Performance of predictive models in marine benthic environments based on predictions of sponge distribution on the Australian continental shelf. - Zhi Huang; Brendan P. Brooke; Jin Li 015 (Ecol. Informatics, 2011)

A review of comparative studies of spatial interpolation methods in environmental sciences: Performance and impact factors. - Jin Li 015; Andrew D. Heap (Ecol. Informatics, 2011)

Application of machine learning methods to spatial interpolation of environmental variables. - Jin Li 015; Andrew D. Heap; Anna Potter; James Daniell (Environ. Model. Softw., 2011)

Spatial interpolation of McArthur's Forest Fire Danger Index across Australia: Observational study. - Luis Augusto Sanabria; Xuerong Qin; Jin Li 015; Robert Peter Cechet; Christopher Lucas 003 (Environ. Model. Softw., 2013)

Spatial interpolation methods applied in the environmental sciences: A review. - Jin Li 015; Andrew D. Heap (Environ. Model. Softw., 2014)

Assessing spatial predictive models in the environmental sciences: Accuracy measures, data variation and variance explained. - Jin Li 015 (Environ. Model. Softw., 2016)

Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness. - Jin Li 015; Belinda Alvarez; Justy P. W. Siwabessy; Maggie Tran; Zhi Huang; Rachel Przeslawski; Lynda Radke; Floyd Howard; Scott L. Nichol (Environ. Model. Softw., 2017)