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Entropy for Sustainable and Resilient Urban Future

A special issue of Entropy (ISSN 1099-4300).

Deadline for manuscript submissions: closed (30 September 2016) | Viewed by 37377

Special Issue Editors


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Guest Editor
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Interests: ecosystem services; geographical information systems; remote sensing; spatial modelling; land use and land cover change; urban planning
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Guest Editor
Tomsk State University, 634050 Tomsk, Russia
Interests: advanced data processing; spatial big data analytics; spatial data mining

Special Issue Information

Dear Colleagues,

Cities are extremely complex systems resulting from the combination of multiple complex systems, organized to provide better conditions for human development. Information Theory offers a very suitable framework to access and monitor the sustainability and resilience of complex systems.

From the Information Theory perspective, cities may be conceptualized as a set of flows of different natures (people, capital, energy, information, and so on) arranged to serve the human development of their inhabitants.

Sustainability refers to the ability of those flows to be maintained and increased for the foreseeable future, adjusting to changes in population and/or population expectations. Sustainability, therefore, implies that an urban system is efficient, with low entropy, so redundancies and losses do not compromise the future capacity of the system to maintain its functions.

On the other hand, resilience accounts for the ability the system to resist or respond to disturbances, from the perspective of information theory, the number of possibilities the system has to rearrange itself in response to disturbances, while maintaining their flows, and, therefore, function. The possibilities of the urban system to maintain functionality in the face of a serious disturbance seems to imply the existence of some level of redundancy, or entropy, so the former, less-efficient paths may be easily taken after a structural change to maintain necessary flows.

The integration of the concepts of resilience and sustainability of urban systems, through spatial dimensions is also a promising development. Cities are also places, spatial entities with location, connectivity, and spatial variation, closely related with surrounding landscapes and ecosystems. Information Theory may, again, provide substantial tools to address the spatial resilience of urban ecosystems, as it has been doing for natural and semi-natural ecosystems.

Dr. Pedro Cabral
Dr. Alexander Zamyatin
Guest Editors

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Keywords

  • Urban sprawl
  • Resilience
  • Urban metabolism
  • Resilience
  • Sustainability
  • Information theory

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Published Papers (4 papers)

