Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Development and Simulation of a Variable Rate Controller for an Air search and Air Sampling Unmanned Aerial System

This report describes the development and simulation of a variable rate controller for a 6-degree of freedom nonlinear model. The variable rate simulation model represents an off the shelf autopilot. Flight experiment involves risks and can be expensive. Therefore a dynamic model to understand the performance characteristics of the UAS in mission simulation before actual flight test or to obtain parameters needed for the flight is important. The control and guidance is implemented in Simulink. The report tests the use of the model for air search and air sampling path planning. A GUI in which a set of mission scenarios, in which two experts (mission expert, i.e. air sampling or air search and an UAV expert) interact, is presented showing the benefits of the method.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Automatic wildfire detection and simulation using optical information from unmanned aerial systems

In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.

Green Falcon IV: An Unmanned Aerial System and an integrated Wireless Sensor Network for remote sensing tasks

This report summarises the development of an Unmanned Aerial System and an integrated Wireless Sensor Network (WSN), suitable for the real world application in remote sensing tasks. Several aspects are discussed and analysed to provide improvements in flight duration, performance and mobility of the UAV, while ensuring the accuracy and range of data from the wireless sensor system.

Revisiting Coptotermes (Isoptera: Rhinotermitidae): a global taxonomic road map for species validity and distribution of an economically important subterranean termite genus

Coptotermes Wasmann (Isoptera: Rhinotermitidae) is one of the most economically important subterranean termite genera and some species are successful invaders. However, despite its important pest status, the taxonomic validity of many named Coptotermes species remains unclear. In this study, we reviewed all named species within the genus and investigated evidence supporting the validity of each named species. Species were systematically scrutinized according to the region of their original description: Southeast Asia, India, China, Africa, the Neotropics, and Australia. We estimate that of the currently 69 named species described by accepted nomenclatural rules, only 21 taxa have solid evidence for validity, 44 names have uncertain status, and the remaining species names should be synonymized or were made unavailable. Species with high degrees of invasiveness may be known under additional junior synonyms due to independent parochial descriptions. Molecular data for a vast majority of species are scarce and significant effort is needed to complete the taxonomic and phylogenetic revision of the genus. Because of the wide distribution of Coptotermes, we advocate for an integrative taxonomic effort to establish the distribution of each putative species, provide specimens and corresponding molecular data, check original descriptions and type specimens (if available), and provide evidence for a more robust phylogenetic position of each species. This study embodies both consensus and contention of those studying Coptotermes and thus pinpoints the current uncertainty of many species. This project is intended to be a roadmap for identifying those Coptotermes species names that need to be more thoroughly investigated, as an incentive to complete a necessary revision process.

Automatic Detection of Marine Mammal from Aerial Imagery

The following technical report describes the approach and algorithm used to detect marine mammals from aerial imagery taken from manned/unmanned platform. The aim is to automate the process of counting the population of dugongs and other mammals. We have developed and algorithm that automatically presents to a user a number of possible candidates of these mammals. We tested the algorithm in two distinct datasets taken from different altitudes. Analysis and discussion is presented in regards with the complexity of the input datasets, the detection performance.

Similarity not favourability : the role of donor prototypes in predicting willingness to donate organs while living

Using an extended Prototype/Willingness Model, we examined the predictors of willingness to donate an organ to a partner/family member and a stranger while living. A questionnaire assessed university students’ (N = 284) attitudes, subjective norm, prototype favourability, prototype similarity, moral norm, and willingness to donate organs in each recipient scenario. All variables, except prototype favourability, predicted willingness to donate organs in both situations. Future strategies should emphasise perceived approval from important others for living donation, the consistency of living donation with one’s own morals, and encourage perceptions of similarity between oneself and living donors to increase acceptance of living donation.

