Journal of Coastal Research

SI 56

pg - pg

ICS2009 (Proceedings)

Portugal

ISSN

Unmanned Air Vehicles for coastal and environmental research E. Pereira†, R. Bencatel‡, J. Correia‡, L. Félix†, G. Gonçalves‡, J. Morgado† and J. Sousa‡ † Laboratório de Ciências e Tecnologias Aeronáuticas, Academia da Força Aérea, Sintra 2715-021, Portugal [email protected]

‡ Departamento de Engenharia Electrotécnica e Computadores, Faculdade de Engenharia do Porto, Porto 4200-465, Porto [email protected]

ABSTRACT PEREIRA, E., BENCATEL, R., CORREIA, J., FÉLIX, L., GONÇALVES, G., MORGADO, J. AND SOUSA, J., 2009. Unmanned Air Vehicles for coastal environmental research. Journal of Coastal Research, SI 56 (Proceedings of the 10th International Coastal Symposium), pg – pg. Lisbon, Portugal, ISBN (Leave the number of pages blank) In the last decade we have witnessed an unprecedented development of Unmanned Air Vehicles (UAVs) for missions with high societal impact. Future generations of UAV systems will reflect the major current trends: increased levels of autonomy, lower cost, longer endurance, and networking capabilities. Networking is one of the major trends for unmanned vehicle systems; it is also one of the enabling technologies for distributed cooperation (and computation). In mobile network systems, vehicles, sensors and operators interact through (inter-operated) communication networks. Dynamic networks of UAVs can be used in a broad range of missions like border patrol, tracking of pollution at sea, and oceanographic and environmental research. The Portuguese Air Force Academy and the School of Engineering at Porto University have been collaborating, since 2006, on the design, implementation and testing of different types of UAVs to demonstrate these technologies in a wide spectrum of military/civil missions. This is a multi-disciplinary cooperation encompassing several technological fields: advanced vision systems for identification and tracking of fixed and mobile features, cooperative control of teams of UAVs in mixed-initiative environments, sensor fusion and navigation systems. These technologies are being developed and integrated into UAV platforms for demonstration in military missions like reconnaissance, surveillance and target acquisition, and also in several civil missions like aerial gravimetry, aerial photography, surveillance and control of maritime traffic, fishing surveillance, and detection and control of coastal hazards. This paper reports on these developments and on the demonstrations that took place in the last two years. We report on video surveillance and environmental monitoring operations with six different types of fixed-wing UAVs (wingspans ranging from 1 to 6 meters), with autonomous take-off and landing capabilities. The smaller platforms can be easily deployed (hand-launched) while the others are more suitable for endurance and larger payloads. ADITIONAL INDEX WORDS: Mobile Sensor Network, Unmanned Air Vehicles

UAV OVERVIEW The challenge of flying unmanned aircraft has been present since the early days of aviation. Unmanned air vehicles evolved from rockets with guidance and navigation capabilities. Such capabilities turned these rockets into relatively precise long haul weapons commonly known as missiles. During World War I, several programs tried to build a reliable missile, but it was only during the World War II (WWII) that the German V-1 “Buzzbomb” proved to be the first successful cruise missile. After WWII, Unmanned Air Vehicles (UAVs) were also used as target drones to train fighter pilots, but the real advent of these systems started in the 60’s when the target drone “Firebee”, remote-controlled and equipped with optic cameras, was demonstrated in photography surveillance missions. At that time, UAVs started to be viewed as a reliable alternative to conventional manned aircrafts mainly on missions where the human presence is highly undesirable, e.g. persistent surveillance missions, combat missions or survey of contaminated areas. Those missions are commonly designated as “Dull, Dirty and Dangerous” missions.

Leveraged by the advances on sensors, communications and computation technologies, UAVs equipped with payloads such as Electro-Optic (EO) / Infra-Red (IR) cameras or Synthetic Aperture Radars (SAR) have been performing a wide set of military missions. These include Intelligence, Surveillance and Reconnaissance (ISR), Battle Damage Assessment (BDA), and target acquisition. These missions have been performed successfully by operational UAVs such as the MQ-1 Predator, RQ-4 Global Hawk and the RQ-2A Pioneer. More recently, Predators armed with Hellfire missiles performed combat missions in Afghanistan and Iraq. These combat missions showed the potential of a new type of UAVs: the Combat UAVs (UCAVs). UAVs are also attracting the attention of the civilian community as well. The proved surveillance capabilities of those systems present a serious alternative for missions such as surveillance of fishery activities, assessment of natural sea resources, surveillance of the exclusive economic zone, and forest fire surveillance. UAVs can also represent a cheaper solution for communication relays when compared with satellites, as demonstrated by the Vulture project funded by Defense Advanced Research Projects

