461 research outputs found
A geospatial approach of downscaling urban energy consumption density in mega-city Dhaka, Bangladesh
Lack of energy consumption data limits resource optimized urban structure and energy planning in developing countries like Bangladesh. Focusing on mega-city Dhaka as a case, this study applies a geospatial approach of using multi-source national and regional datasets and visual analytics to downscale and estimate energy consumption at a local scale (such as ward and gridcell). The energy consumption density (ECD), as a measure of end energy use in a unit area, was estimated and mapped by linking building floorspace data with residentsâ energy use indicators such as per capita energy consumption, household energy expenditure, and mobility (transportation) pattern. This study also evaluated the ECD modelling outputs, and their sensitivity to distance from central business district (CBD) and total building floorspace. Results found a positive correlation between the residential building floorspace and estimated ECD. Regression and sensitivity analysis also identified and mapped significant spatial clusters and outliers in estimated ECD pattern of Dhaka city. This approach and methodology could help similar cities in other developing countries adopt and implement energy focused urban development.Note: Open access after passing embargo period 24 month
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Updating the PECAS Modeling Framework to Include Energy Use Data for Buildings
This study investigates the consumption of electricity and natural gas for building operations for several categories of residential and non-residential buildings. The study updates the Production Exchange Consumption Allocation System (PECAS) land use modeling framework to include energy components. An energy database was assembled to study energy consumption in buildings. The authors conducted statistical analysis of utility data and estimated linear regression models to predict energy consumption in buildings. Results are validated using data from independent sources, including the California Residential Appliance Saturation Study (RASS) and the Commercial End-Use Survey (CEUS). Results are used to update PECAS and form part of the baseline study to estimate energy and greenhouse gas balances in an urban metabolism framework for the analysis of the environmental impacts of complex urban regions. The results also allow the total energy consumption and greenhouse gas emissions for residential and commercial building operations to be estimated through the application to the total residential and commercial building inventory in the region. These results are then useful for the evaluation of possible energy savings in buildings
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Economic impacts of alternative greenspace configurations in fast growing cities: The case of Greater Beijing
Greenspaces at the city scale, like greenbelts, green-wedges or green-grids, have become well-known instruments for shaping urban economic activity and land use. The economic impacts of such instruments are complex and hard to measure. This article addresses one of the rarely studied problems of measuring the economic impacts of alternative greenspace configurations in fast growing cities. In such cities, there is an uncertain basis for making such greenspace related decisions, for example the assumptions about the citiesâ total population and economic activity. Decision makers have few tools to measure and predict the potential economic costs and benefits of alternative greenspace configurations. We present a new model that allows tracking over time of both non-divisible land use decisions and a multitude of gradual adaptations made by businesses and consumers. The model is applied to Greater Beijing, one of the fast growing cities that is actively exploring alternative greenspace configurations to control urban expansion. The modelling results suggest that compared with the trend-development scenario of no greenspace intervention, a strict greenbelt would decrease the overall consumer surplus in Beijing by US3.6 billion per year in 2030. The adaptive configuration also reduces car journeys by 11% in Beijing. More generally, modelling results show that a flexible design of strategic greenspaces and careful siting of new development around metro stations within the designated greenspaces could benefit consumers and promote sustainable travel. </jats:p
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What if Beijing had enforced the 1st or 2nd greenbelt? â Analyses from an economic perspective
Many fast growing cities have designated greenbelts but have failed to maintain them. This is often attributed to weak planning regulations, but there is little understanding of the underlying impacts of greenbelts on the interactions among land use control, transport supply and economic activities. This paper presents a counterfactual analytical model to examine the greenbeltsâ impacts on consumersâ utility, producersâ productivity, and their locational choices. The model establishes historic-what-if scenarios and compares what historically happened with what could have happened under alternative levels of greenbelt interventions. The model is applied to Beijing, which intended to establish two greenbelts in 1994, but large parts of the greenbelts have disappeared under fast urban expansion. The model compares the economic impacts of the greenbelts as they stood with hypothetical fully-enforced greenbelts and no-greenbelt scenarios from 1990 to 2010. The modelling results show that the two greenbelts, if fully enforced, would have decreased consumer surplus by $202 million in Beijing in 2010. To fulfil the policy aim of decentralisation, transport improvements between the city and new towns are crucial. For a more effective implementation of greenbelts in the future, development constraints could be carefully removed from non-ecologically sensitive sites which are served with good transport conditions.Cambridge Overseas Trust
