Bioclimatic classification in the Caroni River basin using the maximum likelihood method
DOI:
https://doi.org/10.21138/GF.901Resumo
Bioclimatic classification is essential for understanding and managing the territory in a more sustainable way, as well as in biodiversity conservation management and climate change assessment. The supervised Maximum Likelihood (ML) classification method is a powerful tool for bioclimatic classification. Therefore, the ML classifier was applied in the Caroni River basin, using data from global sources, from which averages of climatic variables were extracted. Geographic Weighted Regression (GWR) and the 90 m SRTM DEM were used to improve the scale. The Holdridge classification was applied, this presented an overall accuracy of 93 % the classes of premontane rainforest, very humid tropical forest and premontane rainforest denoted the worst performance, as there are transitive structures involved that the classification model could not capture. Key words: Maximum Likelihood Classification, bioclimatic classification, Geographic Weighted Regression.
Downloads
Publicado
Como Citar
Edição
Secção
Licença
©The authors of the articles and other contributions published in GeoFocus keep intact the intellectual property rights over them. The authors and the publisher authorize the total or partial reproduction of the contents of the journal in the following terms:
1) Express mention of the author and the reference of the original publication.
2) Do not perform a commercial or lucrative use of them. Otherwise, you should contact the authors to make the appropriate arrangements.
3) Authors preserve their property rights and give to the journal the rights of the first publication of the work, registered with the Licencia Creative Commons Atribución-NoComercial-SinDerivar 4.0 Internacional, which allows third parties to use the published data whenever the authorship of the work and first publication in this journal is mentioned.
4) It is allowed that authors disseminate electronically (e.g., in institutional repositories or on their own website) the published version of their work, as it encourages the earliest circulation and dissemination, and thus a possible increase in the citation and scope in the academic community.