A Decision-Making Framework for Spatial Multicriteria Suitability Analysis using PROMETHEE II and k Nearest Neighbor Machine Learning Models

Sotiropoulou, Kalliopi F.; Vavatsikos, Athanasios P.

doi:10.1007/s41651-023-00151-3

Cited by 11 publications

(5 citation statements)

References 46 publications

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“…More specifically, the empirical results of the econometric estimation run in this study on real population data at four disaggregation levels (moving from an aggregate level, such as the NUTS-3 prefectures, to a mostly disaggregated level, such as the LAU-2 local communities in Greece) document the highest fit of a quadratic relationship in the estimation of the rank-size rule in Greece against more classical linear relationships [86]. These findings were collected irrespective of the aggregation level characteristic of the elementary observational units and, thus, may demonstrate the existence of distinctive dynamics along the density hierarchy that are independent of data aggregation [87]. Moreover, the results of the econometric estimation have documented the appropriateness of a quadratic relationship identifying two rank-size relationships [75], i.e., with distinctive regression coefficients, along the investigated population hierarchy from the largest cities to the smallest villages in Greece [88].…”

Section: Discussionmentioning

confidence: 78%

Envisaging the Intrinsic Departure from Zipf’s Law as an Indicator of Economic Concentration along Urban–Rural Gradients

Sateriano,

Quaranta,

Salvia

et al. 2024

Land

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A rank-size rule following Zipf’s law was tested along a complete urban–rural hierarchy in Greece using 2021 census data released at different administrative levels. Testing five econometric specifications (linear, quadratic, and cubic forms, together with refined logistic and Gompertz forms) on log-transformed population numbers, deviations from the rank-size rule were assumed as an indicator of economic concentration (considering settlements, population, and activities jointly) along the density gradient in Greece. This hypothesis was verified using progressively disaggregated population numbers at (i) regional units (n = 75), (ii) ‘Kallikratis’ municipalities (n = 333), (iii) ‘Kapodistrian’ municipalities (n = 1037), and (iv) local communities (n = 6126). Econometric results were stable across geographical levels and indicate a relatively poor fit of linear specifications, the classical formulation of Zipf’s law. Quadratic specifications displayed a good fit for all territorial levels outperforming cubic specifications. Gompertz specifications outperformed logistic specifications under aggregate partitions (e.g., regional units and ‘Kallikratis’ municipalities). Quadratic specifications outperformed both logistic and Gompertz specifications under disaggregated levels of investigation (‘Kapodistrian’ municipalities and local communities). Altogether, these findings indicate the persistence of non-linear rank-size relationships estimated over a cross-section of population data at progressively detailed observational units. Such evidence enriches the recent literature on Zipf’s law, demonstrating the inherent complexity of rank-size rules tested on real data along the whole density gradient in a given country.

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Section: Discussionmentioning

confidence: 78%

Envisaging the Intrinsic Departure from Zipf’s Law as an Indicator of Economic Concentration along Urban–Rural Gradients

Sateriano,

Quaranta,

Salvia

et al. 2024

Land

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“…(2) We will further identify high-risk areas and propose countermeasures by simulating and extrapolating the flood inundation process under different scenarios. (3) Since there are some emerging spatiotemporal models, such as machine learning models and social media data-such as Twitter data-which are used in other applications (e.g., land use suitability analysis, post-earthquake building usability assessment, estimation of local-scale domestic electricity energy consumption) [36][37][38], we will try to apply these emerging models to flood risk assessment in the future.…”

Section: Discussionmentioning

confidence: 99%

Flood Risk Assessment Based on a Cloud Model in Sichuan Province, China

Liu,

Wang,

et al. 2023

Sustainability

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Floods are serious threats to the safety of people’s lives and property. This paper systematically introduces the basic theories and methods of flood risk assessment, takes Sichuan Province as the study area, and establishes a flood risk assessment index system with 14 indicators in four aspects—disaster-causing factors, disaster-forming environment, disaster-bearing body, and regional disaster resilience capacity—from the causes of disaster losses and flood formation mechanisms. Furthermore, this paper constructs a flood disaster risk assessment model for Sichuan Province based on a cloud model, entropy value, and GIS technology. The model is validated by taking the July–August 2023 flood disaster as an example, and the results show that the distribution of the disaster was consistent with the flood risk assessment results of this paper, which verifies that the selected indicators are appropriate and the model is accurate and valid.

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“… 13 Sotiropoulou and Vavatsikos (2023) developed a multi-criteria decision framework to support sustainable land suitability analysis and land management planning. 14 Vahidnia et al. (2022) introduced a decision support system based on the Analytic Hierarchy Process (AHP) to optimize the distribution of fire stations, providing them with the best spatial optimization solutions.…”

Section: Introductionmentioning

confidence: 99%

Dual hybrid frameworks combining graph convolutional network with decoding for covering location problem

Zhang,

Wang,

Liang

et al. 2024

iScience

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A Decision-Making Framework for Spatial Multicriteria Suitability Analysis using PROMETHEE II and k Nearest Neighbor Machine Learning Models

Cited by 11 publications

References 46 publications

Envisaging the Intrinsic Departure from Zipf’s Law as an Indicator of Economic Concentration along Urban–Rural Gradients

Envisaging the Intrinsic Departure from Zipf’s Law as an Indicator of Economic Concentration along Urban–Rural Gradients

Flood Risk Assessment Based on a Cloud Model in Sichuan Province, China

Dual hybrid frameworks combining graph convolutional network with decoding for covering location problem

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