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Applying the technique of image classification to climate science: the case of Andalusia (Spain)
Author(s) -
GómezZotano José,
AlcántaraManzanares Jorge,
MartínezIbarra Emilio,
OlmedoCobo José Antonio
Publication year - 2016
Publication title -
geographical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.695
H-Index - 47
eISSN - 1745-5871
pISSN - 1745-5863
DOI - 10.1111/1745-5871.12180
Subject(s) - classifier (uml) , computer science , multivariate statistics , data mining , contextual image classification , artificial intelligence , operability , pattern recognition (psychology) , machine learning , image (mathematics) , software engineering
This paper proposes an empirical climate classification method based on the application of multivariate statistics. In this method, the technique of supervised and unsupervised image classification is used to classify the data and define climatic units. envi software is used to perform the image classification, specifically, the Iterative Self‐Organizing Data Analysis Technique algorithm. Supervised classification is also applied based on reference variables, fundamental parameters and a classifier. The obtained results display greater objectivity, reliability, operability, accessibility and reproducibility than previous climate classifications devised for the region of Andalusia (Spain), taking into account that these previous classifications were not based on quantitative criteria.