scholarly journals Mapping Mexican COVID-19 vulnerability at municipal scale

2020 ◽  
Author(s):  
Rainer Ressl ◽  
Carmen Luz Martínez ◽  
Miriam Elizabeth Piña Camacho ◽  
Florian Hruby ◽  
José Manuel Dávila Rosas ◽  
...  
Keyword(s):  
One Health ◽  
Pairwise Comparison ◽  
Vulnerability Index ◽  
Related Variable ◽  
Pairwise Comparison Matrix ◽  
Digital Atlas ◽  
Population Vulnerability ◽  
Interactive Map ◽  
Municipal Level ◽  
Very High

This paper presents an interactive map related to the population vulnerability concerning COVID-19 at the municipal level for Mexico. A vulnerability index was modeled using seven socioeconomic/sociodemographic variables and one health-care related variable, all with relevance to a health contingency such as COVID-19. The resulting indicator expresses the municipal vulnerability to face a sanitary crisis such as COVID-19 in five categories. Data for each of the eight variables were first categorized in quintiles. A pairwise comparison matrix was used to weight these variables in relation to their estimated relevance for the municipal vulnerability. With respect to COVID-19 vulnerability, Mexican municipalities show the following results: 1.6% (very low), 18.7% (low), 46.6% (medium), 24.6% (high), 8.5% (very high). The map forms part of a dashboard providing daily information on the development of the pandemic in Mexico, and is complemented by a digital atlas visualizing information for each variable of the indicator.

scholarly journals SINKHOLE SUSCEPTIBILITY HAZARD ZONES USING GIS AND ANALYTICAL HIERARCHICAL PROCESS (AHP): A CASE STUDY OF KUALA LUMPUR AND AMPANG JAYA

2017 ◽  
Vol XLII-4/W5 ◽  
pp. 145-151 ◽  
Author(s):  
M. A. H. M. Rosdi ◽  
A. N. Othman ◽  
M. A. M. Zubir ◽  
Z. A. Latif ◽  
Z. M. Yusoff
Keyword(s):  
Groundwater Level ◽  
Pairwise Comparison ◽  
Capital City ◽  
Kuala Lumpur ◽  
Analytical Hierarchical Process ◽  
Pairwise Comparison Matrix ◽  
High Hazard ◽  
Very High ◽  
Sinkhole Hazard

Sinkhole is not classified as new phenomenon in this country, especially surround Klang Valley. Since 1968, the increasing numbers of sinkhole incident have been reported in Kuala Lumpur and the vicinity areas. As the results, it poses a serious threat for human lives, assets and structure especially in the capital city of Malaysia. Therefore, a Sinkhole Hazard Model (SHM) was generated with integration of GIS framework by applying Analytical Hierarchical Process (AHP) technique in order to produced sinkhole susceptibility hazard map for the particular area. Five consecutive parameters for main criteria each categorized by five sub classes were selected for this research which is Lithology (LT), Groundwater Level Decline (WLD), Soil Type (ST), Land Use (LU) and Proximity to Groundwater Wells (PG). A set of relative weights were assigned to each inducing factor and computed through pairwise comparison matrix derived from expert judgment. Lithology and Groundwater Level Decline has been identified gives the highest impact to the sinkhole development. A sinkhole susceptibility hazard zones was classified into five prone areas namely very low, low, moderate, high and very high hazard. The results obtained were validated with thirty three (33) previous sinkhole inventory data. This evaluation shows that the model indicates 64 % and 21 % of the sinkhole events fall within high and very high hazard zones respectively. Based on this outcome, it clearly represents that AHP approach is useful to predict natural disaster such as sinkhole hazard.

scholarly journals MULTICRITERIA DECISION ANALYSIS FOR PRIORITIZING AREAS FOR FOREST RESTORATION

CERNE ◽  
2017 ◽  
Vol 23 (1) ◽  
pp. 53-60 ◽  
Author(s):  
Roberta Averna Valente ◽  
Felipe Coelho de Souza Petean ◽  
Carlos Alberto Vettorazzi
Keyword(s):  
Forest Restoration ◽  
Pairwise Comparison ◽  
Forest Patches ◽  
Pairwise Comparison Matrix ◽  
Priority Areas ◽  
Priority Map ◽  
Definition Of ◽  
Criteria Importance ◽  
Structure And Functions ◽  
Very High

