YOUMARES 8 – Oceans Across Boundaries: Learning from each other

This open access book presents the proceedings volume of the YOUMARES 8 conference, which took place in Kiel, Germany, in September 2017, supported by the German Association for Marine Sciences (DGM). The YOUMARES conference series is entirely bottom-up organized by and for YOUng MARine RESearchers. Qualified early career scientists moderated the scientific sessions during the conference and provided literature reviews on aspects of their research field. These reviews and the presenters’ conference abstracts are compiled here. Thus, this book discusses highly topical fields of marine research and aims to act as a source of knowledge and inspiration for further reading and research

Information Systems for Supporting Fire Emergency Response

Despite recent work on information systems, many first responders in emergency situations are unable to develop sufficient understanding of the situation to enable them to make good decisions. The record of the UK Fire and Rescue Service (FRS) has been particularly poor in terms of providing the information systems support to the fire fighters decision-making during their work. There is very little work on identifying the specific information needs of different types of fire fighters. Consequently, this study has two main aims. The first is to identify the information requirements of several specific members of the FRS hierarchy that lead to better Situation Awareness. The second is to identify how such information should be presented. This study was based on extensive data collected in the FRS brigades of three counties and focused on large buildings having a high-risk of fire and four key fire fighter job roles: Incident Commander, Sector Commander, Breathing Apparatus Entry Control Officer and Breathing Apparatus Wearers. The requirements elicitation process was guided by a Cognitive Task Analysis (CTA) tool: Goal Directed Information Analysis (GDIA), which was developed specifically for this study. Initially appropriate scenarios were developed. Based on the scenarios, 44 semi-structured interviews were carried out in three different elicitation phases with both novice and experienced fire fighters. Together with field observations of fire simulation and training exercises, fire and rescue related documentation; a comprehensive set of information needs of fire fighters was identified. These were validated through two different stages via 34 brainstorming sessions with the participation of a number of subject-matter experts. To explore appropriate presentation methods of information, software mock-up was developed. This mock-up is made up of several human computer interfaces, which were evaluated via 19 walkthrough and workshop sessions, involving 22 potential end-users and 14 other related experts. As a result, many of the methods used in the mock-up were confirmed as useful and appropriate and several refinements proposed. The outcomes of this study include: 1) A set of GDI Diagrams showing goal related information needs for each of the job roles with the link to their decision-making needs, 2) A series of practical recommendations suitable for designing of human computer interfaces of fire emergency response information system, 3) Human computer interface mock-ups for an information system to enhance Situation Awareness of fire fighters and 4) A conceptual architecture for the underlying information system. In addition, this study also developed an enhanced cognitive task analysis tool capable of exploring the needs of emergency first responders. This thesis contributes to our understanding of how information systems could be designed to enhance the Situation Awareness of first responders in a fire emergency. These results will be of particular interest to practicing information systems designers and developers in the FRS in the UK and to the wider academic community

UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

USCID water management conference

Presented at Emerging challenges and opportunities for irrigation managers: energy, efficiency and infrastructure: a USCID water management conference held on April 26-29, 2011 in Albuquerque, New Mexico.Includes bibliographical references.Verifying conservation estimates for on-farm agricultural water conservation programs -- Improving irrigation system performance in the Middle Rio Grande through scheduled water delivery -- Urbanization of irrigation districts in the Texas Rio Grande River Basin -- Urbanization issues in the Middle Rio Grande Conservancy District -- From canyons to canals: applying regulated river research to canal bank analysis -- Water for irrigation, streams and economy: evaluating past and future climate change to secure a reliable water supply for multiple needs -- Flow measurement capabilities of diversion works in the Rio Grande Project area -- Open-channel and pipe flow measurement at Mohave Valley Irrigation and Drainage District using Venturi technology with bubbler sensors -- Using an ADCP to determine canal seepage losses in the Middle Rio Grande Conservancy District -- Venturi meters constructed with pipe fittings: an under-appreciated option for measuring agricultural water -- Improving crop water use determination using adjusted eddy covariance heat fluxes -- Performance evaluation of TDT soil water content and Watermark soil water potential sensors -- Meeting water challenges in Idaho through water banking -- Water transfers in California: 20 years of progress, view to the future

Planning Algorithms for Multi-Robot Active Perception

A fundamental task of robotic systems is to use on-board sensors and perception algorithms to understand high-level semantic properties of an environment. These semantic properties may include a map of the environment, the presence of objects, or the parameters of a dynamic field. Observations are highly viewpoint dependent and, thus, the performance of perception algorithms can be improved by planning the motion of the robots to obtain high-value observations. This motivates the problem of active perception, where the goal is to plan the motion of robots to improve perception performance. This fundamental problem is central to many robotics applications, including environmental monitoring, planetary exploration, and precision agriculture. The core contribution of this thesis is a suite of planning algorithms for multi-robot active perception. These algorithms are designed to improve system-level performance on many fronts: online and anytime planning, addressing uncertainty, optimising over a long time horizon, decentralised coordination, robustness to unreliable communication, predicting plans of other agents, and exploiting characteristics of perception models. We first propose the decentralised Monte Carlo tree search algorithm as a generally-applicable, decentralised algorithm for multi-robot planning. We then present a self-organising map algorithm designed to find paths that maximally observe points of interest. Finally, we consider the problem of mission monitoring, where a team of robots monitor the progress of a robotic mission. A spatiotemporal optimal stopping algorithm is proposed and a generalisation for decentralised monitoring. Experimental results are presented for a range of scenarios, such as marine operations and object recognition. Our analytical and empirical results demonstrate theoretically-interesting and practically-relevant properties that support the use of the approaches in practice