, Greensboro, Charlotte in North Carolina and Greenville, South Carolina. However, a tract-level accessibility analysis reveals that the accessibility gains will be concentrated only in specific parts of a city, with the highest concentration found near rail station areas of Raleigh and Durham, North Carolina, Greenville, South Carolina, and Richmond, Virginia. It is expected that cities along the Southeast corridor will experience improved spatial equity, but the accessibility gap between cities with and cities off the HSIPR system remains. This suggests that upgrading regional intrastate transportation will be necessary to more equally distribute the accessibility benefits from HSR cities to non-HSR cities. Most census tracts in the Southeast will gain spatial equity, but less-accessible areas will receive greater benefits. While both the high- and low-income groups show better accessibility equity from all modes of transportation after completion of HSIPR in the Southeast region, the middle-income group will have less-accessibility equity. This may be a result of the scattered residential locations of the middle-income group compared to the centrally located populations of the high and low-income groups

Reflections and speculations on the progress in Geographic Information Systems (GIS): a geographic perspective

Great strides have been made in Geographic Information Systems (GIS) research over the past half-century. However, this progress has created both opportunities and challenges. From a geographic perspective, certain challenges remain, including the modelling of geographic-featured environments with GIS data model, the enhancement of GIS’s analysis functions for comprehensive geographic analysis and achieving human-oriented geographic information presentation. Several basic theoretical and technical ideas that follow the workflow and processes of geographic information induction, geographic scenario modelling, geographic process analysis and geographic environment representation are proposed to fill the gaps between GIS and geography. We also call for designing methods for big geographic data-oriented analysis, making best use of videos and developing virtual geographic scenario-based GIS for further evolution

Recent Progress in Urbanisation Dynamics Research

This book is dedicated to urbanization, which is observed every day, as well as the methods and techniques of monitoring and analyzing this phenomenon. In the 21st century, urbanization has gained momentum, and the awareness of the significance and influence of this phenomenon on our lives make us take a closer look at it not only with curiosity, but also great attention. There are numerous reasons for this, among which the economy is of special significance, but it also has many results, namely, economic, social, and environmental. First of all, it is a spatial phenomenon, as all of the aspects can be placed in space. We would therefore like to draw special attention to the results of urbanization seen on the Earth's surface and in the surrounding space. The urbanization–land relation seems obvious, but is also interesting and multi-layered. The development of science and technology provides a lot of new tools for observing urbanization, as well as the analyses and inference of the phenomenon in space. This book is devoted to in-depth analysis of past, present and future urbanization processes all over the world. We present the latest trends of research that use experience in the widely understood geography of the area. This book is focused on multidisciplinary phenomenon, i.e., urbanization, with the use of the satellite and photogrammetric observation technologies and GIS analyses

Data integration for urban transport planning

Urban transport planning aims at balancing conflicting challenges by promoting more efficient transport systems while reducing negative impacts. The availability of better and more reliable data has not only stimulated new planning methodologies, but also created challenges for efficient data management and data integration. The major focus of this study is to improve methodologies for representing and integrating multi-source and multi-format urban transport data. This research approaches the issue of data integration based on the classification of urban transport data both from a functional and a representational perspective. The functional perspective considers characteristics of the urban transport system and planning requirements, and categorises data into supply, demand, performance and impact. The representational perspective considers transport data in terms of their spatial and non-spatial characteristics that are important for data representation. These two perspectives correspond to institutional and methodological data integration respectively, and are the foundation of transport data integration. This research is based on the city of Wuhan in China. The methodological issues of transport data integration are based on the representational perspective. A framework for data integration has been put forward, in which spatial data are classified as point, linear and areal types, and the non-spatial data are sorted out as values and temporal attributes. This research has respectively probed the integration of point, linear and areal transport data within a GIS environment. The locations of socio-economic activities are point-type data that need to be spatially referenced. A location referencing process requires a referencing base, source address units and referencing methods. The referencing base consists of such spatial features as streets, street addresses, points of interest and publicly known zones. These referencing bases have different levels of spatial preciseness and have to be kept in a hierarchy. Source addresses in Chinese cities are usually written as one sentence, which has to be divided into address units for automatic geo-coding. As it is difficult to separate from the sentences, the address units have to be clearly identified in survey forms. Depending on the types of address units, the referencing process makes use of either semantic name matching or address matching to link source addresses to features in the referencing base. The name-based and road-based referencing schemes constitute a comprehensive location referencing framework that is applicable to Chinese cities. The relationship between two sets of linear features can be identified with spatial overlay in the case of independent representation, or with internal linkage in a dependent representation. The bus line is such a feature that runs on the street network and can be dependently referenced by streets. In the heavily bus-oriented city of Wuhan, bus lines constitute a large public transit network that is important to transport planning and management. This research has extended conventional bus line representation to a more detailed level. Each bus line has been differentiated as two directional routes that are defined separately with reference to the street network. Accordingly, individual route stops are also represented in the database. These stop sites are spatial features with geometry that are linked to street segments and bus routes by linear location referencing methods. A data model linking base street network, bus lines and routes, line and route stops, and other bus operations data has been constructed. The benefits of the detailed model have been demonstrated in several transport applications. Zonal data transitions include three types of operations, i.e. aggregation, areal interpolation and disaggregation. This study focuses on disaggregating data from larger zones to smaller zones. In the context of Wuhan, zonal data disaggregation involves the allocation of statistical data from statistical units to smaller parcels. Given the availability of land use data, a weighted approach reflecting spatial variations has been applied in the disaggregation process. Two technical processes for disaggregation have been examined. Weighted area-weighting (WAW) is an adaptation of the classic area-weighting method, and Monte Carlo simulation (MC) is a stochastic process based on a raster data model. The MC outcome is more convenient for subsequent re-aggregation, and is also directly available for micro-simulation. An important contribution arising from this zonal integration study is that two standardised disaggregation tools have been developed within a GIS environment. The research has also explored the institutional aspect of data integration. The findings of this study show that there is generally a good institutional transport structure in the city of Wuhan and that there is also a growing awareness of using information technology. Professional cooperation exists among transport organisations, but not yet at a level for data sharing. An integrated data support framework requires data sharing. In such a framework, it should be possible to know where to get data for specific transport studies, or which kind of research an institution supports

