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  • Abdel-Basset, M., Gamal, A., & ELkomy, O. M. (2021). Hybrid multi-criteria decision making approach for the evaluation of sustainable photovoltaic farms locations. Journal of Cleaner Production, 328(July), Article 129526. https://doi.org/10.1016/j.jclepro.2021.129526

  • Al-Shamisi, M. H., Assi, A. H., & Hejase, H. A. N. (2013). Artificial neural networks for predicting global solar radiation in Al Ain City - UAE. International Journal of Green Energy, 10(5), 443-456. https://doi.org/10.1080/15435075.2011.641187

  • Al Garni, H. Z., & Awasthi, A. (2017). Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia. Applied Energy, 206, 1225-1240. https://doi.org/10.1016/j.apenergy.2017.10.024

  • Allen, M. R., Pauline Dube, O., Solecki, W., Aragón-Durand, F., Cramer France, W., Humphreys, S., Dasgupta, P., Millar, R., Dube, O., Solecki, W., Aragón-Durand, F., Cramer, W., Humphreys, S., Kainuma, M., Kala, J., Mahowald, N., Mulugetta, Y., Perez, R., Wairiu, M., … & Waterfield, T. (2018). Special Report: Global warming of 1.5 oC. The Intergovernmental Panel on Climate Change. https://www.ipcc.ch/sr15/

  • Aly, A., Jensen, S. S., & Pedersen, A. B. (2017). Solar power potential of Tanzania: Identifying CSP and PV hot spots through a GIS multicriteria decision making analysis. Renewable Energy, 113, 159-175. https://doi.org/10.1016/J.RENENE.2017.05.077

  • Asuero, A. G., Sayago, A., & González, A. G. (2006). The correlation coefficient: An overview. Critical Reviews in Analytical Chemistry, 36(1), 41-59. https://doi.org/10.1080/10408340500526766

  • Bandyopadhyay, S. (2016). Ranking of suppliers with MCDA technique and probabilistic criteria. In 2016 International Conference on Data Science and Engineering (ICDSE) (pp. 1-5). IEEE Publication. https://doi.org/10.1109/ICDSE.2016.7823948

  • Bishop, M. P., & Giardino, J. R. (2021). Technology-driven geomorphology: introduction and overview. Treatise on Geomorphology, 1, 1-17. https://doi.org/10.1016/B978-0-12-818234-5.00171-1

  • Blest, D. C. (2000). Theory & methods: Rank correlation - An alternative measure. Australian and New Zealand Journal of Statistics, 42(1), 101-111. https://doi.org/10.1111/1467-842X.00110

  • Ceballos, B., Lamata, M. T., & Pelta, D. A. (2016). A comparative analysis of multi-criteria decision-making methods. Progress in Artificial Intelligence, 5, 315-322. https://doi.org/10.1007/s13748-016-0093-1

  • CEPERJ. (2019). Fundação Estadual de Estatísticas, Pesquisas e Formação de Servidores do Estado do Rio de Janeiro. [Foundation for Statistics, Research, and Training of Civil Servants of the State of Rio de Janeiro]. https://www.ceperj.rj.gov.br/wp-content/uploads/2021/07/PIB-ESTADUAL2018.pdf

  • CEPERJ. (2022a). Histórico e Características | CEPERJ. Fundação Estadual de Estatísticas, Pesquisas e Formação de Servidores Do Estado Do Rio de Janeiro [Foundation for Statistics, Research, and Training of Civil Servants of the State of Rio de Janeiro]. https://www.ceperj.rj.gov.br/?page_id=260

  • CEPERJ. (2022b). Regiões | CEPERJ. Fundação Estadual de Estatísticas, Pesquisas e Formação de Servidores Do Estado Do Rio de Janeiro [Foundation for Statistics, Research, and Training of Civil Servants of the State of Rio de Janeiro]. https://www.ceperj.rj.gov.br/?page_id=262

  • Cosenza, C. A. N., Doria, F. A., & Pessôa, L. A. M. (2015). Hierarchy models for the organization of economic spaces. Procedia Computer Science, 55, 82-91. https://doi.org/10.1016/j.procs.2015.07.010

  • Da Costa, J. P., & Soares, C. (2005). A weighted rank measure of correlation. Australian and New Zealand Journal of Statistics, 47(4), 515-529. https://doi.org/10.1111/j.1467-842X.2005.00413.x

  • Das, A. K., & Bhuyan, P. K. (2017). Hardcl method for defining LOS criteria of urban streets. International Journal of Civil Engineering, 15, 1077-1086. https://doi.org/10.1007/S40999-017-0207-6

  • de Souza, M. P., Moura, L. C. B., & Cosenza, C. A. N. (2019). Analysis to determine the most suitable location for a photovoltaic solar plant in the state of Rio De Janeiro, Brazil. International Journal of Development Research, 09(11), Article 17462.

