Indexing habitat suitability and human-elephant conflicts using GIS-MCDA in a human-dominated landscape

Withanage, W.K.N.C.; Gunathilaka, M.D.K.L.; Mishra, Prabuddh Kumar; Wijesinghe, W.M.D.C.; Tripathi, Sumita

doi:10.1016/j.geosus.2023.08.004

Cited by 9 publications

(4 citation statements)

References 41 publications

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“…The flat terrain (Figure 3a) of the study area may reveal the possibility of high groundwater potential. The slope of the area was categorized into five groups very high (0.018-1.5), high (1.6-3.9), moderate (4-8.3), low (8.4-15), and very low (16)(17)(18)(19)(20)(21)(22). Towards the center of the area, there is a slightly steeper slope.…”

Section: Slopementioning

confidence: 99%

“…To make the best choice feasible, MCDA is used to assess and contrast several factors, which are frequently at odds with one another [16]. Multi-criteria approaches are referred to in the academic community in a variety of ways, including multiple-criteria decision aiding (MCDA), multi-criteria decision making (MCDM), multiobjective decision making (MODM), and multi-attribute decision making (MADM) [16][17][18]. Different MCDA techniques are available, including the analytical hierarchy process (AHP), TOPSIS, PROMETHEE, ELECTRE, SWARA, WASPAS, etc.…”

Section: Introductionmentioning

confidence: 99%

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Application of GIS, Multi-Criteria Decision-Making Techniques for Mapping Groundwater Potential Zones: A Case Study of Thalawa Division, Sri Lanka

Wijesinghe,

Mishra,

Withanage

et al. 2023

Water

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Groundwater resources are depleting due to phenomena such as significant climate change and overexploitation. Therefore, it is essential to estimate water production and identify potential groundwater zones. An integrated conceptual framework comprising GIS and the analytical hierarchy process (AHP) has been applied for the present study to identify groundwater potential areas in the Thalawa division of Sri Lanka. The criteria, including rainfall, soil types, slope, stream density, lineament density, geology, geomorphology, and land use, were taken into account as the most contributing factors when identifying the groundwater zones. Weights were allocated proportionally to the eight thematic layers according to their importance. Hierarchical ranking and final normalized weighting of these determinants were performed using the pairwise comparison matrix (PCM) available in AHP. Based on the results obtained, the groundwater potential zone (GWPZ) was classified into three regions: low potentiality (33.4%), moderate potentiality (55.8%), and high potentiality (10.6%). Finally, the zoning map was compared to find consistency with field data on groundwater discharge and depth taken from 18 wells in the division. The results revealed that the GIS-multi-criteria decision-making (MCDM) approach brings about noticeably better results, which can support groundwater resource planning and sustainable use in the research area.

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Section: Slopementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of GIS, Multi-Criteria Decision-Making Techniques for Mapping Groundwater Potential Zones: A Case Study of Thalawa Division, Sri Lanka

Wijesinghe,

Mishra,

Withanage

et al. 2023

Water

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“…AHP is a commonly used multi‐criteria decision‐making method used to analyze and compare the relative importance of multiple criteria or solutions [7]. AHP provides a structured approach where decision‐makers can decompose complex decision‐making problems into hierarchical structures based on their own experience and knowledge, making the decision‐making process more organized and actionable [8]. In fact, the above decision‐making process makes AHP dependent on the subjective judgment and comparison of decision‐makers, so there is a risk of subjectivity and personal bias.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive performance evaluation algorithm for substation secondary equipment: An improved analytic hierarchy process entropy weight and learning vector quantization neural network approach

Wang,

Zhang,

Wang

et al. 2024

The Journal of Engineering

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This paper introduces a comprehensive performance evaluation algorithm explicitly designed for secondary equipment in substations, specifically targeting the relay protection system. In contrast to the current evaluation systems, this novel method navigates the complex internal interconnections and mechanisms inherent within secondary system equipment. Such complications have previously impeded the accuracy and breadth of evaluations, thereby limiting the degree of precision and innovation attainable within substations. The proposed approach effectively integrates the improved Analytic Hierarchy Process entropy weight (IAHP‐EW) method with the Learning Vector Quantization (LVQ) neural network. Initially, the IAHP‐EW method identified the comprehensive evaluation indicators and their corresponding weights for relay protection devices. Following weight allocation, these evaluation indicators are scrutinized and computed utilizing the multivariate regression analysis algorithm, resulting in performance evaluation outcomes for the relay protection system. These outcomes are subsequently classified and utilized in training the LVQ neural network, promoting the network's capacity to autonomously evaluate the performance status of the relay protection system. To corroborate the viability and effectiveness of this proposed performance evaluation and prediction algorithm, empirical operating data from a local substation is used. The results suggest a significant improvement in the evaluation accuracy of secondary equipment performance, indicating potential for practical application and a valuable contribution to the field through the introduction of a novel approach to performance assessment of substation relay protection systems.

