Landscape Economic Attractiveness: An Integrated Methodology for Exploring the Rural Landscapes in Piedmont (Italy)

Assumma, Vanessa; Bottero, Marta Carla; Monaco, Roberto

doi:10.3390/land8070105

Cited by 19 publications

(15 citation statements)

References 33 publications

(24 reference statements)

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“…Industrial ecology "The ability [for industrial ecosystems] to maintain their defining feature of eco-efficient material and energy flows under disruptions" (p. 74). Dynamic…”

Section: Rose 2007mentioning

confidence: 99%

“…In Table 5, a number of literature contributions are listed, in that the outcome of Lotka-Volterra systems may be interpreted as a resilience factor. More in details, Finotto and Monaco [70] and Gobattoni et al [71,72] are generally used for developing stability analyses on ecological sectors, thus predicting future possible equilibrium states; Monaco and Servente [69] are used to simulate the population's mobility and Monaco [73] integrates a synthetic index calculated through a system of indicators for investigating the population's mobility with respect to Gross Leasable Areas (GLAs); Assumma et al [74,75] predicts the population's flow over time in rural landscapes with respect to the economic attractiveness; Assumma et al [76] simulates the dynamics related to economic attractiveness and ecological quality as resilience factor. Therefore, Lotka-Volterra models have been employed at different spatial scales with different purposes, thus obtaining useful insights, such as in the field of landscape ecology and landscape economics [77].…”

Section: Illustrative Examplementioning

confidence: 99%

“…where P' i is the state variable of the population i; A represents a synthetic index of ecological quality and economic attractiveness calculated for the poles i and j; d ij consists in the distance recorded between the poles i and j, whereas d M measures the recorded highest distance between the poles; and S i is the carrying capacity, that is intended as the threshold number of people in a given pole. It has to be noticed that the parameter A i was calculated by considering a system of landscape economic indicators and a system of ecological indicators, according to a Multicriteria approach (for more, please see [74,79,80]). The considered systems of indicators and their indices aim to calculate a super-index that measures the overall attractiveness of the territory by considering the ecological quality and the economic attractiveness.…”

Section: Illustrative Examplementioning

confidence: 99%

“…These two DMs use, in different ways the time scale: the SDM model use a real time scale that may be traduced in months, years or centuries, whereas the LV model uses an arbitrary time scale that may be subdivided in an initial phase when the function starts with the state of art conditions (t 0 ), transitory phase, when the linear function evolves in terms of growth or degrowth, and a final phase, when the linear function became stable. The arbitrary time scale may be traduced in a real time scale by considering the historical series of the analyzed parameters [74]. Sensitivity analysis is a valuable procedure for testing the model response with respect to the variation of parameter values, as well as to identify those parameters that have more impact than the others on the investigated phenomenon [88].…”

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confidence: 99%

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Dynamic Models for Exploring the Resilience in Territorial Scenarios

