3 resultados para Pères
em Queensland University of Technology - ePrints Archive
Resumo:
The city centre represents a complex environment for cycling with large volumes of pedestrians and motorised vehicles and frequent signalised intersections. Much of the previous literature has focused on cyclist-motor vehicle interactions because of the safety implications for cyclists, but there is increasing concern from pedestrians about the threats they perceive from cyclists. In the absence of objective data, this has the potential to lead to restrictions on cyclist access and behaviour. This presentation reports the development of a method to study the extent of cycling in the city centre and the frequency and nature of interactions between cyclists and pedestrians. Queensland is one of the few Australian jurisdictions that permits adults to cycle on the footpath and this was also of interest. 1992 cyclists were observed at six locations in the Brisbane city centre, during 7-9am, 9-11am, 2-4pm and 4-6pm on four weekdays in October 2010. The majority (85.5%) of cyclists were male, and 21.8% rode on the footpath. Females were more likely to travel on the footpath than males. One or more pedestrians were within 1m for 18.1% of observed cyclists, and one or more pedestrians were within 5m for 39.1% of observed cyclists. There were few conflicts, defined as an occasion where if no one took evasive action a collision would occur, between cyclists and pedestrians or vehicles (1.1% and 0.6% respectively) but they were more common for adolescents and riders not wearing (or not fastening) helmets.
Resumo:
Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.