Integrating field survey data with satellite image data to improve shallow water seagrass maps : the role of AUV and snorkeller surveys

Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

Recreational needs and service performance expectations

The theoretical contribution of this study lies with its focus on subjective experiencing, that is, the emotional convergence between feeling states, and perceptions of servicescapes and holiday activities. An empirical study models the impact of recreational needs on the perceived importance of destination attributes and intentions to participate in activities. A sample of prospective tourists was asked to indicate how important they considered servicescape elements to be in their general holiday planning. They were also asked to report on their emotional state (orientation) as a proxy for their needs for recreation, and to state their intention and likely involvement with holiday activities. Results suggest that those with high recreational needs (self-reflexive and inward-looking) regard elements of tourism servicescapes as significantly more important than those without (who are outward-looking and energetic), as well as show significant variations in their inclinations to be active and explorative at destinations. Rather, those with higher recreational needs as measured by combinations of lack of energy, self-confidence, and physiological well-being look for creature comfort, coziness, and familiarity, in other words, for things they already know and have experienced before. Subjective experiencing and service performance evaluations are thereby suggested to be influenced by emotional states. These states may also impact tourists' recognition of destination uniqueness as a major component of a destination's competitive advantage that cannot easily be copied. As a consequence, it may be worth reconsidering the role of recreation in tourism service design. Turning an inwardlooking focus bent on recreation to an outward-looking one interested in discovery would enable more tourists to more fully experience the destination before they leave.

Incident reporting culture in recreational hot air ballooning

Hot air ballooning incidents are relatively rare; however, they have a high potential to be fatal. In order to inform appropriate safety interventions it is first necessary to understand the causal factors which lead to incidents and near-misses, which requires a formal incident report database. The Australian Balloon Federation (ABF) advocates the reporting of recreational hot air ballooning incidents, by reporting directly to the ABF safety officer or by completing an online incident report form. The objective of this paper is to understand how widely used the reporting system is and whether there are any perceived barriers to reporting. Sixty-nine balloonists participated in an online survey about their experience of incident reporting. Survey respondents were mostly male (11 female), experienced balloonists (mean years’ experience ballooning 19.51y with a SD 11.19). Sixty respondents (87%) held a pilot license. The majority (82.6%) of respondents were aware of the ABF incident reporting system. Over half (62.3%) had been involved in a ballooning incident or near-miss in Australia. However, 40% of those who had an incident or near-miss did not report it to the ABF and only 15.9% of all those surveyed had used the online incident report form. There was some disagreement regarding when it was appropriate to report an incident or near miss. Some respondents felt an incident or near miss should only be reported if it resulted in injury or damage, while others said near-misses should also be reported. The most frequent barriers identified were: a lack of understanding of when to report to the ABF; trivializing of incidents; and concerns about the system itself Steps should be taken to increase understanding of the system purpose and long term benefits. Specifically, reporting near-misses should be encouraged. This study is significant because it is the first to examine reporting practices in non-motorised recreational aviation.

Clustering acoustic events in environmental recordings for species richness surveys

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

Economic value of recreational fishing in Moreton Bay and the potential impact of the marine park rezoning

In 2009, the area of the Moreton Bay Marine Park was increased from 0.5 per cent of the Bay area to 16 per cent. During the planning process, opposition by commercial and recreational fishers alike was raised, arguing that loss of fishing grounds would lead to substantial loss in economic benefits. The commercial sector was compensated through a buyback of fishing effort, but the recreational sector received no compensation. In this paper, we develop a travel cost model to estimate the potential economic impact on the recreational sector from the marine park rezoning. The results suggest that, counter to initial claims, non-market recreational fishing benefits may have increased by between $1.3m and $2.5m a year, with a current total annual value of around $20m. Keywords: Travel cost model; Economic valuation; Moreton Bay Marine Park; Recreational fishing

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Assistive classification for improving the efficiency of avian species richness surveys

Avian species richness surveys, which measure the total number of unique avian species, can be conducted via remote acoustic sensors. An immense quantity of data can be collected, which, although rich in useful information, places a great workload on the scientists who manually inspect the audio. To deal with this big data problem, we calculated acoustic indices from audio data at a one-minute resolution and used them to classify one-minute recordings into five classes. By filtering out the non-avian minutes, we can reduce the amount of data by about 50% and improve the efficiency of determining avian species richness. The experimental results show that, given 60 one-minute samples, our approach enables to direct ecologists to find about 10% more avian species.

Indicators of wellbeing in recreational video game players

Video game play is a popular entertainment choice, yet we have a limited understanding of the potential wellbeing benefits associated with recreational play. An online survey (final sample, n = 297) addresses this by investigating how the player experience related to wellbeing. The impact of amount of play, game genre, mode of play (social or solitary play) and the psychological experience of play (flow and need satisfaction) on a multi-dimensional measure of wellbeing (emotional, psychological and social) was examined via hierarchical regression. Age, gender, the play of casual games compared to shooters, and in-game experiences of flow, autonomy and relatedness were associated with increases in dimensions of wellbeing.

The impact of a streamlined funding application process on application time: Two cross-sectional surveys of Australian researchers

Objective: To examine if streamlining a medical research funding application process saved time for applicants. Design: Cross-sectional surveys before and after the streamlining. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant applications in 2012 or 2014. Main outcome measures: Average researcher time spent preparing an application and the total time for all applications in working days. Results: The average time per application increased from 34 working days before streamlining (95% CI 33 to 35) to 38 working days after streamlining (95% CI 37 to 39; mean difference 4 days, bootstrap p value <0.001). The estimated total time spent by all researchers on applications after streamlining was 614 working years, a 67-year increase from before streamlining. Conclusions: Streamlined applications were shorter but took longer to prepare on average. Researchers may be allocating a fixed amount of time to preparing funding applications based on their expected return, or may be increasing their time in response to increased competition. Many potentially productive years of researcher time are still being lost to preparing failed applications.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.