Impact of land use and land cover change on land surface temperature in Iskandar Malaysia using remote sensing technique

Iskandar Malaysia is one of the impressive development projects ever undertaken in Malaysia that has been experiencing rapid rate of land use change since 2006. Land use change is due to the urban expansion and reduction in natural green areas resulted from enhanced economic growth. The three objectives of this study are (i) to estimate the land use and land cover changes (LULC) in Iskandar Malaysia from 1989 to 2014, (ii) to investigate the effect of LULC changes on land surface temperature (LST) change in the study area and (iii) to predict the LST by 2025. Remote sensing data namely Landsat (Landsat 5, 7 and 8) and Moderate Resolution Imaging Spectroradiometer (MODIS) of Terra product (MOD11A1) were used to classify various LULC and to calculate the LST in Iskandar Malaysia. There are two digital classification techniques used to classify and test the different LULC in this study area. Maximum Likelihood Classification (MLC) technique provided higher accuracies compared to the Support Vector Machine (SVM) technique. Consequently, the classified satellite images using the MLC technique were used to monitor changes in LULC in Iskandar Malaysia. LST was extracted using mono window. The mean LST using Geographic Information System (GIS) analysis according to LULC shows that water areas recorded the highest night time LST value, while forest recorded the lowest day time LST value. Urban areas are the warmest land use during the day and the second warmest land use during the night time. Moreover, the weighted average used to predict the mean LST of entire Iskandar Malaysia, it was found that if green space increases LST value would decrease by 0.5○C. To predict the effect of LULC changes on mean LST of each LULC types linear curve fitting model was used. According to the results, the mean night LST from 2000 to 2025 will increase in Iskandar Malaysia as urban (20.89°C to 22.39°C±0.45), mangrove (20.88°C to 22.59°C±0.50), forest (20.39°C to 21.04°C±0.18), oil palm (20.39°C to 21.25±0.25), rubber (20.34°C to 22.36°C ± 0.57), and water (21.61 °C to 23.31°C ± 0.51). The results show increment in day time at urban (29.26°C to 32.78°C±1.07), mangrove (26.23°C to 28.82 °C±0.89), forest (25.76°C to 27.54°C±0.49), oil palm (27.02°C to 29.54±0.70), rubber (26.49°C to 27.24°C ±0.29), and water (26.10 °C to 28.77 °C ± 0.8) respectively. Moreover, the relationship between LST and several impervious and vegetation indexes show that there is a strong relationship between impervious indexes and LST, and an inverse relationship between vegetation indexes and LST. Finally, this study concluded that replacing green natural area with improvise surface can increase the land surface temperature and have negative effect on urban thermal comfort

HISTORY URBANISM RESILIENCE VOLUME 03:

The 17th conference (2016, Delft) of the International Planning History Society (IPHS) and its proceedings place presentations from different continents and on varied topics side by side, providing insight into state-of-the art research in the field of planning history and offering a glimpse of new approaches, themes, papers and books to come. VOLUME 03: Change and Responsive Plannin

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity