Positional Error Propagation Analysis in Habitat Distribution Modelling
Babak Naimi1*, Andrew K. Skidmore2, Nicholas A.S. Hamm2, and Thomas A. Groen2
1.Faculty of Geo-Information Science and Earth Observation, (ITC), Enschede, The Netherlands, Graduate School of the Environment and Energy,Science and Research Branch, Islamic Azad University, Tehran, Iran
2.Faculty of Geo-Information Science and Earth Observation, (ITC), Enschede, The Netherlands
Abstract: This study examines how robust habitat distribution models are to uncertainty in the position of species occurrence. An artificial species was simulated and mapped in southern Spain (Malaga) and error was introduced to the location of samples. Three commonly used habitat distribution modelling algorithms (GAM, BRT, and MaxEnt) were selected. The propagation of error into the predictions was then analyzed using Monte Carlo (MC) simulation. The models were evaluated for overall performance using the area under receiver operating characteristic curve (AUC). The Root Mean Square Error (RMSE) was also calculated to assess the accuracy of probabilities predicted at grid cells. The results indicate only a small decline in the performance of models with introduced error in species position. Visualizing of RMSEs at grid cells indicates that uncertainty varies with location.
Keywords: Habitat distribution modeling; positional uncertainty; spatial error propagation