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“…The combination of GIS-MCDA has been used for various purposes such as the assessment of land suitability [11,[22][23][24][25], renewable energy [26][27][28][29], vulnerability to natural hazards [30,31], socio-environmental resilience [32], agricultural management [33], habitat suitability [34], spatial modeling of migration [35], and urban management [1,36,37]. In past studies, various GIS-MCDA methods such as AHP, Fuzzy AHP, Fuzzy TOPSIS, ANP, VIKOR, ELECTRE, and PROMETHEE have been used for these applications.…”

Section: Introductionmentioning

confidence: 99%

A Scenario-Based Multi-Criteria Decision-Making Approach for Allocation of Pistachio Processing Facilities: A Case Study of Zarand, Iran

Ebrahimi Sirizi,

Taghavi Zirvani,

Esmailzadeh

et al. 2023

Sustainability

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Site selection and allocation of manufacturing and processing facilities are essential to sustainable economic productivity of a given product while preserving soil, the environment, and biodiversity. An essential criterion when evaluating various approaches to model land suitability for pistachio processing facilities is their adaptability to accommodate diverse perspectives and circumstances of managers and decision makers. Incorporating the concept of risk into the decision-making process stands as a significant research gap in modeling land suitability for pistachio processing facilities. This study presents a scenario-based multi-criteria decision-making system for modeling the land suitability of pistachio processing facilities. The model was implemented based on a stakeholder analysis as well as inclusion of a set of influential criteria and restrictions for an Iranian case study, which is among the top three producers. The weight of each criterion was determined based on the best-worst method (BWM) after the stakeholder analysis. Then, the ordered weighted averaging (OWA) model was used to prepare maps of spatial potential for building a pistachio processing factory in different decision-making scenarios, including very pessimistic, pessimistic, intermediate, optimistic, and very optimistic attitudes. Finally, the sensitivity analysis of very-high- and high-potential regions to changes in the weight of the effective criteria was evaluated and proved that the most important criteria were proximity to pistachio orchards, proximity to residential areas, proximity to the road network, and proximity to industrial areas. Overall, 327 km2 of the study area was classified as restricted, meaning that they are not suitable locations for pistachio processing. The average estimated potential values based on the proposed model for very pessimistic, pessimistic, intermediate, optimistic, and very optimistic scenarios were 0.19, 0.47, 0.63, 0.78, and 0.97, respectively. The very-high-potential class covered 0, 0.41, 8.25, 39.64, and 99.78 percent of the study area based on these scenarios, respectively. The area of suitable regions for investment decreased by increasing risk aversion in decision making. The model was more sensitive to changes in the weights of proximity to residential areas, proximity to pistachio orchards, and proximity to transportation hubs. The proposed approach and the achieved findings could be of broader use to respective stakeholders and investors. Given the suitability of arid regions for planting pistachio and its relatively high profitability, the local authorities and decision makers can promote further expansion of the orchards, which can lead to better welfare of farmers and reducing rural-urban migration in the region.

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Indexing habitat suitability and human-elephant conflicts using GIS-MCDA in a human-dominated landscape

Cited by 9 publications

References 41 publications

Application of GIS, Multi-Criteria Decision-Making Techniques for Mapping Groundwater Potential Zones: A Case Study of Thalawa Division, Sri Lanka

Application of GIS, Multi-Criteria Decision-Making Techniques for Mapping Groundwater Potential Zones: A Case Study of Thalawa Division, Sri Lanka

A comprehensive performance evaluation algorithm for substation secondary equipment: An improved analytic hierarchy process entropy weight and learning vector quantization neural network approach

A Scenario-Based Multi-Criteria Decision-Making Approach for Allocation of Pistachio Processing Facilities: A Case Study of Zarand, Iran

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