  • de Souza, M. P., Moura, L. C. B., Cosenza, C. A. N., Brasil, C. N. F., Cosenza, H. J. S. R., Amaral, S. de M., & Dias, S. M. P. (2021a). Analysis to determine the most suitable location for a photovoltaic solar plant using coppe-cosenza method: Case study Rio De Janeiro. International Journal of Development Research, 11(04), 46378-46382.

  • de Souza, M. P., Moura, L. C. B., & Cosenza, C. A. N. (2021b). Análise para a localização ótima de uma usina solar fotovoltaica no estado do Rio de Janeiro [Analysis for the optimal location of a photovoltaic solar plant in the state of Rio de Janeiro]. Revista Brasileira de Energia, 27(4), 8-37. https://doi.org/10.47168/rbe.v27i4.491

  • de Souza, M. P., Moura, L. C. B., Cosenza, C. A. N., Dias, S. M. P., & Barata, P. R. (2021c, October 18-21). Determinação da Localização de uma Usina Solar Fotovoltaica com o Auxílio de Método de Decisão Multicritério [Determination of the location of a solar photovoltaic plant with the aid of a multicriteria decision method]. In Proceedings of the National Production Engineering Meeting - Enegep (pp. 1-12). Paraná, Brazil. https://doi.org/10.14488/enegep2021_tn_sto_362_1872_41849

  • Doorga, J. R. S., Rughooputh, S. D. D. V., & Boojhawon, R. (2019). Multi-criteria GIS-based modelling technique for identifying potential solar farm sites: A case study in Mauritius. Renewable Energy, 133, 1201-1219. https://doi.org/10.1016/j.renene.2018.08.105

  • EGPEnergia, & PUC-Rio. (2016). Atlas Rio Solar - Atlas Solarimétrico do Estado do Rio de Janeiro [Rio Solar Atlas - Solimeric Atlas of the State of Rio de Janeiro].

  • EPE. (2020a). Balanço energético nacional 2020 [National energy balance 2020]. Empresa de Pesquisa Energética. https://www.epe.gov.br/pt/publicacoes-dados-abertos/publicacoes/balanco-energetico-nacional-2020

  • EPE. (2020b). Plano decenal de expanção de energia 2029 [Ten-year energy expansion plan 2029]. Empresa de Pesquisa Energética. https://www.epe.gov.br/pt/publicacoes-dados-abertos/publicacoes/plano-decenal-de-expansao-de-energia-2029

  • EPE. (2016). Estudos da demanda de energia: Demanda de energia 2050 [Energy Demand Studies: Energy Demand 2050]. https://www.epe.gov.br/sites-pt/publicacoes-dados-abertos/publicacoes/PublicacoesArquivos/publicacao-227/topico-458/DEA 13-15 Demanda de Energia 2050.pdf

  • Fagin, R., Kumar, R., & Sivakumar, D. (2003). Comparing top k lists. Journal on Discrete Mathematics, 17(1), 134-160. https://doi.org/10.1137/S0895480102412856

  • Figueira, J., Greco, S., & Ehrogott, M. (2005). Multiple Criteria Decision Analysis: State of the Art Surveys. Springer. https://doi.org/10.1007/b100605

  • Figueira, J. R., Mousseau, V., & Roy, B. (2016). ELECTRE methods. In S. Greco, M. Ehrgott & J. Figueira (Eds.), Multiple Criteria Decision Analysis. International Series in Operations Research & Management Science (Vol. 233; pp. 155-185). Springer. https://doi.org/10.1007/978-1-4939-3094-4_5

  • Giamalaki, M., & Tsoutsos, T. (2019). Sustainable siting of solar power installations in the Mediterranean using a GIS/AHP approach. Renewable Energy, 141, 64-75. https://doi.org/10.1016/j.renene.2019.03.100