ABSTRACT Urbanization process transforms original landscapes into an anthropic mosaic, causing impacts on hydrologic cycles and on landscape structure and functions. Aiming at the maintenance of the water resources and biodiversity, in an urbanized watershed, the objective of this study was the definition of priority areas for forest restoration. We used a Multicriteria Evaluation (MCE) method, following the steps: criteria definition, identification of the criteria importance, and criteria aggregation through Weighted Linear Combination (WLC). According to the experts, consulted in the context of the Participatory Technique, only two criteria represented the studied landscape: proximity to drainage network and proximity to forest patches. The first criterion was considered twice more important than the second, and through the pairwise comparison matrix, it was obtained respectively the criterion weights of 0.83 and 0.17. The priority map was obtained through the criteria aggregation, using WLC, that considered the criterion weights. The result was a priority map, indicating 5.06% of the study area with very-high priority for forest restoration; 5.22% with high priority; 5.76% with medium priority; 5,42% with low and; 78.53% with very-low priority. We can say that the framework predefined for the study proposed a scenario for priority areas that allowed driving the actions in order to obtain a landscape restoration, beginning through a forest corridor in the riparian zone. Thus, we concluded that the definition of priority areas for forest restoration is possible in an urbanized landscape, using the traditional WLC Multicriteria method.

scholarly journals GIS Based Approach for Vulnerability Assessment of the Karnataka Coast, India

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Akshaya Beluru Jana ◽  
Arkal Vittal Hegde
Keyword(s):  
Shoreline Change ◽  
Vulnerability Index ◽  
Tidal Range ◽  
Coastal Zones ◽  
Remotely Sensed Data ◽  
Coastal Vulnerability Index ◽  
Karnataka State ◽  
Administrative Units ◽  
2004 Tsunami ◽  
Very High

The coastal zones are highly resourceful and dynamic. In recent times, increased events of tropical cyclones and the devastating impact of the December 2004 tsunami have brought forth the importance of assessing the vulnerability of the coast to hazard-induced flooding and inundation in coastal areas. This study intends to develop coastal vulnerability index (CVI) for the administrative units, known astalukasof the Karnataka state. Seven physical and geologic risk variables characterizing the vulnerability of the coast, including rate of relative sea level change, historical shoreline change, coastal slope, coastal regional elevation, mean tidal range, and significant wave height derived using conventional and remotely sensed data, along with one socioeconomic parameter “population,” were used in the study. A total of 298 km of shoreline are ranked in the study. It was observed that about 68.65 km of the shoreline is under very high vulnerable category and 79.26 km of shoreline is under high vulnerable category. Of the remaining shoreline, 59.14 km and 91.04 km are of moderate and low vulnerable categories, respectively.

scholarly journals A Decision Analysis Model for the Brand Experience of Branded Apps Using Consistency Fuzzy Linguistic Preference Relations

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1151
Author(s):  
Tsuen-Ho Hsu ◽  
Chun-Hsien Chen ◽  
Ya-Wun Yang
Keyword(s):  
Customer Loyalty ◽  
Pairwise Comparison ◽  
Brand Experience ◽  
Decision Analysis Model ◽  
Analysis Model ◽  
Pairwise Comparison Matrix ◽  
Preference Relations ◽  
New Business ◽  
Fuzzy Linguistic ◽  
The Impact

Branded apps are not only an important platform for enterprises and customers to have real-time interactions and communicate marketing messages, but also a new business model that encourages value co-creation between the two. In order to explore the impact of branded apps on customers, this study constructs a fuzzy multi-criteria decision making (FMCDM) analysis model, and it uses consistent fuzzy linguistic preference relations (CFLPR) to set up a symmetric pairwise comparison matrix, which greatly reduces the complexity and error rate of calculations. Empirical research findings show that brand experience attributes and the influence of brand experience on customer loyalty and satisfaction can be more accurately measured. As a consequence of this study, we show that, among the brand experience facets of two retail chain branded apps, behavioral experience is the most favored, while affective experience is the least favored. Furthermore, brand attachment and active participation should be strengthened to enhance customer loyalty. Through the analytical model employed in this study, enterprises can regularly monitor changes in the brand experience preferences of branded app users and evaluate app performance to flexibly adjust mobile device-based marketing campaigns and strategies. It can also aid enterprises in using mobile devices effectively to improve customer loyalty and address the issue of diminishing brand loyalty.

scholarly journals ASSESSMENT OF SUSCEPTIBILITY TO SΕA-LΕVEL RISE IN THE COASTAL AREA OF PIERIA PREFECTURE

2017 ◽  
Vol 50 (3) ◽  
pp. 1721
Author(s):  
A. Mavromatidi ◽  
E. Karymbalis
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Accretion Rate ◽  
Vulnerability Index ◽  
Coastal Areas ◽  
Tidal Range ◽  
Coastal Vulnerability Index ◽  
Economic Significance ◽  
Very High

