An integrated GIS-based Ordered Weighted Averaging analysis for solar energy evaluation in Iran: Current conditions and future planning

Firozjaei, Mohammad Karimi; Nematollahi, Omid; Mijani, Naeim; Shorabeh, Saman Nadizadeh; Firozjaei, Hamzeh Karimi; Toomanian, Ara

doi:10.1016/j.renene.2018.09.090

Cited by 104 publications

(54 citation statements)

References 67 publications

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“…Other data sources correspond to dedicated location information providers such as the Environmental Systems Research Institute (ESRI 1 ), Openstreetmap 2 , and Google [11], [12], [17], [24], [44], [45], [47]- [50], [52], [54], [55], [60], [64], [76], [78], [80]- [85], [87]- [93], [95]- [97], [107], [108], [111]- [114], [117], [118], [121], [126], [127], [129], [132], [137], [138], [143], [147], [149]- [154], [156], [157], [159], [168], [169], [171], [175]- [184], [192], [197], [199]...…”

Section: Data Component Findingsmentioning

confidence: 99%

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

2020

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Section: Data Component Findingsmentioning

confidence: 99%

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

2020

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“…They reached a conclusion that renewable energy plays a significant role to satisfy the electricity needs of the country. Firozjaei et al also evaluated the solar energy in Iran. In this framework, the priority of regions is determined with Ordered Weighted Averaging approach.…”

Section: Literature Reviewmentioning

confidence: 58%

Multidimensional evaluation of global investments on the renewable energy with the integrated fuzzy decision-making model under the hesitancy

Dınçer

Yüksel

2019

Int J Energy Res

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Summary This study aims to assess global investment alternatives with respect to renewable energy. Within this framework, five different renewable energy types (biomass, hydropower, geothermal, wind, and solar) are determined as investment alternatives. Moreover, eight different criteria are selected by considering the four different dimensions of balanced scorecard. Additionally, the fuzzy‐based decision making trial and the evaluation laboratory under the hesitancy (HF‐DEMATEL) model are taken into the account to weight these dimensions and criteria and the technique for order the preferences by the similarity to the ideal solution with the fuzzy hesitant methodology (HF‐TOPSIS) is considered to select the alternatives of renewable energy investments. The novelties of this study are to propose an integrated model and provide the balanced scorecard–based evaluations of global renewable energy investment alternatives. The findings show that learning and growth and customer are the most important dimensions for the investment on renewable energy. It is also identified that market potential, product customization, and technological development are the most significant criteria for this situation. On the other side, solar and wind energy are the most important renewable investment alternatives. These results explain that technological improvement should be maintained, and customer expectations should be met by the companies. Furthermore, solar power plant and wind power plant should be developed in the countries. For this purpose, governments should give necessary incentives to the investors, such as allocating appropriate lands. These actions can attract the attentions of the potential investors for these renewable energy alternatives. Owing to this issue, it can be possible to increase the capacity of electricity productions in the countries with a potential minimum cost.

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“…Such normalization uniformly rescales the distribution of LST to the 0-and-1 range, as well as reduces the climatic differences. Then, we classified the NLST into different thermal field levels (from 3 to 6) through the equalization method and the mean value-standard deviation (STD) method (Table A3), and chose the preferred method and numbers of corresponding thermal field levels based on the results (Figures A1-A4) [61]. Subsequently, the area of each level and SUHI pattern were calculated and investigated during the period of interest.…”

Section: Normalized Lst Level Mapmentioning

confidence: 99%

“…where m represents the level number in the previous normalized step, n the number of the levels higher than the mean temperature, Wi the weight of the levels higher than the mean temperature (the order value of the level in m, for example , the weight value of high and extra-high levels are 5 and 6, respectively), and P i the area proportion of the SUHI level of i in the study area [59,61].…”

Section: Suhi Ratio Index Computationmentioning

confidence: 99%

Assessing the Impact of Land Cover Changes on Surface Urban Heat Islands with High-Spatial-Resolution Imagery on a Local Scale: Workflow and Case Study

et al. 2019

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Low-altitude remote sensing platform has been increasingly applied to observing local thermal environments due to its obvious advantage in spatial resolution and apparent flexibility in data acquisition. However, there is a general lack of systematic analysis for land cover (LC) classification, surface urban heat island (SUHI), and their spatial and temporal change patterns. In this study, a workflow is presented to assess the LC’s impact on SUHI, based on the visible and thermal infrared images with high spatial resolution captured by an unmanned airship in the central area of the Sino-Singapore Guangzhou Knowledge City in 2012 and 2015. Then, the accuracy assessment of LC classification and land surface temperature (LST) retrieval are performed. Finally, the commonly-used indexes in the field of satellites are applied to analyzing the spatial and temporal changes in the SUHI pattern on a local scale. The results show that the supervised maximum likelihood algorithm can deliver satisfactory overall accuracy and Kappa coefficient for LC classification; the root mean square error of the retrieved LST can reach 1.87 °C. Moreover, the LST demonstrates greater consistency with land cover type (LCT) and more fluctuation within an LCT on a local scale than on an urban scale. The normalized LST classified by the mean and standard deviation (STD) is suitable for the high-spatial situation; however, the thermal field level and the corresponded STD multiple need to be judiciously selected. This study exhibits an effective pathway to assess SUHI pattern and its changes using high-spatial-resolution images on a local scale. It is also indicated that proper landscape composition, spatial configuration and materials on a local scale exert greater impacts on SUHI.

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An integrated GIS-based Ordered Weighted Averaging analysis for solar energy evaluation in Iran: Current conditions and future planning

Cited by 104 publications

References 67 publications

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

Multidimensional evaluation of global investments on the renewable energy with the integrated fuzzy decision-making model under the hesitancy

Assessing the Impact of Land Cover Changes on Surface Urban Heat Islands with High-Spatial-Resolution Imagery on a Local Scale: Workflow and Case Study

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