China Scholarship Council
special fund of Key Laboratory of Eco Planning & Green Building, Ministry of Education (Tsinghua University), China
Capco Future Cities Fellowship, Cambridge Real Estate Research
Centre
The Cambridge-UC Berkeley-National University of Singapore University Alliance project âSmart Design
A knowledge discovery approach to urban analysis
Enhancing our knowledge of the complexities of cities in order to empower ourselves to make more informed decisions has always been a challenge for urban research. Recent developments in large-scale computing, together with the new techniques and automated tools for data collection and analysis are opening up promising opportunities for addressing this problem. The main motivation that served as the driving force behind this research is how these developments may contribute to urban data analysis. On this basis, the thesis focuses on urban data analysis in order to search for findings that can enhance our knowledge of urban environments, using the generic process of knowledge discovery using data mining. A knowledge discovery process based on data mining is a fully automated or semi-automated process which involves the application of computational tools and techniques to explore the âpreviously unknown, and potentially useful informationâ (Witten & Frank, 2005) hidden in large and often complex and multi-dimensional databases. This information can be obtained in the form of correlations amongst variables, data groupings (classes and clusters) or more complex hypotheses (probabilistic rules of co-occurrence, performance vectors of prediction models etc.). This research targets researchers and practitioners working in the field of urban studies who are interested in quantitative/ computational approaches to urban data analysis and specifically aims to engage the interest of architects, urban designers and planners who do not have a background in statistics or in using data mining methods in their work.
Accordingly, the overall aim of the thesis is the development of a knowledge discovery approach to urban analysis; a domain-specific adaptation of the generic process of knowledge discovery using data mining enabling the analyst to discover ârelational urban knowledgeâ. âRelational urban knowledgeâ is a term employed in this thesis to refer to the potentially âusefulâ and/or âvaluableâ information patterns and relationships that can be discovered in urban databases by applying data mining algorithms. A knowledge discovery approach to urban analysis through data mining can help us to understand site-specific characteristics of urban environments in a more profound and useful way.
On a more specific level, the thesis aims towards âknowledge discoveryâ in traditional thematic maps published in 2008 by the Istanbul Metropolitan Municipality as a basis of the Master Plan for the BeyoÄlu Preservation Area. These thematic maps, which represent urban components, namely buildings, streets, neighbourhoods and their various attributes such as floor space use of the buildings, land price, population density or historical importance, do not really extend our knowledge of BeyoÄlu Preservation Area beyond documenting its current state and do not contribute to the interventions presented in the master plan. However it is likely that âusefulâ and âvaluableâ information patterns discoverable using data mining algorithms are hidden in them.
In accordance with the stated aims, three research questions of the thesis concerns (1) the development of a general process model to adapt the generic process of knowledge discovery using data mining for urban data analysis, (2) the investigation of information patterns and relationships that can be extracted from the traditional thematic maps of the BeyoÄlu Preservation Area by further developing and implementing this model and (3) the investigation of how could this ârelational urban knowledgeâ support architects, urban designers or urban planners whilst developing intervention proposals for urban regeneration.
A Knowledge Discovery Process Model (KDPM) for urban analysis was developed, as an answer to the the first research question. The KDPM for urban analysis is a domain-specific adaptation of the widely accepted process of knowledge discovery in databases defined by Fayyad, Piatetsky-Shapiro, and Smyth (1996b). The model describes a semi-automated process of database formulation, analysis and evaluation for extracting information patterns and relationships from raw data by combining both GIS and data mining functionalities in a complementary way. The KDPM for urban analysis suggests that GIS functionalities can be used to formulate a database, and GIS and data mining can complement each other in analyzing the database and evaluating the outcomes. The model illustrates that the output of a GIS platform can become the input for a data mining platform and vice versa, resulting in an interlinked analytical process which allows for a more sophisticated analysis of urban data.
