Identifying optimal cell size for geodiversity quantitative assessment with richness, diversity and evenness indices

• Autor(a) principal: Lopes Catarina
• Data de Publicação: 2023
• Outros Autores: Teixeira, Zara, Pereira, D. I., Pereira, Paulo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/1822/84970
• topic: Grid system; Geodiversity quantitative assessment; Cell size; Diversity indices; Ciências Naturais::Ciências da Terra e do Ambiente

The importance of quantitatively assessing the spatial patterns of geodiversity, and their intrinsic relationship with biodiversity and the ecosystem services provided to society, has been signalized by several authors, due to the relevance of this information in territorial management, the planning of environmental and conservation strategies. Within geodiversity method assessments, the grid system is the most widely used GIS spatial approach to calculate a geodiversity index. Preferred for its simplicity, it implies the fundamental decision of choosing the scale of the analysis, defined by the selection of cell size, determinant for the accuracy and correctness of the final maps. Although this topic has been occasionally approached by some authors within geodiversity assessments, there is no formal procedure for cell size selection. This is a key issue, and, in the scope of the present work, an empirical procedure to select optimal cell size(s) was tested on the national scale in Portugal, in lithology and geomorphology datasets. The quantitative method based on geodiversity indices was applied, using richness, diversity and evenness indices, in a hexagonal analytical grid, through eight cell dimensions. Several descriptive statistical parameters were analyzed, with particular emphasis on dispersion statistical measures. Optimal cell size corresponded to the minimum cell size, once dispersion values were significatively reduced or stabilized, and distributions from evenness and diversity indices were closer to symmetry, which provided more accurate results and higher spatial differentiation, although the final decision should always consider the main purposes of the analysis.