climate zoning; clustering; microclimate; principal component analysis; K-means
Abstract :
[en] Climatic classification is essential for evaluating climate parameters that allow sustainable urban planning and resource management in countries with difficult access to meteorological information. Clustering methods are on trend to identify climate zoning; however, for microclimate, it is necessary to apply a double clustering technique to reduce the variability from former clusters. This research raised a climate classification of an emerging country, Colombia, using climatological models based on freely available satellite image data. A double clustering approach was applied, including climatological, geographic, and topographic patterns. The research was divided into four stages, covering the collection and selection of climatic and geographic data, and multivariate statistical analysis including principal components analysis (PCA) and agglomerative hierarchical clustering (HAC). The meteorological data were from reliable sources from the Center for Hydrometeorology and Remote Sensing (CHRS) and the National Renewable Energy Laboratory (NREL). The results showed that a total of 17 microclimates distributed across the country were identified, each characterized by a different threshold of the climatic and geographic factors evaluated. This subdivision provided a detailed understanding of local climatic conditions, especially in the mountain chains of the Andes.
Disciplines :
Architecture
Author, co-author :
Mejía-Parada, Cristian ; Research Group on Threats, Vulnerability and Risks to Natural Phenomena, Faculty of Engineering, Research and Development University (UDI), Bucaramanga 680001, Colombia
Mora-Ruiz, Viviana ; Research Group on Threats, Vulnerability and Risks to Natural Phenomena, Faculty of Engineering, Research and Development University (UDI), Bucaramanga 680001, Colombia
Soto-Paz, Jonathan ; Research Group on Threats, Vulnerability and Risks to Natural Phenomena, Faculty of Engineering, Research and Development University (UDI), Bucaramanga 680001, Colombia
Parra-Orobio, Brayan A. ; GE&TES Research Group, Department of Environmental and Health Sciences, Popular University of Cesar, Aguachica 205010, Colombia
Attia, Shady ; Université de Liège - ULiège > Département ArGEnCo > Techniques de construction des bâtiments
Language :
English
Title :
Microclimate Zoning Based on Double Clustering Method for Humid Climates with Altitudinal Gradient Variations: A Case Study of Colombia
Publication date :
14 June 2024
Journal title :
Atmosphere
eISSN :
2073-4433
Publisher :
MDPI AG
Volume :
15
Issue :
6
Pages :
709
Peer reviewed :
Peer Reviewed verified by ORBi
Development Goals :
11. Sustainable cities and communities 13. Climate action
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Perera N.G.R. Emmanuel R. A “Local Climate Zone” Based Approach to Urban Planning in Colombo, Sri Lanka Urban. Clim. 2018 23 188 203 10.1016/J.UCLIM.2016.11.006
Reckien D. Salvia M. Heidrich O. Church J.M. Pietrapertosa F. De Gregorio-Hurtado S. D’Alonzo V. Foley A. Simoes S.G. Krkoška Lorencová E. et al. How Are Cities Planning to Respond to Climate Change? Assessment of Local Climate Plans from 885 Cities in the EU-28 J. Clean. Prod. 2018 191 207 219 10.1016/J.JCLEPRO.2018.03.220
Davidson A.S. Malet-Damour B. Praene J.P. A New Microclimate Zoning Method Based on Multivariate Statistics: The Case of Reunion Island Urban. Clim. 2023 52 101687 10.1016/j.uclim.2023.101687
