Mostrar el registro sencillo del ítem

Land surface temperature and vegetation index as a proxy to microclimate

dc.contributor.authorMaroni, Danielaspa
dc.contributor.authorTibério Cardoso, Gracespa
dc.contributor.authorNeckel, Alcindospa
dc.contributor.authorStolfo Maculan, Laérciospa
dc.contributor.authorL.S. Oliveira, Marcosspa
dc.contributor.authorThaines Bodah, Elianespa
dc.contributor.authorWilliam Bodah, Brianspa
dc.contributor.authorSantosh, M.spa
dc.date.accessioned2021-08-02T12:57:19Z
dc.date.available2021-08-02T12:57:19Z
dc.date.issued2021-06-04
dc.identifier.urihttps://hdl.handle.net/11323/8499spa
dc.description.abstractThe effect of global climate change on the temperature of urban areas has become more pronounced in the past couple decades, impacting population and quality of life. The United Nations (UN), the National Aeronautics and Space Administration (NASA) and the Intergovernmental Panel on Climate Change (IPCC) have emphasized the impact of urban structures on microclimatic. A better understanding of these effects is important to formulate effective strategies that would contribute to address the impacts of increased urban growth. Here we address a case study of the Vila Rodrigues neighborhood, located in Passo Fundo City in southern Brazil to analyze the variations of emissivity, temperature and vegetation of the terrestrial surface, with influence of buildings. We employ Landsat satellite images, and unpublished data provided by the NASA, interpolated and classified in the QGIS software, using Bands 4, 5 and 10, converted to Gray Level (NC). This procedure allowed the spectral radiance of the reflectance temperature to be obtained. The Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) were used, with correction of emissivity and spectral error, in the identification of the surface temperature of different areas in the Villa Rodrigues. The results showed a total variation of 3.86ºC among the sampled points, which is increased by the difference in significance of the thermal balance in urban areas under open sky with buildings. We suggest that green areas and parks with abundant vegetative cover and the application of new building materials in future constructions would help to improve the urban climate, and such regulation of the local temperature on global scale is an effective step towards addressing the adverse effects from climate change.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.sourceJournal of Environmental Chemical Engineeringspa
dc.subjectEngineeringspa
dc.subjectMicroclimatespa
dc.subjectRemote Sensingspa
dc.subjectAir Temperaturespa
dc.subjectGlobal environmentspa
dc.titleLand surface temperature and vegetation index as a proxy to microclimatespa
dc.typeArtículo de revistaspa
dc.source.urlhttps://www.sciencedirect.com/science/article/abs/pii/S2213343721007739?via%3Dihubspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.jece.2021.105796spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.relation.referencesM. Bonatti, M.A. Lana, L.R. D’agostini, A.C.F. de. Vasconcelos, S. Sieber, L. Eufemia, T. da. Silva-rosa, S.L. Schlindwein Social representations of climate change and climate adaptation plans in southern Brazil: challenges of genuine participation Urban Clim., 29 (2019), Article 100496, 10.1016/j.uclim.2019.100496spa