To investigate the second and third research questions, firstly the KDPM for urban analysis was further developed to construct a GIS database of the BeyoÄlu Preservation Area from the thematic maps. Then, three implementations were performed using this GIS database; the BeyoÄlu Preservation Area Building Features Database consisting of multiple features attributed to the buildings. In Implementation (1), the KDPM for urban analysis was used to investigate a variety of patterns and relationships that can be extracted from the database using three different data mining methods. In Implementations (2) and (3), the KDPM for urban analysis was implemented to test how the knowledge discovery approach through data mining proposed in this thesis can assist in developing draft plans for the regeneration of a run-down neighbourhood in the BeyoÄlu Preservation Area (TarlabaĹÄą). In Implementation (2), the KDPM for urban analysis is implemented in combination with an evolutionary process to apply a regeneration approach developed by the author; a computational process which generates draft plans for ground floor use, user-profile and tenure-type allocation was developed. In Implementation (3), students applied the KDPM for urban analysis during the course of an international workshop. The model enabled them to explore site-specific particularities of TarlabaĹÄą that would support their urban intervention proposals.
Among the outputs of the thesis three of them are considered as utilizable outputs that distinguish this thesis from previous studies:
The KDPM for urban analysis.
Although there have been other studies which make use of data mining methods and techniques combined with GIS technology, to the best of our knowledge no previous research has implemented a process model to depict this process and used the model to extract âknowledgeâ from traditional thematic maps. Researchers and practitioners can re-use this process model to analyze other urban environments. The KDPM for urban analysis is, therefore, one of the main utilizable outputs of the thesis and an important scientific contribution of this study.
The BeyoÄlu Preservation Area Building Features Database.
A large and quite comprehensive GIS database which consists of 45 spatial and non-spatial features attributed to the 11,984 buildings located in the BeyoÄlu Preservation Area was constructed. This database is one of the original features of this study. To the best of our knowledge, there are no other examples of applications of data mining using such a comprehensive GIS database, constructed from a range of actual micro-scale data representing such a variety of features attributed to the buildings. This database can be re-used by analysts interested in studying the BeyoÄlu Preservation Area. The BeyoÄlu Preservation Area Building Features Database is therefore one of the main utilizable outputs of the thesis and represents a scientific contribution to the research material on the BeyoÄlu Preservation Area.
A computational process which generates draft plans for ground floor use, user-profile and tenure-type allocation, using GIS and data mining functionalities with evolutionary computation.
This output of the thesis was generated by Implementation (2), which aimed to investigate Research Question (3). The overall process involved the successive application of NaĂŻve Bayes Classification, Association Rule Analysis and an Evolutionary Algorithm to a subset of the BeyoÄlu Preservation Area Building Features Database representing the TarlabaĹÄą neighbourhood. Briefly, the findings of the data mining analysis were used to formulate a set of rules for assigning ground floor use information to the buildings. These rules were then used for fitness measurements of an Evolutionary Algorithm, together with other fitness measurements for assigning user-profile and tenure-type information (defined by the author according to the regeneration approach developed by the author). As a result, the algorithm transformed the existing allocation of the ground floor use in the buildings located in TarlabaĹÄą in accordance with the given rules and assigned user-profile and tenure type information for each building. This computational process demonstrated one way to use the data mining analysis findings in developing intervention proposals for urban regeneration. A similar computational process can be implemented in other urban contexts by researchers and practitioners. To the best of our knowledge, no prior research has used data mining analysis findings for fitness measurements of an Evolutionary Algorithm in order to produce draft plans for ground floor use, user-profile and tenure-type allocation. This is, therefore, the most original scientific contribution and utilizable output of the thesis.
As a result of the research, on the basis of the data that is available in the thematic maps of the BeyoÄlu Preservation Area, the potential of a knowledge discovery approach to urban analysis in revealing the relationships between various components of urban environments and their various attributes is demonstrated. It is also demonstrated that these relationships can reveal site-specific characteristics of urban environments and if found âvaluableâ by the the targeted researchers and practitioners, these can lead to the development of more informed intervention proposals. Thereby the knowledge discovery approach to urban analysis developed in this thesis may help to improve the quality of urban intervention proposals and consequently the quality of built environments. On the other hand, the implementations carried out in the thesis also exposed the major limitation of the knowledge discovery approach to urban analysis through data mining, which is the fact that the findings discoverable by this approach are limited by the relevant data that is collectable and accessible
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Towards a spatial energy model: A theoretical comparison of accessibility and energy-use in regional settlement patterns
The research reported is a theoretical investigation of the interaction of land-use and transport in relation to the use of energy. Of particular interest is the relationship between the spatial arrangement of settlements and the use of energy within them for both transport and building services.