Mejía-Parada C. Mora-Ruiz V. Attia S. Bioclimatic Design Recommendations for Novel Cluster Analysis-Based Mapping for Humid Climates with Altitudinal Gradient Variations J. Build. Eng. 2024 82 108262 10.1016/j.jobe.2023.108262
Ascencio-Vásquez J. Brecl K. Topič M. Methodology of Köppen-Geiger-Photovoltaic Climate Classification and Implications to Worldwide Mapping of PV System Performance Sol. Energy 2019 191 672 685 10.1016/J.SOLENER.2019.08.072
Attia S. Lacombe T. Architect-Friendly Climate Analysis Tool for Bioclimatic Design in Hot Humid Climates Proceedings of the Building Simulation 2019: 16th Conference of International Building Performance Simulation Association Rome, Italy 2–4 September 2019 Volume 7 4785 4792
Sengupta M. Xie Y. Lopez A. Habte A. Maclaurin G. Shelby J. The National Solar Radiation Data Base (NSRDB) Renew. Sustain. Energy Rev. 2018 89 51 60 10.1016/J.RSER.2018.03.003
Nguyen P. Ombadi M. Gorooh V.A. Shearer E.J. Sadeghi M. Sorooshian S. Hsu K. Bolvin D. Ralph M.F. Persiann Dynamic Infrared–Rain Rate (PDIR-Now): A near-Real-Time, Quasi-Global Satellite Precipitation Dataset J. Hydrometeorol. 2020 21 2893 2906 10.1175/JHM-D-20-0177.1 34158807
Walsh A. Cóstola D. Labaki L.C. Review of Methods for Climatic Zoning for Building Energy Efficiency Programs Build. Environ. 2017 112 337 350 10.1016/J.BUILDENV.2016.11.046
Peel M.C. Finlayson B.L. McMahon T.A. Updated World Map of the Köppen-Geiger Climate Classification Hydrol. Earth Syst. Sci. 2007 11 1633 1644 10.5194/HESS-11-1633-2007
Beck H.E. Zimmermann N.E. McVicar T.R. Vergopolan N. Berg A. Wood E.F. Present and Future Köppen-Geiger Climate Classification Maps at 1-Km Resolution Sci. Data 2018 5 180214 10.1038/SDATA.2018.214
Martinopoulos G. Alexandru A. Papakostas K.T. Mapping Temperature Variation and Degree-Days in Metropolitan Areas with Publicly Available Sensors Urban. Clim. 2019 28 100464 10.1016/j.uclim.2019.100464
Omarov B. Memon S.A. Kim J. A Novel Approach to Develop Climate Classification Based on Degree Days and Building Energy Performance Energy 2023 267 126514 10.1016/j.energy.2022.126514
Roshan G. Farrokhzad M. Attia S. Climatic Clustering Analysis for Novel Atlas Mapping and Bioclimatic Design Recommendations Indoor Built Environ. 2021 30 313 333 10.1177/1420326X19888572
Manzano-Agugliaro F. Montoya F.G. Sabio-Ortega A. García-Cruz A. Review of Bioclimatic Architecture Strategies for Achieving Thermal Comfort Renew. Sustain. Energy Rev. 2015 49 736 755 10.1016/j.rser.2015.04.095
Liu S. Shi Q. Local Climate Zone Mapping as Remote Sensing Scene Classification Using Deep Learning: A Case Study of Metropolitan China ISPRS J. Photogramm. Remote Sens. 2020 164 229 242 10.1016/j.isprsjprs.2020.04.008
Kotharkar R. Bagade A. Local Climate Zone Classification for Indian Cities: A Case Study of Nagpur Urban. Clim. 2018 24 369 392 10.1016/j.uclim.2017.03.003
Wicki A. Parlow E. Attribution of Local Climate Zones Using a Multitemporal Land Use/Land Cover Classification Scheme J. Appl. Remote Sens. 2017 11 026001 10.1117/1.jrs.11.026001
Nadarajah P.D. Singh M.K. Mahapatra S. Pajek L. Košir M. Bioclimatic Classification for Building Energy Efficiency Using Hierarchical Clustering: A Case Study for Sri Lanka J. Build. Eng. 2023 83 108388 10.1016/j.jobe.2023.108388