dc.relation.referencesA. Neckel, J.L. da. Silva, P.P. Saraiva, H.A. Kujawa, J. Araldi, E.P. Paladini Estimation of the economic value of urban parks in Brazil, the case of the City of Passo Fundo J. Clean. Prod., 264 (2020), Article 121369, 10.1016/j.jclepro.2020.121369spa
dc.relation.referencesL.F.O. Silva, D. Pinto, A. Neckel, G.L. Dotto, M.L.S. Oliveira The impact of air pollution on the rate of degradation of the fortress of Florianópolis Island, Brazil Chemosphere, 251 (2020) (2020), Article 126838, 10.1016/j.chemosphere.2020.126838spa
dc.relation.referencesH. Li, Y. Zhou, G. Jia, K. Zhao, J. Dong Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model Geosci. Front. (2021), Article 101141, 10.1016/j.gsf.2021.101141spa
dc.relation.referencesP.B. Cobbinah Urban resilience in climate change hotspot Land Use Policy, 100 (2021), Article 104948, 10.1016/j.landusepol.2020.104948spa
dc.relation.referencesPBMC, Brazilian Panel on Climate Change, In: Climate Change and Cities: Special Report of the Brazilian (Rio de Janeiro, Brazil), 2016. https://agenciabrasil.ebc.com.br/en/geral/noticia/2017–06/brazils-coastal-cities-more-vulnerable-climate-change.spa
dc.relation.referencesJ.V. de. Oliveira, J.C.P. Cohen, M. Pimentel, H.L.Z. Tourinho, M.A. Lôbo, G. Sodré, A. Abdala Urban climate and environmental perception about climate change in Belém, Pará, Brazil Urban Clim., 31 (2020), Article 100579, 10.1016/j.uclim.2019.100579spa
dc.relation.referencesT.K. Dhar, L. Khirfan A multi-scale and multi-dimensional framework for enhancing the resilience of urban form to climate change Urban Clim., 19 (2017), pp. 72-91, 10.1016/j.uclim.2016.12.004spa
dc.relation.referencesR.M. de. Carvalho, C.F. Szlafsztein Urban vegetation loss and ecosystem services: The influence on climate regulation and noise and air pollution Environ. Pollut., 245 (2019), pp. 844-852, 10.1016/j.envpol.2018.10.114spa
dc.relation.referencesC.M. Nascimento, W..de.S. Mendes, N.E.Q. Silvero, R.R. Poppiel, V.M. Sayão, A.C. Dotto, N.V..dos. Santos, M.T.A. Amorim, J.A.M. Demattê, Soil degradation index developed by multitemporal remote sensing images, climate variables, terrain and soil attributes, J. Environ. Manage. 277 (2021), 111316. https://ezproxy.cuc.edu.co:2067/10.1016/j.jenvman.2020.111316.spa
dc.relation.referencesH. Bherwani, A. Singh, R. Kumar Assessment methods of urban microclimate and its parameters: a critical review to take the research from lab to land Urban Clim., 34 (2020), Article 100690, 10.1016/j.uclim.2020.100690spa
dc.relation.referencesM.E. Gavito, H. Paz, F. Barragán, I. Siddique, F. Arreola-Villa, F. Pineda-García, P. Balvanera Indicators of integrative recovery of vegetation, soil and microclimate in successional fields of a tropical dry forest For. Ecol. Manag., 479 (2021), Article 118526, 10.1016/j.foreco.2020.118526spa
dc.relation.referencesZ.L. Li, B.H. Tang, H. Wu, H. Ren, G. Yan, Z. Wan, I.F. Trigo, J.A. Sobrino Satellite-derived land surface temperature: current status and perspectives Remote Sens. Environ., 131 (2013), pp. 14-37, 10.1016/j.rse.2012.12.008spa
dc.relation.referencesR.S. Chatterjee, N. Singh, S. Thapa, D. Sharma, D. Kumar Retrieval of land surface temperature (LST) from landsat TM6 and TIRS data by single channel radiative transfer algorithm using satellite and ground-based inputs Int. J. Appl. Earth Obs. Geoinf., 58 (2017), pp. 264-277, 10.1016/j.jag.2017.02.017spa
