Spatial Variability of Forest Species: Case Study for Alto Alentejo, Portugal

Ana Margarida Coelho, Adélia M. O. Sousa and Ana Cristina Gonçalves ()
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Ana Margarida Coelho: ICT—Departamento de Engenharia Rural, Instituto de Ciências da Terra (ICT), Instituto de Investigação e Formação Avançada, Universidade de Évora Apartado 94, 7002-544 Évora, Portugal
Adélia M. O. Sousa: MED—Mediterranean Institute for Agriculture, Environment and Development & CHANGE—Global Change and Sustainability Institute, Laboratório de Deteção Remota-EaRSLab, Instituto de Investigação e Formação Avançada, Departamento de Engenharia Rural, Escola de Ciências e Tecnologia, Universidade de Évora, Apatado 94, 7002-544 Évora, Portugal
Ana Cristina Gonçalves: MED—Mediterranean Institute for Agriculture, Environment and Development & CHANGE—Global Change and Sustainability Institute, Instituto de Investigação e Formação Avançada, Departamento de Engenharia Rural, Escola de Ciências e Tecnologia, Universidade de Évora, Apartado 94, 7002-544 Évora, Portugal

Land, 2022, vol. 12, issue 1, 1-15

Abstract: Landscape evaluation and monitoring enable us to understand the interactions between its components and the effects of disturbances (whether they are natural or artificial) in its dynamics. Forests have a wide variability and diversity, and their analysis at the landscape level allows us to evaluate its spatial distribution pattern. This study focused on the analysis of the landscape spatial variability of forest species with data derived from remote sensing and landscape metrics of a case study in Alto Alentejo, Portugal. Sentinel-2 satellite images were used to produce a land use and land cover map with a random forest classification algorithm, where the bands, vegetation and texture indices were the explanatory variables. The obtained land use/cover map has classified five forest classes and one non-forest class. The map was used to evaluate the diversity with eleven composition and configuration landscape diversity metrics for Alto Alentejo and for four sub-regions delimited according to their edaphic-climatic characteristics. The results showed that the land use/cover map had a good precision (a global precision of 89% and a kappa of 86%) and that both Alto Alentejo and its sub-regions had high forest diversity both in composition and configuration.

Keywords: Sentinel-2; forest land use; landscape metrics; beta diversity modelling (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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