Praene J.-P. Malet-Damour B. Harimisa Radanielina M. Fontaine L. Riviere G. Philippe Praene J. Rivière G. GIS-Based Approach to Identify Climatic Zoning: A Hierarchical Clustering on Principal Component Analysis GIS-Based Approach to Define Climatic Zoning: A Hierarchical Clustering on Principal Component Analysis Build. Environ. 2019 164 106330 10.1016/j.buildenv.2019.106330
Zscheischler J. Mahecha M.D. Harmeling S. Climate Classifications: The Value of Unsupervised Clustering Procedia Comput. Sci. 2012 9 897 906 10.1016/J.PROCS.2012.04.096
Li T. Rezaeipanah A. Tag El Din E.S.M. An Ensemble Agglomerative Hierarchical Clustering Algorithm Based on Clusters Clustering Technique and the Novel Similarity Measurement J. King Saud. Univ. Comput. Inf. Sci. 2022 34 3828 3842 10.1016/j.jksuci.2022.04.010
Bienvenido-Huertas D. Marín-García D. Carretero-Ayuso M.J. Rodríguez-Jiménez C.E. Climate Classification for New and Restored Buildings in Andalusia: Analysing the Current Regulation and a New Approach Based on k-Means J. Build. Eng. 2021 43 102829 10.1016/J.JOBE.2021.102829
Sinaga K.P. Yang M.S. Unsupervised K-Means Clustering Algorithm IEEE Access 2020 8 80716 80727 10.1109/ACCESS.2020.2988796
Yuan C. Yang H. Research on K-Value Selection Method of K-Means Clustering Algorithm J 2019 2 226 235 10.3390/j2020016
Bechtel B. Daneke C. Classification of Local Climate Zones Based on Multiple Earth Observation Data IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2012 5 1191 1202 10.1109/JSTARS.2012.2189873
Grupo de Climatología y Agrometeoreología-Subdirección de Metereología, IDEAM Clasificaciones Climaticas Colombia Proceedings of the Segundo Congreso Nacional del Clima Bogotá, Colombia 3–5 August 2011
IDEAM Evolución Del Índice de Confort Térmico Por Periodos 1971–2000. Segunda Comunicación Nacional ante la Convención Marco de las Naciones Unidad sobre Cambio Climático Instituto de Hidrología, Meteorología y Estudios Ambientales—IDEAM Bogotá, Colombia 2010
Ministerio de Ambiente y Desarrollo Sostenible Criterios Ambientales Para El Diseño y Construccion de Vivienda Urbana Ministerio de Ambiente y Desarrollo Sostenible Bogotá, Colombia 2012 9789588491585
Gillies S. Rasterio Documentat 23rd ed. MapBox San Francisco, CA, USA 2019
Brimicombe C. Di Napoli C. Quintino T. Pappenberger F. Cornforth R. Cloke H.L. Thermofeel: A Python Thermal Comfort Indices Library SoftwareX 2022 18 101005 10.1016/j.softx.2022.101005
Li H. Huang J. Hu Y. Wang S. Liu J. Yang L. A New TMY Generation Method Based on the Entropy-Based TOPSIS Theory for Different Climatic Zones in China Energy 2021 231 120723 10.1016/j.energy.2021.120723
Tadić L. Bonacci O. Brleković T. An Example of Principal Component Analysis Application on Climate Change Assessment Theor. Appl. Climatol. 2019 138 1049 1062 10.1007/S00704-019-02887-9
Jollife I.T. Cadima J. Principal Component Analysis: A Review and Recent Developments Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2016 374 20150202 10.1098/RSTA.2015.0202
Kaiser H.F. The Application of Electronic Computers to Factor Analysis Educ. Psychol. Meas. 1960 20 141 151 10.1177/001316446002000116
Xiong J. Yao R. Grimmond S. Zhang Q. Li B. A Hierarchical Climatic Zoning Method for Energy Efficient Building Design Applied in the Region with Diverse Climate Characteristics Energy Build. 2019 186 355 367 10.1016/j.enbuild.2019.01.005
Dinh D.T. Fujinami T. Huynh V.N. Estimating the Optimal Number of Clusters in Categorical Data Clustering by Silhouette Coefficient Knowledge and Systems Sciences. KSS 2019 Communications in Computer and Information Science Springer Singapore 2019 Volume 1103 1 17