dc.relation.referencesM. Das, A. Das Assessing the relationship between local climatic zones (LCZs) and land surface temperature (LST) – A case study of Sriniketan-Santiniketan Planning Area (SSPA), West Bengal, India Urban Clim., 32 (2020), Article 100591, 10.1016/j.uclim.2020.100591spa
dc.relation.referencesT.D. Mushore, J. Odindi, T. Dube, T.N. Matongera, O. Mutanga Remote sensing applications in monitoring urban growth impacts on in-and-out door thermal conditions: a review R. S. A. S. E., 8 (2017), pp. 83-93, 10.1016/j.rsase.2017.08.001spa
dc.relation.referencesQ. Vanhellemont, Combined land surface emissivity and temperature estimation from Landsat 8 OLI and TIRS. ISPRS J. Photogramm, Remote Sens. 166, 2020, 390–402. https://ezproxy.cuc.edu.co:2067/10.1016/j.isprsjprs.2020.06.007.spa
dc.relation.referencesJ. Peng, J. Jia, Y. Liu, H. Li, J. Wu Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas Remote Sens. Environ., 215 (2018), pp. 255-267, 10.1016/j.rse.2018.06.010spa
dc.relation.referencesF. Zullo, G. Fazio, B. Romano, A. Marucci, L. Fiorini Effects of urban growth spatial pattern (UGSP) on the land surface temperature (LST): a study in the Po Valley (Italy) Sci. Total Environ., 650 (2019), pp. 1740-1751, 10.1016/j.scitotenv.2018.09.331spa
dc.relation.referencesC. Alexander Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST) Int. J. Appl. Earth Obs. Geoinf., 86 (2020), Article 102013, 10.1016/j.jag.2019.102013spa
dc.relation.referencesL. Sheng, X. Tang, H. You, Q. Gu, H. Hu Comparison of the urban heat island intensity quantified by using air temperature and Landsat land surface temperature in Hangzhou, China Ecol. Indic., 72 (2017), pp. 738-746, 10.1016/j.ecolind.2016.09.009spa
dc.relation.referencesB.T.W. Putra, P. Soni Evaluating NIR-Red and NIR-Red edge external filters with digital cameras for assessing vegetation indices under different illumination Infrared Phys. Technol., 81 (2017), pp. 148-156, 10.1016/j.infrared.2017.01.007spa
dc.relation.referencesD. Gozdowski, M. Stępień, E. Panek, J. Varghese, E. Bodecka, J. Rozbicki, S. Samborski Comparison of winter wheat NDVI data derived from Landsat 8 and active optical sensor at field scale Remote Sens. Appl. Soc. Environ., 20 (2020), Article 100409, 10.1016/j.rsase.2020.100409spa
dc.relation.referencesL. Costa, L. Nunes, Y. Ampatzidis A new visible band index (vNDVI) for estimating NDVI values on RGB images utilizing genetic algorithms Comput. Electron. Agric., 172 (2020), Article 105334, 10.1016/j.compag.2020.105334spa
dc.relation.referencesA. Balew, T. Korme Monitoring land surface temperature in Bahir Dar city and its surrounding using Landsat images Egypt. J. Remote. Sens. Space Sci. (2020), pp. 1-16, 10.1016/j.ejrs.2020.02.001spa
dc.relation.referencesB.J. He, Z.Q. Zhao, L.D. Shen, H.B. Wang, L.G. Li An approach to examining performances of cool/hot sources in mitigating/enhancing land surface temperature under different temperature backgrounds based on Landsat 8 image Sustain. Cities Soc., 44 (2019), pp. 416-427, 10.1016/j.scs.2018.10.049spa
dc.relation.referencesA. Guo, J. Yang, W. Sun, X. Xiao, J.X. Cecilia, C. Jin, X. Li Impact of urban morphology and landscape characteristics on spatiotemporal heterogeneity of land surface temperature Sustain. Cities Soc., 63 (2020), Article 102443, 10.1016/j.scs.2020.102443spa