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Research

2665 KiB  
Article
Assessing Catchment Resilience Using Entropy Associated with Mean Annual Runoff for the Upper Vaal Catchment in South Africa
by Masengo Ilunga
Entropy 2017, 19(5), 147; https://doi.org/10.3390/e19050147 - 27 Apr 2017
Cited by 14 | Viewed by 6732
Abstract
The importance of the mean annual runoff (MAR)-hydrological variable is paramount for catchment planning, development and management. MAR depicts the amount of uncertainty or chaos (implicitly information content) of the catchment. The uncertainty associated with MAR of quaternary catchments (QCs) in the Upper [...] Read more.
The importance of the mean annual runoff (MAR)-hydrological variable is paramount for catchment planning, development and management. MAR depicts the amount of uncertainty or chaos (implicitly information content) of the catchment. The uncertainty associated with MAR of quaternary catchments (QCs) in the Upper Vaal catchment of South Africa has been quantified through Shannon entropy. As a result of chaos over a period of time, the hydrological catchment behavior/response in terms of MAR could be characterized by its resilience. Uncertainty (chaos) in QCs was used as a surrogate measure of catchment resilience. MAR data on surface water resources (WR) of South Africa of 1990 (i.e., WR90), 2005 (WR2005) and 2012 (W2012) were used in this study. A linear zoning for catchment resilience in terms of water resources sustainability was defined. Regression models (with high correlation) between the relative changes/variations in MAR data sets and relative changes in entropy were established, for WR2005 and WR2012. These models were compared with similar relationships for WR90 and WR2005, previously reported. The MAR pseudo-elasticity of the uncertainty associated with MAR was derived from regression models to characterize the resilience state of QCs. The MAR pseudo-elasticity values were relatively small to have an acceptable level of catchment resilience in the Upper Vaal catchment. Within the resilience zone, it was also shown that the effect of mean annual evaporation (MAE) was negatively significant on MAR pseudo-elasticity, compared to the effect of mean annual precipitation (MAP), which was positively insignificant. Full article
(This article belongs to the Special Issue Entropy for Sustainable and Resilient Urban Future)
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7403 KiB  
Article
Modelling Urban Sprawl Using Remotely Sensed Data: A Case Study of Chennai City, Tamilnadu
by Rajchandar Padmanaban, Avit K. Bhowmik, Pedro Cabral, Alexander Zamyatin, Oraib Almegdadi and Shuangao Wang
Entropy 2017, 19(4), 163; https://doi.org/10.3390/e19040163 - 7 Apr 2017
Cited by 76 | Viewed by 14371
Abstract
Urban sprawl (US), propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, adversely affects the provision of ecosystem services. The quantification of US is thus crucial for effective urban [...] Read more.
Urban sprawl (US), propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, adversely affects the provision of ecosystem services. The quantification of US is thus crucial for effective urban planning and environmental management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive US triggered by the doubling of total population over the past three decades. However, the extent and level of US has not yet been quantified and a prediction for future extent of US is lacking. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed six landscape metrics to delineate the extent of urban areas within a 10 km suburban buffer of Chennai. The level of US was then quantified using Renyi’s entropy. A land change model was subsequently used to project land cover for 2027. A 70.35% expansion in urban areas was observed mainly towards the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was 0.9, exhibiting a two-fold level of US when compared to 1991. The spatial metrics values indicate that the existing urban areas became denser and the suburban agricultural, forests and particularly barren lands were transformed into fragmented urban settlements. The forecasted land cover for 2027 indicates a conversion of 13,670.33 ha (16.57% of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value to 1.7, indicating a tremendous level of US. Our study provides useful metrics for urban planning authorities to address the social-ecological consequences of US and to protect ecosystem services. Full article
(This article belongs to the Special Issue Entropy for Sustainable and Resilient Urban Future)
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2149 KiB  
Article
An Urban Cellular Automata Model for Simulating Dynamic States on a Local Scale
by Jenni Partanen
Entropy 2017, 19(1), 12; https://doi.org/10.3390/e19010012 - 28 Dec 2016
Cited by 5 | Viewed by 7197
Abstract
In complex systems, flexibility and adaptability to changes are crucial to the systems’ dynamic stability and evolution. Such resilience requires that the system is able to respond to disturbances by self-organizing, which implies a certain level of entropy within the system. Dynamic states [...] Read more.
In complex systems, flexibility and adaptability to changes are crucial to the systems’ dynamic stability and evolution. Such resilience requires that the system is able to respond to disturbances by self-organizing, which implies a certain level of entropy within the system. Dynamic states (static, cyclical/periodic, complex, and chaotic) reflect this generative capacity, and correlate with the level of entropy. For planning complex cities, we need to develop methods to guide such autonomous progress in an optimal manner. A classical apparatus, cellular automaton (CA), provides such a tool. Applications of CA help us to study temporal dynamics in self-organizing urban systems. By exploring the dynamic states of the model’s dynamics resulting from different border conditions it is possible to discover favorable set(s) of rules conductive to the self-organizing dynamics and enable the system’s recovery at the time of crises. Level of entropy is a relevant measurement for evaluation of these dynamic states. The 2-D urban cellular automaton model studied here is based on the microeconomic principle that similar urban activities are attracted to each other, especially in certain self-organizing areas, and that the local dynamics of these enclaves affect the dynamics of the urban region by channeling flows of information, goods and people. The results of the modeling experiment indicate that the border conditions have a major impact on the model’s dynamics generating various dynamic states of the system. Most importantly, it seemed that the model could simulate a favorable, complex dynamic state with medium entropy level which may refer to the continuous self-organization of the system. The model provides a tool for exploring and understanding the effects of boundary conditions in the planning process as various scenarios are tested: resulting dynamics of the system can be explored with such “planning rules” prior to decisions, helping to identify planning guidelines that will support the future evolution of these areas. Full article
(This article belongs to the Special Issue Entropy for Sustainable and Resilient Urban Future)
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375 KiB  
Article
Entropic Citizenship Behavior and Sustainability in Urban Organizations: Towards a Theoretical Model
by David Coldwell
Entropy 2016, 18(12), 453; https://doi.org/10.3390/e18120453 - 19 Dec 2016
Cited by 13 | Viewed by 8206
Abstract
Entropy is a concept derived from Physics that has been used to describe natural and social systems’ structure and behavior. Applications of the concept in the social sciences so far have been largely limited to the disciplines of economics and sociology. In the [...] Read more.
Entropy is a concept derived from Physics that has been used to describe natural and social systems’ structure and behavior. Applications of the concept in the social sciences so far have been largely limited to the disciplines of economics and sociology. In the current paper, the concept of entropy is applied to organizational citizenship behavior with implications for urban organizational sustainability. A heuristic is presented for analysing personal and organizational citizenship configurations and distributions within a given workforce that can lead to corporate entropy; and for allowing prescriptive remedial steps to be taken to manage the process, should entropy from this source threaten its sustainability and survival. Full article
(This article belongs to the Special Issue Entropy for Sustainable and Resilient Urban Future)
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