Brusco M.J. Steinley D. A Comparison of Heuristic Procedures for Minimum Within-Cluster Sums of Squares Partitioning Psychometrika 2007 72 583 600 10.1007/s11336-007-9013-4
Semahi S. Benbouras M.A. Mahar W.A. Zemmouri N. Attia S. Development of Spatial Distribution Maps for Energy Demand and Thermal Comfort Estimation in Algeria Sustainability 2020 12 6066 10.3390/su12156066
Gupta R. Mathur J. Garg V. Assessment of Climate Classification Methodologies Used in Building Energy Efficiency Sector Energy Build. 2023 298 113549 10.1016/j.enbuild.2023.113549
Oliveira A. Lopes A. Niza S. Local Climate Zones in Five Southern European Cities: An Improved GIS-Based Classification Method Based on Copernicus Data Urban. Clim. 2020 33 100631 10.1016/j.uclim.2020.100631
Bechtel B. Alexander P.J. Böhner J. Ching J. Conrad O. Feddema J. Mills G. See L. Stewart I. Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities ISPRS Int. J. Geoinf. 2015 4 199 219 10.3390/ijgi4010199
Abbasi F. Bazgeer S. Kalehbasti P.R. Oskoue E.A. Haghighat M. Kalehbasti P.R. New Climatic Zones in Iran: A Comparative Study of Different Empirical Methods and Clustering Technique Theor. Appl. Climatol. 2022 147 47 61 10.1007/s00704-021-03785-9
Sathiaraj D. Huang X. Chen J. Predicting Climate Types for the Continental United States Using Unsupervised Clustering Techniques Environmetrics 2019 30 e2524 10.1002/ENV.2524
Balogun I.A. Daramola M.T. The Outdoor Thermal Comfort Assessment of Different Urban Configurations within Akure City, Nigeria Urban. Clim. 2019 29 100489 10.1016/j.uclim.2019.100489
Attia S. Lacombe T. Rakotondramiarana H.T. Garde F. Roshan G.R. Analysis Tool for Bioclimatic Design Strategies in Hot Humid Climates Sustain. Cities Soc. 2019 45 8 24 10.1016/j.scs.2018.11.025
Daemei A.B. Eghbali S.R. Khotbehsara E.M. Bioclimatic Design Strategies: A Guideline to Enhance Human Thermal Comfort in Cfa Climate Zones J. Build. Eng. 2019 25 100758 10.1016/j.jobe.2019.100758
Li Z. Feng X. Fan X. Sun J. Fang Z. Effect of Direct Solar Projected Area Factor on Outdoor Thermal Comfort Evaluation: A Case Study in Shanghai, China Urban. Clim. 2022 41 101033 10.1016/J.UCLIM.2021.101033
Anderson R. Bayer P.E. Edwards D. Climate Change and the Need for Agricultural Adaptation Curr. Opin. Plant Biol. 2020 56 197 202 10.1016/J.PBI.2019.12.006 32057694
Kogo B.K. Kumar L. Koech R. Climate Change and Variability in Kenya: A Review of Impacts on Agriculture and Food Security Environ. Dev. Sustain. 2021 23 23 43 10.1007/S10668-020-00589-1
Attia S. Eleftheriou P. Xeni F. Morlot R. Ménézo C. Kostopoulos V. Betsi M. Kalaitzoglou I. Pagliano L. Cellura M. et al. Overview and Future Challenges of Nearly Zero Energy Buildings (NZEB) Design in Southern Europe Energy Build. 2017 155 439 458 10.1016/J.ENBUILD.2017.09.043
Santos-Herrero J.M. Lopez-Guede J.M. Flores-Abascal I. Modeling, Simulation and Control Tools for NZEB: A State-of-the-Art Review Renew. Sustain. Energy Rev. 2021 142 110851 10.1016/J.RSER.2021.110851
Belussi L. Barozzi B. Bellazzi A. Danza L. Devitofrancesco A. Fanciulli C. Ghellere M. Guazzi G. Meroni I. Salamone F. et al. A Review of Performance of Zero Energy Buildings and Energy Efficiency Solutions J. Build. Eng. 2019 25 100772 10.1016/j.jobe.2019.100772
Dnp Colombia, Potencial Mundial De La Vida Bases Del Plan Nacional de Desarrollo 2022–2026 Departamento Nacional de Planeación Bogotá, Colombia 2022
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.
