@article {bnh-3919, title = {Development of a predictive model for estimating forest surface fuel load in Australian eucalypt forests with LiDAR data}, journal = {Environmental Modelling \& Software}, volume = {97}, year = {2017}, month = {11/2017}, pages = {61-71}, chapter = {61}, abstract = {

Accurate description of forest surface fuel load is important for understanding bushfire behaviour and suppression difficulties, predicting ongoing fires for operational activities, assessing potential fire hazards and assisting in fuel hazard-reduction burns to reduce fire risks to the community and the environment. Bushfire related studies and current operational activities have a common challenge in quantifying fuels, since the fuel load varies across the landscape. This paper developed a predictive model that efficiently and accurately estimates quantities of surface fuel in Australian southeast Eucalypt forests. Model coefficients were determined through a three-step process that attempts to evaluate how the spatial variation in surface fuel load relates to litter-bed depth, fuel characteristics, topography and previous fire disturbance. First, the forest surface fuel depth-to-load relationship was established; second, key quantitative variables of environmental factors were added; and third, important qualitative variables of fuel characteristics were included. The verification of model prediction was conducted through leave-one-out cross-validation (CV). Light Detection and Ranging was used to quantify forest structural characteristics and terrain features. The calibrated model had a\ R2\ of 0.89 (RMSE\ =\ 20.7\ g) and performed better than the currently used surface fuel load models, including McArthur{\textquoteright}s (R2\ =\ 0.61 and\ RMSE\ =\ 39.6\ g) and Gilroy and Tran{\textquoteright}s (R2\ =\ 0.69 and\ RMSE\ =\ 36.5\ g) models. This study describes a novel approach to forest surface fuel load modelling using forest characteristics and environmental factors derived from LiDAR data through statistical analysis. The model established in this study can be used as an efficient approach to assist in forest fuel management and fire related operational activities.

}, doi = {10.1016/j.envsoft.2017.07.007}, url = {http://www.sciencedirect.com/science/article/pii/S1364815216304418}, author = {Chen, Yang and Xuan Zhou and Marta Yebra and Sarah Harris and Nigel Tapper} } @conference {bnh-3232, title = {Estimation of forest surface fuel load using airborne LiDAR data}, booktitle = {SPIE Remote Sensing}, year = {2017}, month = {09/2017}, publisher = {SPIE}, organization = {SPIE}, address = {Warsaw, Poland}, abstract = {

Accurately describing forest surface fuel load is significant for understanding bushfire behaviour and suppression difficulties, predicting ongoing fires for operational activities, as well as assessing potential fire hazards. In this study, the Light Detection and Ranging (LiDAR) data was used to estimate surface fuel load, due to its ability to provide threedimensional
information to quantify forest structural characteristics with high spatial accuracies. Firstly, the multilayered eucalypt forest vegetation was stratified by identifying the cut point of the mixture distribution of LiDAR point density through a non-parametric fitting strategy as well as derivative functions. Secondly, the LiDAR indices of heights, intensity, topography, and canopy density were extracted. Thirdly, these LiDAR indices, forest type and previous fire disturbances were then used to develop two predictive models to estimate surface fuel load through multiple regression analysis. Model 1 was developed based on LiDAR indices, which produced a R2 value of 0.63. Model 2 (R2 = 0.8) wasderived from LiDAR indices, forest type and previous fire disturbances. The accurate and consistent spatial variation in surface fuel load derived from both models could be used to assist fire authorities in guiding fire hazard-reduction burns and fire suppressions in the Upper Yarra Reservoir area, Victoria, Australia.

}, author = {Chen, Yang and Xuan Zhou and Marta Yebra and Sarah Harris and Nigel Tapper} } @article {bnh-2504, title = {Are two halves better than one whole? A comparison of the amount and quality of sleep obtained by healthy adult males living on split and consolidated sleep{\textendash}wake schedules}, journal = {Accident Analysis \& Prevention}, year = {2015}, month = {11/2015}, abstract = {

The aim of this study was to compare the quantity/quality of sleep obtained by people living on split and consolidated sleep{\textendash}wake schedules. The study had a between-groups design, with 13 participants in a consolidated condition (all males, mean age of 22.5yr) and 16 participants in a split condition (all males, mean age of 22.6yr). Both conditions employed forced desynchrony protocols with the activity:rest ratio set at 2:1, but the consolidated condition had one sleep{\textendash}wake cycle every 28h (9.33+18.67), while the split condition had one sleep{\textendash}wake cycle every 14h (4.67+9.33). Sleep was assessed using polysomnography. Participants in the split and consolidated conditions obtained 4.0h of sleep per 14h and 7.6h of sleep per 28h, respectively. Some differences between the groups indicated that sleep quality was lower in the split condition than the consolidated condition: the split sleeps had longer sleep onset latency (9.7 vs. 4.3min), more arousals (7.4 vs. 5.7 per hour in bed), and a greater percentage of stage 1 sleep (4.1\% vs. 3.1\%), than the consolidated sleeps. Other differences between the groups indicated that sleep quality was higher in the split condition than the consolidated condition: the split sleeps had a lower percentage of wake after sleep onset sleep (11.7\% vs. 17.6\%), and a greater percentage of slow wave sleep (30.2\% vs. 23.8\%), than the consolidated sleeps. These results indicate that the split schedule was not particularly harmful, and may have actually been beneficial, to sleep. Split work{\textendash}rest schedules can be socially disruptive, but their use may be warranted in work settings where shiftworkers are separated from their normal family/social lives (e.g., fly-in fly-out mining) or where the need for family/social time is secondary to the task (e.g., emergency response to natural disasters).