Knowing a donor and identifying as one : determinants of people's willingness for related and anonymous living donation in Australia

While LRD (living donation to a genetically/emotionally related recipient) is well established in Australia, LAD (living anonymous donation to a stranger) is rare. Given the increasing use of LAD overseas, Australia may likely follow suit. Understanding the determinants of people’s willingness for LAD is essential but infrequently studied in Australia. Consequently, we compared the determinants of people’s LRD and LAD willingness, and assessed whether these determinants differed according to type of living donation. We surveyed 487 health students about their LRD and LAD willingness, attitudes, identity, prior experience with blood and organ donation, deceased donation preference, and demographics. We used Structural Equation Modelling (SEM) to identify the determinants of willingness for LRD and LAD and paired sample t-tests to examine differences in LRD and LAD attitudes, identity, and willingness. Mean differences in willingness (LRD 5.93, LAD 3.92), attitudes (LRD 6.43, LAD 5.53), and identity (LRD 5.69, LAD 3.58) were statistically significant. Revised SEM models provided a good fit to the data (LRD: x2 (41) = 67.67, p = 0.005, CFI = 0.96, RMSEA = 0.04; LAD: x2 (40) = 79.64, p < 0.001, CFI = 0.95, RMSEA = 0.05) and explained 45% and 54% of the variation in LRD and LAD willingness, respectively. Four common determinants of LRD and LAD willingness emerged: identity, attitude, past blood donation, and knowing a deceased donor. Religious affiliation and deceased donation preference predicted LAD willingness also. Identifying similarities and differences in these determinants can inform future efforts aimed at understanding people’s LRD and LAD willingness and the evaluation of potential living donor motives. Notably, this study highlights the importance of people’s identification as a living donor as a motive underlying their willingness to donate their organs while living.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Determining the psychosocial predictors of living, living-related, and posthumous organ donation