  • Guitouni, A., & Martel, J. M. (1998). Tentative guidelines to help choosing an appropriate MCDA method. European Journal of Operational Research, 109(2), 501-521. https://doi.org/10.1016/S0377-2217(98)00073-3

  • IBGE. (2022). Cidades e Estados [Cities and States]. IBGE. https://www.ibge.gov.br/cidades-e-estados/rj.html

  • IRENA. (2020). Renewable Power Generation Costs in 2019 - Key Findings. International Renewable Energy Agency. https://www.irena.org/publications/2020/Jun/Renewable-Power-Costs-in-2019

  • Ishizaka, A., & Siraj, S. (2018). Are multi-criteria decision-making tools useful? An experimental comparative study of three methods. European Journal of Operational Research, 264(2), 462-471. https://doi.org/10.1016/j.ejor.2017.05.041

  • Ivlev, I., Jablonsky, J., & Kneppo, P. (2016). Multiple-criteria comparative analysis of magnetic resonance imaging systems. International Journal of Medical Engineering and Informatics, 8(2), 124-141. https://doi.org/10.1504/IJMEI.2016.075757

  • Jain, A., Mehta, R., & Mittal, S. K. (2011). Modeling impact of solar radiation on site selection for solar pv power plants in India. International Journal of Green Energy, 8(4), 486-498. https://doi.org/10.1080/15435075.2011.576293

  • Janke, J. R. (2010). Multi-criteria GIS modeling of wind and solar farms in Colorado. Renewable Energy, 35(10), 2228-2234. https://doi.org/10.1016/j.renene.2010.03.014

  • Kizielewicz, B., Wątróbski, J., & Sałabun, W. (2020). Identification of relevant criteria set in the MCDA process - Wind farm location case study. Energies, 13(24), Article 6548. https://doi.org/10.3390/en13246548

  • Kolios, A., Mytilinou, V., Lozano-Minguez, E., & Salonitis, K. (2016). A comparative study of multiple-criteria decision-making methods under stochastic inputs. Energies, 9(7), 1-21. https://doi.org/10.3390/en9070566

  • Kwak, Y., Deal, B., & Heavisides, T. (2021). A large scale multi-criteria suitability analysis for identifying solar development potential: A decision support approach for the state of Illinois, USA. Renewable Energy, 177, 554-567. https://doi.org/10.1016/j.renene.2021.05.165

  • La Camera, F. (2020). Renewable Power Generation Costs in 2019. International Renewable Energy Agency. https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2018/Jan/IRENA_2017_Power_Costs_2018.pdf

  • Manson, S., Matson, L., Kernik, M., DeLuca, E., Bonsal, D., & Nelson, S. (2017). Mapping, Society, and Technology. Libraries Publishing.

  • Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustainable housing affordability. Omega, 59(Part B), 146-156. https://doi.org/10.1016/j.omega.2015.05.013

  • Ohunakin, O. S., & Saracoglu, B. O. (2018). A comparative study of selected multi-criteria decision-making methodologies for location selection of very large concentrated solar power plants in Nigeria. African Journal of Science, Technology, Innovation and Development, 10(5), 551-567. https://doi.org/10.1080/20421338.2018.1495305

  • Palmer, D., Gottschalg, R., & Betts, T. (2019). The future scope of large-scale solar in the UK: Site suitability and target analysis. Renewable Energy, 133, 1136-1146. https://doi.org/10.1016/j.renene.2018.08.109

  • Paramasivam, C. R., & Venkatramanan, S. (2019). Chapter 3 - An introduction to various spatial analysis techniques. In GIS and Geostatistical Techniques for Groundwater Science (pp. 23-30). Elsevier. https://doi.org/10.1016/B978-0-12-815413-7.00003-1

  • Pereira, E. B., Martins, F. R., Gonçalves, A. R., Costa, R. S., Lima, F. J. L. de, Rüther, R., Abreu, S. L. de, Tiepolo, G. M., Pereira, S. V., & Souza, J. G. de. (2017). Atlas Brasileiro Energia Solar 2a Edição [Brazilian Solar Energy Atlas 2nd Edition]. Instituto Nacional de Pesquisas Espaciais.