dc.relation.referencesK.J. Gohain, P. Mohammad, A. Goswami Assessing the impact of land use land cover changes on land surface temperature over Pune city, India Quat. Int., 1 (2020), pp. 1-38, 10.1016/j.quaint.2020.04.052spa
dc.relation.referencesT. Adulkongkaew, T. Satapanajaru, S. Charoenhirunyingyos, W. Singhirunnusorn Effect of land cover composition and building configuration on land surface temperature in an urban-sprawl city, case study in Bangkok Metropolitan Area, Thailand Heliyon, 6 (2020), p. 04485, 10.1016/j.heliyon.2020.e04485spa
dc.relation.referencesM. Lemus-Canovas, J. Martin-Vide, M. Moreno-Garcia, J.A. Lopez-Bustins Estimating Barcelona's metropolitan daytime hot and cold poles using Landsat-8 Land Surface Temperature Sci. Total Environ., 699 (2020), Article 134307, 10.1016/j.scitotenv.2019.134307spa
dc.relation.referencesL.S. Ferreira, D.H.S. Duarte Exploring the relationship between urban form, land surface temperature and vegetation indices in a subtropical megacity Urban Clim., 27 (2019), pp. 105-123, 10.1016/j.uclim.2018.11.002spa
dc.relation.referencesR.L.N. Wanderley, L.M. Domingues, C.A. Joly, H.R. da. Rocha Relationship between land surface temperature and fraction of anthropized area in the Atlantic forest region, Brazil Plos One, 14 (2019), pp. 1-19, 10.1371/journal.pone.0225443spa
dc.relation.referencesW.L.F. Correia Filho, D. de, B. Santiago, J.F. de. Oliveira-Jðnior, C.A. da. Silva Junior Impact of urban decadal advance on land use and land cover and surface temperature in the city of Maceió, 87, Land Use Policy,, Brazil (2019), 10.1016/j.landusepol.2019.104026spa
dc.relation.referencesR.A. Carrasco, M.M.F. Pinheiro, J. Marcato Junior, R.E. Cicerelli, P.A. Silva, L.P. Osco, A.P.M. Ramos Land use/land cover change dynamics and their effects on land surface temperature in the western region of the state of São Paulo, Brazil Reg. Environ. Change, 20 (2020), pp. 1-12, 10.1007/s10113-020-01664-zspa
dc.relation.referencesC.I. Portela, K.G. Massi, T. Rodrigues, E. Alcântara Impact of urban and industrial features on land surface temperature: evidences from satellite thermal indices Sustain. Cities Soc., 56 (2020), Article 102100, 10.1016/j.scs.2020.102100spa
dc.relation.referencesV.M. Sayão, N.V. dos. Santos, W. de, S. Mendes, K.P.P. Marques, J.L. Safanelli, R.R. Poppiel, J.A.M. Demattê Land use/land cover changes and bare soil surface temperature monitoring in southeast Brazil Geo. Reg., 22 (2020), Article e00313, 10.1016/j.geodrs.2020.e00313spa
dc.relation.referencesIbge, Brazilian Institute of Geography and Statistics, Demographic Data of 2020 - Brazil, 2021. https://cidades.ibge.gov.br/brasil/rs/passo-fundo/panorama.spa
dc.relation.referencesEmbrapa, Climate of Passo Fundo in Brazil, 2020. http://www.cnpt.embrapa.br/pesquisa/agromet/app/principal/boletim.php.spa
dc.relation.referencesL.S. Maculan, V.R. Tângari Structuring elements of the territory and the effects on the urban border of Passo Fundo R. Nac. Geren. Cid., 8 (2020), pp. 18-35, 10.17271/2318847285720202284spa
dc.relation.referencesA. Chemura, O. Mutanga, T. Dube Integrating age in the detection and mapping of incongruous patches in coffee (Coffea arabica) plantations using multi-temporal Landsat 8 NDVI anomalies Int. J. Appl. Earth Obs. Geoinf., 57 (2017), pp. 1-13, 10.1016/j.jag.2016.12.007spa