Tourism development in Greece has led to increasing pressure on coastal areas, which makes the study of sensitive coastal areas essential, in order to find appropriate solutions for their shielding. The aim of this study is an estimation of the effects of an anticipated sea level rise for the touristically developed part of Pieria Prefecture, which includes the settlements Paralia, Skala of Katerini, Olympic Beach, Korinos Beach and extends north to the area of the Kitrous saltworks and south to the mouth of Mavroneri river. Therefore the Coastal Vulnerability Index (CVI) is applied, in an attempt to determine the susceptible parts to the potential sea level rise. CVI depends on the following parameters: (a) coastal geomorphology, (b) coastal slope, (c) shoreline erosion/accretion rate, (d) relative sea-level rise fluctuations, (e) mean tidal range and (f) mean significant wave height. The classification of the coast, which is of particular socio-economic significance since it hosts urbanized areas, into five CVI classes (from very low vulnerability to very high vulnerability), showed that 43.6% of the entire coastline is of very high vulnerability. 

scholarly journals An Approach for Generating Weights Using the Pairwise Comparison Matrix

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zaher Sepehrian ◽  
Sahar Khoshfetrat ◽  
Said Ebadi
Keyword(s):  
Pairwise Comparison ◽  
Decision Criterion ◽  
Data Envelopment ◽  
Decision Criteria ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Proposed Model ◽  
Assurance Region ◽  
Potential Applications ◽  
Hierarchy Process

Data envelopment analysis (DEA) has been used for obtaining weights for the analytic hierarchy process (AHP), an approach known as DEAHP. This method sometimes identifies more than one decision criterion or alternative as DEAHP-efficient. To overcome this problem, this paper proposes a new approach that not only generates appropriate weights for the decision criteria or alternatives, but also differentiates between DEAHP-efficient decision criteria or alternatives. To this end, we propose a DEA model with an assurance region and a cross-weight model that prioritizes decision criteria or alternatives by considering their most unfavorable weights. Two numerical examples are also provided to illustrate the advantages and potential applications of the proposed model.

scholarly journals AHP PRIORITIES AND MARKOV-CHAPMAN-KOLMOGOROV STEADY-STATES PROBABILITIES

2015 ◽  
Vol 7 (2) ◽  
Author(s):  
Stan Lipovetsky
Keyword(s):  
Steady State ◽  
General Solution ◽  
Stochastic Modeling ◽  
Pairwise Comparison ◽  
System Of Equations ◽  
Pairwise Comparison Matrix ◽  
Pair Comparison ◽  
Priority Vector ◽  
Discrete States ◽  
Steady State Probabilities

<div class="MsoTitle" style="margin: 12pt 0in 15pt;"><p>An AHP matrix of the quotients of the pair comparison priorities is transformed to a matrix of shares of the preferences which can be used in Markov stochastic modeling via the Chapman-Kolmogorov system of equations for the discrete states. It yields a general solution and the steady-state probabilities. The AHP priority vector can be interpreted as these probabilities belonging to the discrete states corresponding to the compared items. The results of stochastic modeling correspond to robust estimations of priority vectors not prone to influence of possible errors among the elements of a pairwise comparison matrix.</p></div><div class="MsoTitle" style="margin: 12pt 0in 15pt;"> </div>

Application of AHP and Geospatial Techniques for Evaluating Gully Erosion Vulnerability in Benin City, Edo State, Nigeria

2021 ◽  
Vol 2 (1) ◽  
pp. 1-15
Author(s):  
Deborah Alaigba ◽  
Keyword(s):  
Drainage System ◽  
Pairwise Comparison ◽  
Road Construction ◽  
Gully Erosion ◽  
Control Measures ◽  
Pairwise Comparison Matrix ◽  
Geospatial Techniques ◽  
Benin City ◽  
The People ◽  
And Control

Gully erosion remains a major threat to the people of Benin City. This study applies Analytical Hierarchical Process (AHP) and geospatial techniques to evaluate vulnerability to gully erosion in Benin City, Nigeria. Five essential criteria were identified based on literature, and evaluation by experts. Pairwise Comparison Matrix (PCM) was obtained and weights for each of the PCM were determined using AHP. The consistency of generated weights obtained is not above 0.07. The method resulted in a gully erosion vulnerability model. Analysis of the model revealed that 52.1% (488.69Km2) of the area is vulnerable to gully erosion, while 3.4% (32.37 Km2) was found to be highly vulnerable to gully erosion. Fieldwork was conducted to establish the people’s perception and identify the causes and control measures for the gully erosion problem in the area. Findings on the major contributing factor that leads to the gully erosion formation showed that lack of drainage system accounts for 56.25%, improper land use practice account for 25%, and bad road construction (18.75%). About 50% of the respondents are of the view that an adequate drainage system would go a long way to mitigate the gully erosion. This present study has provided information on the state of gully erosion vulnerability in Benin City through mapping of vulnerable areas.

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