  • Qiu, T., Wang, L., Lu, Y., Zhang, M., Qin, W., Wang, S., & Wang, L. (2022). Potential assessment of photovoltaic power generation in China. Renewable and Sustainable Energy Reviews, 154, Article 111900. https://doi.org/10.1016/j.rser.2021.111900

  • Ramedani, Z., Omid, M., & Keyhani, A. (2013). Modeling solar energy potential in a Tehran province using artificial neural networks. International Journal of Green Energy, 10(4), 427-441. https://doi.org/10.1080/15435075.2011.647172

  • Razykov, T. M., Ferekides, C. S., Morel, D., Stefanakos, E., Ullal, H. S., & Upadhyaya, H. M. (2011). Solar photovoltaic electricity: Current status and future prospects. Solar Energy, 85(8), 1580-1608. https://doi.org/10.1016/j.solener.2010.12.002

  • Ribeiro, M. A., & Nunes, N. da S. (2019). Geografia do Estado do Rio de Janeiro [Geography of the State of Rio de Janeiro]. CECIERJ. https://canal.cecierj.edu.br/022020/6a6bfdba31d1653c8e1cb37b757a531a.pdf

  • Rios, R., & Duarte, S. (2021). Selection of ideal sites for the development of large-scale solar photovoltaic projects through analytical hierarchical process – Geographic information systems (AHP-GIS) in Peru. Renewable and Sustainable Energy Reviews, 149, Article 111310. https://doi.org/10.1016/j.rser.2021.111310

  • Rodgers, J. L., & Nicewander, W. A. (1988). Thirteen ways to look at the correlation coefficient. American Statistician, 42(1), 59-66. https://doi.org/10.1080/00031305.1988.10475524

  • Roy, B. (2016). Paradigms and challenges. In S. Greco, M. Ehrgott & J. Figueira (Eds.), Multiple Criteria Decision Analysis (pp 19-39). Springer. https://doi.org/10.1007/978-1-4939-3094-4_2

  • Sałabun, W., & Piegat, A. (2017). Comparative analysis of MCDM methods for the assessment of mortality in patients with acute coronary syndrome. Artificial Intelligence Review, 48, 557-571. https://doi.org/10.1007/s10462-016-9511-9

  • Sałabun, W., & Urbaniak, K. (2020). A new coefficient of rankings similarity in decision-making problems. In V. Krzhizhanovskaya, G. Závodszky, M. H. Lees, J. J. Dongarra, P. M. A. Sloot, S. Brissos & J. Teixeira (Eds.), Computational Science - ICCS 2020. ICCS 2020. Lecture Notes in Computer Science (pp. 632-645). Springer. https://doi.org/10.1007/978-3-030-50417-5_47

  • Sałabun, W., Watróbski, J., & Shekhovtsov, A. (2020). Are MCDA methods benchmarkable? A comparative study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II methods. Symmetry, 12(9), Article 1549. https://doi.org/10.3390/SYM12091549

  • San Cristóbal, J. R. (2011). Multi-criteria decision-making in the selection of a renewable energy project in Spain: The Vikor method. Renewable Energy, 36(2), 498-502. https://doi.org/10.1016/j.renene.2010.07.031

  • Sánchez-Lozano, J. M., García-Cascales, M. S., & Lamata, M. T. (2016a). Comparative TOPSIS-ELECTRE TRI methods for optimal sites for photovoltaic solar farms. Case study in Spain. Journal of Cleaner Production, 127, 387-398. https://doi.org/10.1016/j.jclepro.2016.04.005

  • Sánchez-Lozano, J. M., García-Cascales, M. S., & Lamata, M. T. (2016b). Comparative TOPSIS-ELECTRE TRI methods for optimal sites for photovoltaic solar farms. Case study in Spain. Journal of Cleaner Production, 127, 387-398. https://doi.org/10.1016/j.jclepro.2016.04.005

  • Schober, P., & Schwarte, L. A. (2018). Correlation coefficients: Appropriate use and interpretation. Anesthesia and Analgesia, 126(5), 1763-1768. https://doi.org/10.1213/ANE.0000000000002864

  • Scott, L. M. (2015). Spatial pattern, analysis of. In J. D. Wright (Ed), International Encyclopedia of the Social & Behavioral Sciences: Second Edition (Vol. 22). Elsevier. https://doi.org/10.1016/B978-0-08-097086-8.72064-2