dc.relation.referencesV. Rodriguez-Galiano, E. Pardo-Iguzquiza, M. Sanchez-Castillo, M. Chica-Olmo, M. Chica-Rivas Downscaling Landsat 7 ETM+ thermal imagery using land surface temperature and NDVI images Int. J. Appl. Earth Obs. Geoinf., 18 (2012), pp. 515-527, 10.1016/j.jag.2011.10.002spa
dc.relation.referencesS. Roy, S. Pandit, E.A. Eva, Md.S.H. Bagmar, M. Papia, L. Banik, T. Dube, F. Rahman, M.A. Razi Examining the nexus between land surface temperature and urban growth in Chattogram Metropolitan Area of Bangladesh using long term Landsat series data Urban Clim., 32 (2020), Article 100593, 10.1016/j.uclim.2020.100593spa
dc.relation.referencesEmbrapa, Meteorological measurements of Brazil, 2020. http://www.cnpt.embrapa.br/pesquisa/agromet/app/principal/graficos.php.spa
dc.relation.referencesM.L. Plume SPSS (Statistical Package for the Social Sciences) Encycl. Inf. Syst. (2003), pp. 187-196, 10.1016/b0-12-227240-4/00166-0spa
dc.relation.referencesD. Bera, Nd Chatterjee, S. Bera Comparative performance of linear regression, polynomial regression and generalized additive model for canopy cover estimation in the dry deciduous forest of West Bengal R. S. A. S. E., 22 (2021), Article 100502, 10.1016/j.rsase.2021.100502spa
dc.relation.referencesK. Pandiaraj, P. Sivakumar, K.J. Prakash Machine learning based effective linear regression model for TSV layer assignment in 3DIC Microprocess. Microsyst., 83 (2021), Article 103953, 10.1016/j.micpro.2021.103953spa
dc.relation.referencesB. Djordjević, A.S. Mane, E. Krmac Analysis of dependency and importance of key indicators for railway sustainability monitoring: a new integrated approach with dea and pearson correlation Res. Transp. Bus. Manag. (2021), Article 100650, 10.1016/j.rtbm.2021.100650spa
dc.relation.referencesW. Zeng, T. Lu, Z. Liu, Q. Xu, H. Peng, C. Li, S. Yang, F. Yao Research on a laser ultrasonic visualization detection method for human skin tumors based on pearson correlation coefficient Opt. Laser Technol., 141 (2021), Article 107117, 10.1016/j.optlastec.2021.107117spa
dc.relation.referencesM. Baak, R. Koopman, H. Snoek, S. Klous A new correlation coefficient between categorical, ordinal and interval variables with Pearson characteristics Comput. Stat. Data Anal., 152 (2020), Article 107043, 10.1016/j.csda.2020.107043spa
dc.relation.referencesT. Fu, X. Tang, Z. Cai, Y. Zuo, Y. Tang, X. Zhao Effect of chemical composition of black tea infusion on the color of milky tea Food Res Int, 139 (2021), Article 109945, 10.1016/j.porgcoat.2019.105459spa
dc.relation.referencesJ. Peng, Y. Hu, J. Dong, Q. Liu, Y. Liu Quantifying spatial morphology and connectivity of urban heat islands in a megacity: a radius approach Sci. Total Environ., 714 (2020), Article 136792, 10.1016/j.scitotenv.2020.136792spa
dc.relation.referencesJ.Y. Deng, N.H. Wong Impact of urban canyon geometries on outdoor thermal comfort in central business districts Sustain. Cities Soc., 53 (2020), Article 101966, 10.1016/j.scs.2019.101966spa
dc.relation.referencesA. Vilches, Á.B. Padura, M.M. Huelva Retrofitting of homes for people in fuel poverty: approach based on household thermal comfort Energy Policy, 100 (2017), pp. 283-291, 10.1016/j.enpol.2016.10.016spa
dc.relation.referencesP.C. Toscan, A. Neckel, C. Korcelski, L.S. Maculan, D. Maroni, T.M. Fuga, L.P. Cambrussi, H.A. Kujawa, E.T. Bodah, B.W. Bodah Urban Cemeteries in Southern Brazil: an analysis of planimetric variations, vegetation indices and temperature J. Civ. Eng. Archit., 14 (2020), pp. 617-624, 10.17265/1934-7359/2020.11.005spa
