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.

Green Falcon and Raptor UAV for remote gas sensing

This report documents showcases my learning experiences and design of Green Falcon Solar Powered UAV. Only responsible aspects will be discussed inside this report. Using solar power that is captured by solar panels it can fly all day and also store power for night flying. Its major advantage lies in the fact that it is simple and versatile, which makes it applicable to a large range of UAVs of different wingspans. Green Falcon UAV is designed as a supporting tool for scientists to get a deeper understanding of gases exchange amongst ground plane and atmosphere

An investigation into drink driving among aboriginal and Torres strait islander peoples in regional and remote Queensland and the development of the 'Hero to Healing' program

This program of research investigated the factors facilitating drink driving in Indigenous communities in Far North Queensland. Drink driving-related road crashes are a significant health burden for Indigenous people, as they die in road crashes at three times the rate of other Australians and are 30% more likely to be seriously injured. This research provided information to develop and pilot a culturally-specific program, 'Hero to Healing'. The main motivation to drink drive was related to 'kinship pressure; where drivers were pressured by family members to drive after drinking. The underlying responsibility for transporting family members was related to cultural values and involved responding to family needs as a priority. Exposure to older family members drink driving was considered to play a role in normalising the behaviour, leading to imitation into adulthood. The research highlighted the need to treat drink driving as a community issue, rather than an individual phenomenon.

Nutrition in remote Aboriginal communities: Lessons from Mai Wiru and the Anangu Pitjantjatjara Yankunytjatjara Lands

Objective To examine the impact of efforts to improve nutrition on the Anangu Pitjantjatjara Yankunytjatjara (APY) Lands from 1986, especially in Mai Wiru stores. Methods Literature was searched in a systematic manner. In 2012, the store-turnover method was used to quantify dietary intake of the five APY communities that have a Mai Wiru (good food) store. Results were compared with those available from 1986. Prices of a standard market basket of basic foods, implementation of nutrition policy requirements and healthy food checklists were also assessed in all seven APY community stores from 2008 and compared with available data from 1986. Results Despite concerted efforts and achievements decreasing intake of sugar and increasing the availability and affordability of healthy foods, particularly fruit and vegetables, and consequent improvements in some nutrient indicators, the overall effect has been a decrease in diet quality as indicated primarily by the increased supply and proportion of energy intake from discretionary foods, particularly sugar-sweetened beverages, convenience meals and take-away foods. Conclusions The study findings reinforce the notion that, in the absence of supportive regulation and market intervention, adequate and sustained resources are required to improve nutrition and prevent diet-related chronic disease on the APY Lands. Implications This study also provides insights into food supply/security issues affecting other remote Aboriginal communities and wider Australia.

A Touch of Red : Archaeological and Ethnographic Approaches to Interpreting Finnish Rock Paintings

Approximately 125 prehistoric rock paintings have been found in the modern territory of Finland. The paintings were done with red ochre and are almost without exception located on steep lakeshore cliffs associated with ancient water routes. Most of the sites are found in the central and eastern parts of the country, especially on the shores of Lakes Päijänne and Saimaa. Using shore displacement chronology, the art has been dated to ca. 5000 – 1500 BC. It was thus created mainly during the Stone Age and can be associated with the so-called ‘Comb Ware’ cultures of the Subneolithic period. The range of motifs is rather limited, consisting mainly of schematic depictions of stick-figure humans, elks, boats, handprints and geometric signs. Few paintings include any evidence of narrative scenes, making their interpretation a rather difficult task. In Finnish archaeological literature, the paintings have traditionally been associated with ’sympathetic’ hunting magic, or the belief that the ritual shooting of the painted animals would increase hunting luck. Some writers have also suggested totemistic and shamanistic readings of the art. This dissertation is a critical review of the interpretations offered of Finnish rock art and an exploration of the potentials of archaeological and ethnographic research in increasing our knowledge of its meaning. Methods used include ’formal’ approaches such as archaeological excavation, landscape analysis and the application of neuropsychological research to the study of rock art, as well as ethnographically ’informed’ approaches that make use of Saami and Baltic Finnish ethnohistorical sources in interpretation. In conclusion, it is argued that although North European hunter-gatherer rock art is often thought to lie beyond the reach of ‘informed’ knowledge, the exceptional continuity of prehistoric settlement in Finland validates the informed approach in the interpretation of Finnish rock paintings. The art can be confidently associated with shamanism of the kind still practiced by the Saami of Northern Fennoscandia in the historical period. Evidence of similar shamanistic practices, concepts and cosmology are also found in traditional Finnish-Karelian epic poetry. Previous readings of the art based on ‘hunting magic’ and totemism are rejected. Most of the paintings appear to depict experiences of falling into a trance, of shamanic metamorphosis and trance journeys, and of ‘spirit helper’ beings comparable to those employed by the Saami shaman (noaidi). As demonstrated by the results of an excavation at the rock painting of Valkeisaari, the painted cliffs themselves find a close parallel in the Saami cult of the 'sieidi', or sacred cliffs and boulders worshipped as expressing a supernatural power. Like the Saami, the prehistoric inhabitants of the Finnish Lake Region seem to have believed that certain cliffs were ’alive’ and inhabited by the spirit helpers of the shaman. The rock paintings can thus be associated with shamanic vision quests, and the making of ‘art’ with an effort to socialize the other members of the community, especially the ritual specialists, with trance visions. However, the paintings were not merely to be looked at. The red ochre handprints pressed on images of elks, as well as the fact that many paintings appear ’smeared’, indicate that they were also to be touched – perhaps in order to tap into the supernatural potency inherent in the cliff and in the paintings of spirit animals.

