Models implemented in the land surface temperature and vegetation indexes time series analysis: a taxonomic proposal in the context of the global climate change

Authors

  • Oscar Arley Zuluaga Gómez Universidad de San Buenaventura Sede Medellín
  • Jorge Eduardo Patiño Quinchía Universidad EAFIT
  • German Mauricio Valencia Hernández Universidad de San Buenaventura Sede Medellín

DOI:

https://doi.org/10.4067/S0718-34022021000100323

Keywords:

Time Series, Vegetation Index, Global Warming, GCM, Linear Regression Analysis, Nonlinear Regression Analysis

Abstract

Climate change and global warming are caused principally by anthropogenic activities. For this reason, understanding the research lines that relate Land Surface Temperature and Vegetation Index time series is of great importance, given the amplitude of different open scientific areas on global warming. The result of this classification is presented to the academic community, which divides the studies into two main representative areas in the study of climate change: (1) Geodata Modeling and Analysis and (2) Remote Sensing. From the last one, two types are derived, some constructed with Linnear Regression Analysis (RL) and others with Nonlinear Regression Analysis (RNL). On the Geodata Modeling and Analysis, the Global Climate Models (GCM) are not the right tool for these analyzes due to their coarse spatial resolution. This implies the development of hybrid models with remote sensing, which are also limited by differences in resolution. On the other hand, remote sensing is the most widely disseminated tool for this type of studies. Finally, a promising window for development in the time series opens with non-linear regression analysis.

 

 

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Author Biographies

Oscar Arley Zuluaga Gómez, Universidad de San Buenaventura Sede Medellín

Especialista en Sistemas de Información Geográfica, Candidato MSc Geoinformática Universidad de San Buenaventura Sede Medellín  

Jorge Eduardo Patiño Quinchía, Universidad EAFIT

Investigador Senior, Grupo de Investigación Research In Spatial Economics (RiSE) Universidad EAFIT. Departamento de Economía. 

German Mauricio Valencia Hernández, Universidad de San Buenaventura Sede Medellín

MSc en Geoinformática Profesor de Planta Facultad de Ingeniería Universidad de San Buenaventura Sede Medellín 

Published

2021-10-05

How to Cite

Zuluaga Gómez, O. A. ., Patiño Quinchía, J. E. ., & Valencia Hernández, G. M. . (2021). Models implemented in the land surface temperature and vegetation indexes time series analysis: a taxonomic proposal in the context of the global climate change. Revista De Geografía Norte Grande, (78), 323–344. https://doi.org/10.4067/S0718-34022021000100323

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Artículos