The worldwide organ shortage occurs despite people’s positive organ donation attitudes. The discrepancy between attitudes and behaviour is evident in Australia particularly, with widespread public support for organ donation but low donation and communication rates. This problem is compounded further by the paucity of theoretically based research to improve our understanding of people’s organ donation decisions. This program of research contributes to our knowledge of individual decision making processes for three aspects of organ donation: (1) posthumous (upon death) donation, (2) living donation (to a known and unknown recipient), and (3) providing consent for donation by communicating donation wishes on an organ donor consent register (registering) and discussing the donation decision with significant others (discussing). The research program used extended versions of the Theory of Planned Behaviour (TPB) and the Prototype/Willingness Model (PWM), incorporating additional influences (moral norm, self-identity, organ recipient prototypes), to explicate the relationship between people’s positive attitudes and low rates of organ donation behaviours. Adopting the TPB and PWM (and their extensions) as a theoretical basis overcomes several key limitations of the extant organ donation literature including the often atheoretical nature of organ donation research, thefocus on individual difference factors to construct organ donor profiles and the omission of important psychosocial influences (e.g., control perceptions, moral values) that may impact on people’s decision-making in this context. In addition, the use of the TPB and PWM adds further to our understanding of the decision making process for communicating organ donation wishes. Specifically, the extent to which people’s registering and discussing decisions may be explained by a reasoned and/or a reactive decision making pathway is examined (Stage 3) with the novel application of the TPB augmented with the social reaction pathway in the PWM. This program of research was conducted in three discrete stages: a qualitative stage (Stage 1), a quantitative stage with extended models (Stage 2), and a quantitative stage with augmented models (Stage 3). The findings of the research program are reported in nine papers which are presented according to the three aspects of organ donation examined (posthumous donation, living donation, and providing consent for donation by registering or discussing the donation preference). Stage One of the research program comprised qualitative focus groups/interviews with university students and community members (N = 54) (Papers 1 and 2). Drawing broadly on the TPB framework (Paper 1), content analysed responses revealed people’s commonly held beliefs about the advantages and disadvantages (e.g., prolonging/saving life), important people or groups (e.g., family), and barriers and motivators (e.g., a family’s objection to donation), related to living and posthumous organ donation. Guided by a PWM perspective, Paper Two identified people’s commonly held perceptions of organ donors (e.g., altruistic and giving), non-donors (e.g., self-absorbed and unaware), and transplant recipients (e.g., unfortunate, and in some cases responsible/blameworthy for their predicament). Stage Two encompassed quantitative examinations of people’s decision makingfor living (Papers 3 and 4) and posthumous (Paper 5) organ donation, and for registering and discussing donation wishes (Papers 6 to 8) to test extensions to both the TPB and PWM. Comparisons of health students’ (N = 487) motivations and willingness for living related and anonymous donation (Paper 3) revealed that a person’s donor identity, attitude, past blood donation, and knowing a posthumous donor were four common determinants of willingness, with the results highlighting students’ identification as a living donor as an important motive. An extended PWM is presented in Papers Four and Five. University students’ (N = 284) willingness for living related and anonymous donation was tested in Paper Four with attitude, subjective norm, donor prototype similarity, and moral norm (but not donor prototype favourability) predicting students’ willingness to donate organs in both living situations. Students’ and community members’ (N = 471) posthumous organ donation willingness was assessed in Paper Five with attitude, subjective norm, past behaviour, moral norm, self-identity, and prior blood donation all significantly directly predicting posthumous donation willingness, with only an indirect role for organ donor prototype evaluations. The results of two studies examining people’s decisions to register and/or discuss their organ donation wishes are reported in Paper Six. People’s (N = 24) commonly held beliefs about communicating their organ donation wishes were explored initially in a TPB based qualitative elicitation study. The TPB belief determinants of intentions to register and discuss the donation preference were then assessed for people who had not previously communicated their donation wishes (N = 123). Behavioural and normative beliefs were important determinants of registering and discussing intentions; however, control beliefs influenced people’s registering intentions only. Paper Seven represented the first empirical test of the role of organ transplant recipient prototypes (i.e., perceptions of organ transplant recipients) in people’s (N = 465) decisions to register consent for organ donation. Two factors, Substance Use and Responsibility, were identified and Responsibility predicted people’s organ donor registration status. Results demonstrated that unregistered respondents were the most likely to evaluate transplant recipients negatively. Paper Eight established the role of organ donor prototype evaluations, within an extended TPB model, in predicting students’ and community members’ registering (n = 359) and discussing (n = 282) decisions. Results supported the utility of an extended TPB and suggested a role for donor prototype evaluations in predicting people’s discussing intentions only. Strong intentions to discuss donation wishes increased the likelihood that respondents reported discussing their decision 1-month later. Stage Three of the research program comprised an examination of augmented models (Paper 9). A test of the TPB augmented with elements from the social reaction pathway in the PWM, and extensions to these models was conducted to explore whether people’s registering (N = 339) and discussing (N = 315) decisions are explained via a reasoned (intention) and/or social reaction (willingness) pathway. Results suggested that people’s decisions to communicate their organ donation wishes may be better explained via the reasoned pathway, particularly for registering consent; however, discussing also involves reactive elements. Overall, the current research program represents an important step toward clarifying the relationship between people’s positive organ donation attitudes but low rates of organ donation and communication behaviours. Support has been demonstrated for the use of extensions to two complementary theories, the TPB and PWM, which can inform future research aiming to explicate further the organ donation attitude-behaviour relationship. The focus on a range of organ donation behaviours enables the identification of key targets for future interventions encouraging people’s posthumous and living donation decisions, and communication of their organ donation preference.

Globalization, frontier masculinities and violence : booze, blokes and brawls

Over the last two decades, two new trajectories have taken hold in criminology - the study of masculinity and crime, after a century of neglect, and the geography of crime. This article brings both those fields together to analyse the impact of globalisation in the resources sector on frontier cultures of violence. This paper approaches this issue through a case study of frontier masculinities and violence in communities at the forefront of generating resource extraction for global economies. This paper argues that the high rates of violence among men living in work camps in these socio-spatial contexts cannot simply be understood as individualised expressions of psycho-pathological deficit or social disorganisation. Explanations for these patterns of violence must also consider a number of key subterranean convergences between globalising processes and the social dynamics of male-on-male violence in such settings.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.