}, url = {http://www.sciencedirect.com/science/article/pii/S0001457515300932}, author = {Gregory Roach and Xuan Zhou and David Darwent and Anastasi Kosmadopoulos and Drew Dawson and Charli Sargent} } @article {bnh-2506, title = {The efficacy of objective and subjective predictors of driving performance during sleep restriction and circadian misalignment}, journal = {Accident Analysis \& Prevention}, year = {2015}, month = {11/2015}, abstract = {

Fatigue is a significant contributor to motor-vehicle accidents and fatalities. Shift workers are particularly susceptible to fatigue-related risks as they are often sleep-restricted and required to commute around the clock. Simple assays of performance could provide useful indications of risk in fatigue management, but their effectiveness may be influenced by changes in their sensitivity to sleep loss across the day. The aim of this study was to evaluate the sensitivity of several neurobehavioral and subjective tasks to sleep restriction (SR) at different circadian phases and their efficacy as predictors of performance during a simulated driving task. Thirty-two volunteers (M{\textpm}SD; 22.8{\textpm}2.9 years) were time-isolated for 13-days and participated in one of two 14-h forced desynchrony protocols with sleep opportunities equivalent to 8h/24h (control) or 4h/24h (SR). At regular intervals during wake periods, participants completed a simulated driving task, several neurobehavioral tasks, including the psychomotor vigilance task (PVT), and subjective ratings, including a self-assessment measure of ability to perform. Scores transformed into standardized units relative to baseline were folded into circadian phase bins based on core body temperature. Sleep dose and circadian phase effect sizes were derived via mixed models analyses. Predictors of driving were identified with regressions. Performance was most sensitive to sleep restriction around the circadian nadir. The effects of sleep restriction around the circadian nadir were larger for simulated driving and neurobehavioral tasks than for subjective ratings. Tasks did not significantly predict driving performance during the control condition or around the acrophase during the SR condition. The PVT and self-assessed ability were the best predictors of simulated driving across circadian phases during SR. These results show that simple performance measures and self-monitoring explain a large proportion of the variance in driving when fatigue-risk is high.

}, url = {http://www.sciencedirect.com/science/article/pii/S0001457515300968}, author = {Anastasi Kosmadopoulos and Charli Sargent and Xuan Zhou and David Darwent and Raymond Matthews and Drew Dawson and Gregory Roach} } @article {BF-4370, title = {Alternatives to polysomnography (PSG): A validation of wrist actigraphy and a partial-PSG system}, journal = {Behavior Research Methods}, year = {2014}, month = {January 2014}, abstract = {The objective of this study was to assess the validity of a sleep/wake activity monitor, an energy expenditure activity monitor, and a partial-polysomnography system at measuring sleep and wake under identical conditions. Secondary aims were to evaluate the sleep/wake thresholds for each activity monitor and to compare the three devices. To achieve these aims, two nights of sleep were recorded simultaneously with polysomnography (PSG), two activity monitors, and a partial-PSG system in a sleep laboratory. Agreement with PSG was evaluated epoch by epoch and with summary measures including total sleep time (TST) and wake after sleep onset (WASO). All of the devices had high agreement rates for identifying sleep and wake, but the partial-PSG system was the best, with an agreement of 91.6 \% {\textpm} 5.1 \%. At their best thresholds, the sleep/wake monitor (medium threshold, 87.7 \% {\textpm} 7.6 \%) and the energy expenditure monitor (very low threshold, 86.8 \% {\textpm} 8.6 \%) had similarly high rates of agreement. The summary measures were similar to those determined by PSG, but the partial-PSG system provided the most consistent estimates. Although the partial-PSG system was the most accurate device, both activity monitors were also valid for sleep estimation, provided that appropriate thresholds were selected. Each device has advantages, so the primary consideration for researchers will be to determine which best suits a given research design.}, keywords = {Accelerometry, Actigraphy, Wireless sleep monitoring}, doi = {dx.doi.org/10.3758/s13428-013-0438-7}, url = {http://link.springer.com/article/10.3758\%2Fs13428-013-0438-7}, author = {Anastasi Kosmadopoulos and Charli Sargent and David Darwent and Xuan Zhou and Gregory Roach} }