  • Shao, M., Han, Z., Sun, J., Xiao, C., Zhang, S., & Zhao, Y. (2020). A review of multi-criteria decision-making applications for renewable energy site selection. Renewable Energy, 157, 377-403. https://doi.org/10.1016/j.renene.2020.04.137

  • Shekhovtsov, A., & Kolodziejczyk, J. (2020). Do distance-based multi-criteria decision analysis methods create similar rankings? Procedia Computer Science, 176, 3718-3729. https://doi.org/10.1016/j.procs.2020.09.015

  • Shieh, G. S. (1998). A weighted Kendall’s tau statistic. Statistics and Probability Letters, 39(1), 17-24. https://doi.org/10.1016/s0167-7152(98)00006-6

  • Shorabeh, S. N., Firozjaei, M. K., Nematollahi, O., Firozjaei, H. K., & Jelokhani-Niaraki, M. (2019). A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran. Renewable Energy, 143, 958-973. https://doi.org/10.1016/j.renene.2019.05.063

  • Sindhu, S., Nehra, V., & Luthra, S. (2017). Investigation of feasibility study of solar farms deployment using hybrid AHP-TOPSIS analysis: Case study of India. Renewable and Sustainable Energy Reviews, 73, 496-511. https://doi.org/10.1016/j.rser.2017.01.135

  • Taylor, R. (1990). Interpretation of the correlation coefficient: A basic review. Journal of Diagnostic Medical Sonography, 6(1), 35-39. https://doi.org/10.1177/875647939000600106

  • Thirugnanasambandam, M., Iniyan, S., & Goic, R. (2010). A review of solar thermal technologies. Renewable and Sustainable Energy Reviews, 14(1), 312-322. https://doi.org/10.1016/J.RSER.2009.07.014

  • Uyan, M. (2013). GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region Konya/Turkey. Renewable and Sustainable Energy Reviews, 28, 11-17. https://doi.org/10.1016/j.rser.2013.07.042

  • Van Haaren, R., & Fthenakis, V. (2011). GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for New York State. Renewable and Sustainable Energy Reviews, 15(7), 3332-3340. https://doi.org/10.1016/J.RSER.2011.04.010

  • Villacreses, G., Gaona, G., Martínez-Gómez, J., & Jijón, D. J. (2017). Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renewable Energy, 109, 275-286. https://doi.org/10.1016/j.renene.2017.03.041

  • Visser, H., & De Nijs, T. (2006). The map comparison kit. Environmental Modelling and Software, 21(3), 346-358. https://doi.org/10.1016/j.envsoft.2004.11.013

  • Wang, H., Pan, Y., & Luo, X. (2019). Integration of BIM and GIS in sustainable built environment: A review and bibliometric analysis. Automation in Construction, 103, 41-52. https://doi.org/10.1016/J.AUTCON.2019.03.005

  • Yushchenko, A., de Bono, A., Chatenoux, B., Patel, M. K., & Ray, N. (2018). GIS-based assessment of photovoltaic (PV) and concentrated solar power (CSP) generation potential in West Africa. Renewable and Sustainable Energy Reviews, 81(Part 2), 2088-2103. https://doi.org/10.1016/j.rser.2017.06.021

  • Zanakis, S. H., Solomon, A., Wishart, N., & Dublish, S. (1998). Multi-attribute decision making: A simulation comparison of select methods. European Journal of Operational Research, 107(3), 507-529. https://doi.org/10.1016/S0377-2217(97)00147-1

  • Zar, J. H. (1972). Significance testing of the Spearman rank correlation coefficient. Journal of the American Statistical Association, 67(339), 578-580. https://doi.org/10.1080/01621459.1972.10481251

  • Zar, J. H. (2005). Spearman rank correlation. In Encyclopedia of Biostatistics. Wiley. https://doi.org/10.1002/0470011815.B2A15150

  • Zoghi, M., Ehsani, A. H., Sadat, M., Amiri, M. J., & Karimi, S. (2017). Optimization solar site selection by fuzzy logic model and weighted linear combination method in arid and semi-arid region: A case study Isfahan-IRAN. Renewable and Sustainable Energy Reviews, 68(Part 2), 986-996. https://doi.org/10.1016/j.rser.2015.07.014

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