The literature of scenarios of energy futures is reviewed, and three scenarios of future constraints on regional planning are adopted. The adopted scenarios emphasise constraints imposed by energy policy and the availability of fuels; they form the background to the comparison of a number of theoretical regional settlement patterns, in terms of their implications for land-use and their potential for fuel-conservation.
A study of an existing regional settlement pattern is used in combination with published land-use data as the basis of a configurational model. This model is intended to characterise the real pattern spatially, quantitatively and in a manner suitable for experimental manipulation. The model encompasses the pattern of developed land (disaggregated by uses), the shape of the transport network, and the intensity of development (in terms of population and floorspace).
A review is then made of published proposals for energy-efficient settlements, which are found to include concentrated, dispersed, nucleated and linear patterns. Five modified versions of the regional configurational model are then constructed in order to characterise the range of realistic possibilities for future regional form which might result from the fuel-conservation policies inherent in the proposals reviewed.
The five regional configurations and the original pattern are then compared by means of a specially-developed land-use transport and energy-evaluation model. The comparison is made in terms of the accessibility of the population in each pattern to employment and services (measured 'biy the model as "benefits"), and. in terms of the use of fuel in both transport and domestic space heating. Fuel use in transport is related to modal split and vehicle speed; fuel use in homes is related to dwelling size and location. Parametric calibration of the land-use and transport models allows the comparison of the patterns to be repeated in the context of each of the three adopted energy scenarios, taking into account changes in travelling behaviour, vehicle efficiencies, and building services technologies.
The results of the comparison are discussed and assessed in terms of their implications for long-term strategic planning policy
An econometric analysis of Shanghai office rents
The modern commercial office market in Shanghai emerged with Chinaâs economic reform and open door policy in the 1980s and grew rapidly at the beginning of 1990s,with increasing demand for office space from foreign and domestic occupiers. Though total real estate investment is skewed towards residential property, office investment has grown by 23% per annual in terms of value and by 24% per annum in terms of completed floor space from 1995 to 2007. The Shanghai office market is of importance for a number of reasons. First, it is one of the largest office markets in China in terms of square footage and in investment terms. Second, the office market is one of most established ones in China and attracts most attention from policy makers, investors, practitioners and academia. However, so far there is little empirical research on the Shanghai office market. This paper will use econometric modelling techniques to investigate office rent determination of the CBD in the central Puxi area, Shanghai, over the period 1991 â2007. Using a reduced form modelling specification in an error correction framework based on demand and supply interactions, GDP and office stock are found to significantly affect office rental performance in the Shanghai market in the long run. The model also shows that the office market adjusts to equilibrium. This model is then extended to test the impact of foreign direct investment, real interest rates, and vacancy rates on rental determination
Areas, nodes and networks: Some analytical considerations
In spatial interaction modelling, trips between origins and destinations within the same areal zone have a predominant influence on both the value of the gravity parameter and on the associated pattern of flows. Despite this, the relevant highly sensitive intrazonal impedance values are usually based on approximate average intrazonal distances or times. This situation has been identified in the literature as the ?self potential? problem. In this paper, integration over continuous space within the origin destination zones is applied to not only compute the intrazonal flows more accurately, but also to determine their influence on calibration of the value of the gravity parameter itself. In addition, whereas all trips are assumed to have destinations corresponding to nodes of the transport network, interzonal trips, starting from dispersed origins, are assigned shortest path routes to join the interzonal links at efficient intermediate points. In the analysis, further approximations incurred in evaluation of the sets of origin/destination flows between contiguous zones are also identified. The eventual aim is to develop practical ?rules of thumb? for correcting the conventional analysis. Flows between areal zones and facility nodes may occur along several plausible alternative paths, rather than via one abstract ?interzonal? path, as usually considered in conventional spatial interaction models. Such destination/route choice is easy to handle in the relatively uncongested conditions characterizing off-peak discretionary travel. This paper examines facility choice via alternative routes, as well as attempting to discern the influence of ?intervening opportunities?. It is indicated how intervening opportunities may influence discretionary travel positively, in contrast to their identified negative influence on the probability of choosing the final destination in journey to work travel. Such intervening opportunities can only be considered meaningfully along the alternative paths of the actual network, as specified above.
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