Automated pre-processing strategies for species occurrence data used in biodiversity modelling
Heap, M. J. and Culham, A. (2010) Automated pre-processing strategies for species occurrence data used in biodiversity modelling. Lecture Notes in Computer Science: Lecture Notes in Artificial Intelligence, Part I (6279). pp. 517-526. ISSN 0302-9743
To link to this item DOI: 10.1007/978-3-642-15384-6
To construct Biodiversity richness maps from Environmental Niche Models (ENMs) of thousands of species is time consuming. A separate species occurrence data pre-processing phase enables the experimenter to control test AUC score variance due to species dataset size. Besides, removing duplicate occurrences and points with missing environmental data, we discuss the need for coordinate precision, wide dispersion, temporal and synonymity filters. After species data filtering, the final task of a pre-processing phase should be the automatic generation of species occurrence datasets which can then be directly ’plugged-in’ to the ENM. A software application capable of carrying out all these tasks will be a valuable time-saver particularly for large scale biodiversity studies.