Remote sensing of nitrogen and water stress in wheat

Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Evaluation of a remote drafting system for regulating sheep access to supplement

Remote drafting technology now available for sheep makes possible targeted supplementation of individuals within a grazing flock. This system was evaluated by using 68 Merino wethers grazing dry-season, native Mitchell grass pasture (predominantly Astrebla spp.) as a group and receiving access to lupin grain through a remote drafter 0, 1, 2, 4 or 7 days/week for 8 weeks. The sole paddock watering point was separately fenced and access was via a one-way flow gate. Sheep exited the watering point through a remote drafter operated by solar power and were drafted by radio frequency identification (RFID) tag, according to treatment, either back into the paddock or into a common supplement yard where lupins were provided ad libitum in a self-feeder. Sheep were drafted into the supplement yard on only their first time through the drafter during the prescribed 24-h period and exited the supplement yard via one-way flow gates in their own time. The remote drafter operated with a high accuracy, with only 2.1% incorrect drafts recorded during the experimental period out of a total of 7027 sheep passes through the remote drafter. The actual number of accesses to supplement for each treatment group, in order, were generally less than that intended, i.e. 0.02, 0.69, 1.98, 3.35 and 6.04 days/week. Deviations from the intended number of accesses to supplement were mainly due to sheep not coming through to water on their allocated day of treatment access, although some instances were due to incorrect drafts. There was a non-linear response in growth rate to increased frequency of access to lupins with the growth rate response plateauing at similar to 3 actual accesses per week, corresponding to a growth rate of 72.5 g/head. day. This experiment has demonstrated the application of the remote drafting supplementation system for the first time under grazing conditions and with the drafter operated completely from solar power. The experiment demonstrates a growth response to increasing frequency of access to supplement and provides a starting point with which to begin to develop feeding strategies to achieve sheep weight-change targets.

Design and Simulation of a Solar Powered UAV for Remote Sensing Tasks Technical Report

This research deals with the development of a Solar-Powered UAV designed for remote sensing, in particular to the development of the autopilot sub-system and path planning. The design of the Solar-Powered UAS followed a systems engineering methodology, by first defining system architecture, and selecting each subsystem. Validation tests and integration of autopilot is performed, in order to evaluate the performances of each subsystem and to obtain a global operational system for data collection missions. The flight tests planning and simulation results are also explored in order to verify the mission capabilities using an autopilot on a UAS. The important aspect of this research is to develop a Solar-Powered UAS for the purpose of data collection and video monitoring, especially data and images from the ground; transmit to the GS (Ground Station), segment the collected data, and afterwards analyze it with a Matlab code.

Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model

Background: Standard methods for quantifying IncuCyte ZOOM™ assays involve measurements that quantify how rapidly the initially-vacant area becomes re-colonised with cells as a function of time. Unfortunately, these measurements give no insight into the details of the cellular-level mechanisms acting to close the initially-vacant area. We provide an alternative method enabling us to quantify the role of cell motility and cell proliferation separately. To achieve this we calibrate standard data available from IncuCyte ZOOM™ images to the solution of the Fisher-Kolmogorov model. Results: The Fisher-Kolmogorov model is a reaction-diffusion equation that has been used to describe collective cell spreading driven by cell migration, characterised by a cell diffusivity, D, and carrying capacity limited proliferation with proliferation rate, λ, and carrying capacity density, K. By analysing temporal changes in cell density in several subregions located well-behind the initial position of the leading edge we estimate λ and K. Given these estimates, we then apply automatic leading edge detection algorithms to the images produced by the IncuCyte ZOOM™ assay and match this data with a numerical solution of the Fisher-Kolmogorov equation to provide an estimate of D. We demonstrate this method by applying it to interpret a suite of IncuCyte ZOOM™ assays using PC-3 prostate cancer cells and obtain estimates of D, λ and K. Comparing estimates of D, λ and K for a control assay with estimates of D, λ and K for assays where epidermal growth factor (EGF) is applied in varying concentrations confirms that EGF enhances the rate of scratch closure and that this stimulation is driven by an increase in D and λ, whereas K is relatively unaffected by EGF. Conclusions: Our approach for estimating D, λ and K from an IncuCyte ZOOM™ assay provides more detail about cellular-level behaviour than standard methods for analysing these assays. In particular, our approach can be used to quantify the balance of cell migration and cell proliferation and, as we demonstrate, allow us to quantify how the addition of growth factors affects these processes individually.

Remote sensing applications for cotton.

This paper compares classified normalized difference vegetation index images of cotton crops derived from both low and high resolution satellite imagery to determine the most accurate and feasible option for Australian cotton growers. It also demonstrates a rapid automated processing and internet delivery system for distributing satellite SPOT-2 imagery. Also provided is the profile of two case studies conducted in the Darling Towns demonstrating the potential benefit of adopting this technology for improving in-season agronomic crop assessments and therefore enable improved management decisions to be made.

Environment characterization as an aid to wheat improvement: interpreting genotype-environment interactions by modelling water-deficit patterns in North-Eastern Australia.

Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Remote Sensing - based precision agriculture tool for the sugar industry

The project will produce practical and relevant benchmarks, protocols and recommendations for the adoption of remote sensing technologies for improved in season management and therefore production within the Australian sugar cane industry.

Remote sensing to implement an effective pest management strategy for canegrubs

Develop a remote-sensing system that can identify canegrub infestations and provide early- warning to growers via the internet.

Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.