dc.relation.referencesZ. Wu, L. Yao, M. Zhuang, Y. Ren Detecting factors controlling spatial patterns in urban land surface temperatures: a case study of Beijing Sustain. Cities Soc., 63 (2020), Article 102454, 10.1016/j.scs.2020.102454spa
dc.relation.referencesJ. Li, Y. Wang, Z. Ni, S. Chen, B. Xia An integrated strategy to improve the microclimate regulation of green-blue-grey infrastructures in specific urban forms J. Clean. Prod., 271 (2020), Article 122555, 10.1016/j.jclepro.2020.122555spa
dc.relation.referencesR.L. Hwang, T.P. Lin, F.Y. Lin Evaluation and mapping of building overheating risk and air conditioning use due to the urban heat island effect J. Build. Eng., 32 (2020), Article 101726, 10.1016/j.jobe.2020.101726spa
dc.relation.referencesA. Aslam, M. Ibrahim, A. Mahmood, M. Mubashir, H.F.K. Sipra, I. Shahid, S. Ramzan, M.T. Latif, M.Y. Tahir, P.L. Show Mitigation of particulate matters and integrated approach for carbon monoxide remediation in an urban environment J. Environ. Chem. Eng., 9 (2021), Article 105546, 10.1016/j.jece.2021.105546spa
dc.relation.referencesD. Wang, Y. Chen, L. Hu, J.A. Voogt, J.P. Gastellu-Etchegorry, E.S. Krayenhoff Modeling the angular effect of MODIS LST in urban areas: a case study of toulouse, france Remote Sens. Environ., 257 (2021), Article 112361, 10.1016/j.rse.2021.112361spa
dc.relation.referencesA.H.M. Eldesoky, J. Gil, M.B. Pont The suitability of the urban local climate zone classification scheme for surface temperature studies in distinct macroclimate regions Urban Clim., 37 (2021), Article 100823, 10.1016/j.uclim.2021.100823spa
dc.relation.referencesS. Pal, S. Ziaul Detection of land use and land cover change and land surface temperature in English Bazar urban centre Egypt. J. Remote. Sens. Space Sci., 20 (2017), pp. 125-145, 10.1016/j.ejrs.2016.11.003spa
dc.relation.referencesS. Guha, H. Govil, N. Gill, A. Dey A long-term seasonal analysis on the relationship between LST and NDBI using Landsat data Quat. Int. (2020), pp. 1-36, 10.1016/j.quaint.2020.06.041spa
dc.relation.referencesH. Wu, T. Wang, Q.G. Wang, Y. Cao, Y. Qu, D. Nie Radiative effects and chemical compositions of fine particles modulating urban heat island in Nanjing, China Atmos. Environ., 247 (2021), Article 118201, 10.1016/j.atmosenv.2021.118201spa
dc.relation.referencesY. Liu, Q. Li, L. Yang, K. Mu, M. Zhang, J. Liu Urban heat island effects of various urban morphologies under regional climate conditions Sci. Total Environ., 743 (2020), Article 140589, 10.1016/j.scitotenv.2020.140589spa
dc.relation.referencesC. Liotta, Y. Kervinio, H. Levrel, L. Tardieu Planning for environmental justice - reducing well-being inequalities through urban greening Environ. Sci. Policy, 112 (2020), pp. 47-60, 10.1016/j.envsci.2020.03.017spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


Ficheros en el ítem

Thumbnail
Nombre:
Land surface temperature and ...
Tamaño:
106.3Kb
Formato:
PDF
Ver/
Thumbnail
Nombre:
license_rdf
Tamaño:
805bytes
Formato:
application/rdf+xml
Ver/

Este ítem aparece en la(s) siguiente(s) colección(ones)

  • Artículos científicos [3154]
    Artículos de investigación publicados por miembros de la comunidad universitaria.

Mostrar el registro sencillo del ítem

Attribution-NonCommercial-NoDerivatives 4.0 International
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International