Spatial rules that generate urban patterns: Emergence of the power law in the distribution of axial line length

Rezayan, Hani; Delavar, Mahmoud Reza; Frank, Andrew U.; Mansouri, Alireza

doi:10.1016/j.jag.2010.04.003

Cited by 7 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It will facilitate the prediction and management of urban sprawl [75–77] and push forward sustainable urban planning in not just the developed world, but also the developing countries as they catch on with the technologies [46,49]. The technical and hence the perceived barriers to similar topics of research are taken down thanks to the facts that the data here is the “worst” case scenario that one can have for a similar project and that the workflow was developed for a diverse community ranging from engineers, spatial analyst to urban and social planners.…”

Section: Discussion and Future Workmentioning

confidence: 99%

“…This study extended the argument made by Sunak & Madener [ 39 ] and Manfren et al [ 73 ] on the shifting paradigm and confirmed the vision by such authors as Buchanan & Brussel [ 74 ] and Brenner [ 24 ]: remote sensing will play an important role not just in the paradigm shift of urban energy, but in urban planning as a whole. It will facilitate the prediction and management of urban sprawl [ 75 – 77 ] and push forward sustainable urban planning in not just the developed world, but also the developing countries as they catch on with the technologies [ 46 , 49 ]. The technical and hence the perceived barriers to similar topics of research are taken down thanks to the facts that the data here is the “worst” case scenario that one can have for a similar project and that the workflow was developed for a diverse community ranging from engineers, spatial analyst to urban and social planners.…”

Section: Discussion and Future Workmentioning

confidence: 99%

See 1 more Smart Citation

The Application of LiDAR to Assessment of Rooftop Solar Photovoltaic Deployment Potential in a Municipal District Unit

Nguyên

Pearce

Harrap

et al. 2012

Sensors

View full text Add to dashboard Cite

A methodology is provided for the application of Light Detection and Ranging (LiDAR) to automated solar photovoltaic (PV) deployment analysis on the regional scale. Challenges in urban information extraction and management for solar PV deployment assessment are determined and quantitative solutions are offered. This paper provides the following contributions: (i) a methodology that is consistent with recommendations from existing literature advocating the integration of cross-disciplinary competences in remote sensing (RS), GIS, computer vision and urban environmental studies; (ii) a robust methodology that can work with low-resolution, incomprehensive data and reconstruct vegetation and building separately, but concurrently; (iii) recommendations for future generation of software. A case study is presented as an example of the methodology. Experience from the case study such as the trade-off between time consumption and data quality are discussed to highlight a need for connectivity between demographic information, electrical engineering schemes and GIS and a typical factor of solar useful roofs extracted per method. Finally, conclusions are developed to provide a final methodology to extract the most useful information from the lowest resolution and least comprehensive data to provide solar electric assessments over large areas, which can be adapted anywhere in the world.

show abstract

Section: Discussion and Future Workmentioning

confidence: 99%

Section: Discussion and Future Workmentioning

confidence: 99%

The Application of LiDAR to Assessment of Rooftop Solar Photovoltaic Deployment Potential in a Municipal District Unit

Nguyên

Pearce

Harrap

et al. 2012

Sensors

View full text Add to dashboard Cite

show abstract

“…As identified in the spatial analysis of urban growth, spatial variables adopted in CA models should closely relate to urban development and land use changes (Rezayan et al 2010;Stanilov and Batty 2011;Wu and Webster 1998). With regard to spatial variables used in the MachCA model, some of them (e.g.…”

Section: Input Datamentioning

confidence: 99%

Modeling urban growth with GIS based cellular automata and least squares SVM rules: a case study in Qingpu–Songjiang area of Shanghai, China

Feng

Liu

Batty

2015

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

A critical issue in urban cellular automata (CA) modeling concerns the identification of transition rules that generate realistic urban land use patterns. Recent studies have demonstrated that linear methods cannot sufficiently delineate the extraordinary complex boundaries between urban and non-urban areas and as most urban CA models simulate transitions across these boundaries, there is an urgent need for good methods to facilitate such delineations. This paper presents a machine learning CA model (termed MachCA) with nonlinear transition rules based on least squares support vector machines (LS-SVM) to simulate such urban growth. By projecting the input dataset into a high dimensional space using the LS-SVM method, an optimal hyper-plane is constructed to separate the complex boundaries between urban and nonurban land, thus enabling the retrieval of nonlinear CA transition rules. In the MachCA model, the transition rules are yes-no decisions on whether a cell changes its state or not, the rules being dynamically updated for each iteration of the model implementation. The application of the MachCA for simulating urban growth in the Shanghai QingpuSongjiang area in China reveals that the spatial configurations of rural-urban patterns can be modeled. A comparison of the MachCA model with a conventional CA model fitted by logarithmic regression (termed LogCA) shows that the MachCA model produces more hits and less misses and false alarms due to its capability for capturing the spatial complexity of urban dynamics. This results in improved simulation accuracies, although with only less than 1 % deviation between the overall errors produced by the MachCA and LogCA models. Nevertheless, the way MachCA model use in retrieving the transition rules provides a new method for simulating the dynamic process of urban growth.

show abstract

From Simulation to Implementation: Practical Advice for Policy Makers Who Want to Use Computer Modeling as an Analysis and Communication Tool

Félix

Castañón–Puga

2019

Applied Decision-Making

View full text Add to dashboard Cite

Spatial rules that generate urban patterns: Emergence of the power law in the distribution of axial line length

Cited by 7 publications

References 11 publications

The Application of LiDAR to Assessment of Rooftop Solar Photovoltaic Deployment Potential in a Municipal District Unit

The Application of LiDAR to Assessment of Rooftop Solar Photovoltaic Deployment Potential in a Municipal District Unit

Modeling urban growth with GIS based cellular automata and least squares SVM rules: a case study in Qingpu–Songjiang area of Shanghai, China

From Simulation to Implementation: Practical Advice for Policy Makers Who Want to Use Computer Modeling as an Analysis and Communication Tool

Contact Info

Product

Resources

About