et al. 2019

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The present paper focuses on the role covered by dynamic models as support for the decision-making process in the evaluation of policies and actions for increasing the resilience of cities and territories. In recent decades, urban resilience has been recognized as a dynamic and multidimensional phenomenon that characterizes urban and metropolitan area dynamics. Therefore, it may be considered a fundamental aspect of urban and territorial planning. The employment of quantitative methods, such as dynamic models, is useful for the prediction of the dynamic behavior of territories and of their resilience. The present work discusses the system dynamics model and the Lotka-Volterra cooperative systems and shows how these models can aid technicians in resilience assessment and also decision makers in the definition of policies and actions, especially if integrated in wide evaluation frameworks for urban resilience achievements. This paper aims to provide an epistemological perspective of the application of dynamic models in resilience assessment, underlying the possible contribution to this issue through the analysis of a real case study and methodological framework. The main objective of this work is to lay the basis for future compared applications of these two models to the same case study.in order to underline dynamic model (DM) features that are closely related to the decision-making process in territorial and urban planning [11]. DMs are recognized as suitable tools to evaluate policies and actions aimed at increasing urban resilience [12][13][14]. This property is related to the fact that these models are built and grounded on dimensions related to both urban systems and urban resilience. In fact, during the construction of the model, it is necessary to select and identify which aspects of a territorial system have to be included with reference to the evaluation goal, from the environmental to the economic dimension [11,12,15]. In this sense, DMs are able to reveal both the dynamic behavior of urban and territorial systems and the impacts of policies on the key variables identified.Specifically, the main aim of this work is to study the principal characteristics of the system dynamics model (SDM) and Lotka-Volterra models (LV) in order to apply both to the same case study. The final purpose of this investigation is to understand the importance of the modelling approach in the field of resilience evaluation.The paper is structured as follows: Section 2 describes the current state of the art of resilience and urban resilience; Section 3 explains the role of dynamic models-the system dynamic models (SDM) and Lotka-Volterra models (LV)-in the decision-making process and summarizes their methodological background, state of art and some illustrative examples; Section 4 explains how the SDM models and LV models could contribute to urban planning; a comparative matrix is developed to investigate the utility of the considered models in predicting support in the design of future transformation scenarios; and Section 5 incl...

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“…Industrial ecology "The ability [for industrial ecosystems] to maintain their defining feature of eco-efficient material and energy flows under disruptions" (p. 74). Dynamic…”

Section: Rose 2007mentioning

confidence: 99%

Section: Illustrative Examplementioning

confidence: 99%

Section: Illustrative Examplementioning

confidence: 99%

mentioning

confidence: 99%

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Dynamic Models for Exploring the Resilience in Territorial Scenarios

et al. 2019

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“…It is recognized that the conservation and reuse for new functions of the cultural and landscape heritage can have positive impacts on the quality of life and individual and community well-being, contributing to the creation of jobs, the conservation of natural resources, and the revitalization of cities hosting heritage [20][21][22]. Given these premises, adaptive reuse could be the answer to both preserving memory and generating new values, looking at a more holistic vision, i.e., integrating social, economic, environmental, urban, and political policies in agreement with the Sustainable Development Goals (SDGs) and providing additional benefits related to the economic value of the landscape where the asset is located [23,24].…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Cultural Heritage through Adaptive Reuse. A Multicriteria Approach to Evaluate the Castello Visconteo in Cusago (Italy)

et al. 2021

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Cultural heritage can play a strategic role in developing a sustainable built environment, contributing to the improvement of the economic, social, and environmental productivity of a city. Human activities are constantly affecting the quality of the environment and altering the ecosystems, which produce negative consequences also on human wellbeing. Within this context, it has been much discussed how cities and the built environment can counteract this process by supporting more sustainable development. Adaptive reuse is defined as “a process that changes a disused or ineffective item into a new item that can be used for a different purpose”, which strongly triggers the sustainable development of cities. It can be recognized as a promoter of economic growth, social wellbeing, and environmental preservation, given its capability of both preserving past values and creating new ones. The adaptive reuse matches the main points of the circular economy, seen as the sustainable economy, which is aimed at the reduction of natural resource extraction and environmental impact by extending the useful life of materials and promoting recovery, reuse, and regeneration processes. Given these premises, the current contribution aimed to evaluate alternative scenarios for reuse in Castello Visconteo in Cusago, located in the Lombardy region (Italy), and understanding how adaptive reuse could contribute to generating new values within a circular economy perspective. In detail, four alternative scenarios were proposed to face the new needs born during the COVID-19 pandemic period. Since both intangible and tangible values must be considered, a multicriteria decision analysis (MCDA) has been applied by combining economic and qualitative indicators to define the most suitable function for its adaptive reuse. In detail, the Novel Approach to Imprecise Assessment and Decision Environments (NAIADE) was used to identify the best alternative solution based on the opinions of conflicting stakeholders. The innovativeness of the contribution is given by the combination of different methodologies, the preservation of the memory and the generation of new values, and the consideration of adaptive reuse as a strategy for the achievement of sustainable development within a circular economy perspective.

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