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Agency (DARPA). Vulture is an ultra-long endurance UAV able to be aloft for five years. The United States National Oceanography and Atmosphere Administration (NOAA) have been using Unmanned Underwater Vehicles (UUV) and is planning to use UAVs to explore and gather atmospheric data. Researchers at NOAA are also interested in using UAVs to fulfill critical research and operational data collection gaps in several areas such as climate, weather and water, ecosystem monitoring and management, and coastal mapping. The National Space Administration (NASA) Altair UAV performed several demonstrations for NOAA flying over the Channel Islands in the Southern California coast. In these demonstrations, Altair mapped the ocean color, performed atmospheric chemistry measurements and observed marine mammals and their environment. These flights also conducted low-tide coastal mapping and law enforcement surveillance of the Channel Islands National Marine. There are several challenges facing the use of UAVs in civilian missions. These are mainly due to legal and technical constraints concerning the safety of flying on a non-segregated airspace. This paper is organized as follows in the section “UAV Systems” we described the testbed jointly developed by the Portuguese Air Force Academy (AFA) and the School of Engineering of Porto University (FEUP) to provide the background against which we will phrase our discussion; the section “UAVs in Coastal and Environmental Surveys” is a short state of the art on the use of UAVs on missions concerning coastal and environmental issues; section “Future Operations” highlights what are the expected operations in a near future; the “Challenges” section outlines the main challenges concerning the operation of UAV systems; the section “Predictive Essay” describes a coastal/environmental mission that could be performed in the near future; we finish the paper with some conclusions.

UAV SYSTEMS The System Breakdown Structure (SBS) for the AFA/FEUP Unmanned Air Vehicle Systems (UAS) is depicted in Figure 1.

The UAV systems are decomposed on three main subsystems: the UAVs, the Ground Station, and the Command, Control, Communications and Computations Interface (C4I). Each UAV is also decomposed in several subsystems such as the avionics systems, the airframe, the payload, the power system, and the actuators (engine and servos).

Airframes Currently, we are operating and developing six UAVs: ANTEX X03, ANTEX X02, Lusitânia, a Silver Fox (from Advanced Ceramics Research), a Nova-40 trainer and a hand launched flying wing.

Figure 1: SBS of the AFA/FEUP UAS

Figure 2: ANTEX X03 The ANTEX XX and the flying wing airframes are being developed by the Air Force Academy personal. Lusitânia, Silver Fox and the Nova-40 trainer are off-the-shelf platforms, which enabled us to quickly implement and test control concepts. ANTEX-M X03 (Figure 2) is a 6 meters wingspan aircraft equipped with a two stroke 3W engine (220cc and 22Hp). The current configuration allows us to use payloads heavier than 30kg. ANTEX X02 (figure 3) is a half-sized version of the ANTEXX03. ANTEX X02 and Lusitânia share the same computational and sensor configurations. Both airframes use a OS 91-FX engine (15cc and 2.9HP). The maximum payload weight is in the order of 5kg and the maximum flight time is close to 80 minutes. The flying wing is equipped with an electric motor and a video camera. The design aims to allow up to 1kg of payload, a nominal velocity of less than 50 knots and one hour maximum flight time. The wingspan is about 2 meters. In Table 1 we summarize the operational characteristics of our main airframes. ANTEX-X02 and ANTEX-X03 are being optimized in order to increase endurances. We expect to reach an endurance of 5-7h to X02 and 15h to X03.

Avionics Our UAVs are equipped with one of two off-the-shelf autopilots: Piccolo (Figure 5) from CloudCap Technology (VAGLIENTI et al., 2004) and Micropilot from Micropilot Inc. (MICROPILOT, 2005). The autopilot system consists of a central controller (ground station) and an onboard autopilot. A single user can control a number of autopilot-equipped UAVs through the Operator Interface (Piccolo) or Horizon (Micropilot) software. Both Piccolo and Micropilot allow the user to perform the typical mission lifecycle: specification, simulation, and supervision. Both autopilots use a 2.4 GHz radio link. The autopilot is controlled by an on-board computer. The onboard computer system is based on a PC104 stack equipped with a wireless modem. The on-board computer controls the autopilot and the mission sensors through serial ports and other Inpup/Output (I/O) ports. This arrangement is aimed at autonomous flight. It is also used for sensor data collection and to

Figure 3: ANTEX X02

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Table 1: Vehicles characteristics Antex Antex X02 X03 MTOW* (kg) 10 100 Wing Span (m) 2.4 6 Max. Speed (km/h) 151 130 Payload (kg) 4 30 Endurance (h) 0.8 0.3 * - Maximum Take-off Weight

Lusitânia 10 2.4 150 5 0.8

Fling Wing 3 1.6 90 0.4 0.3

Silver Fox 12.2 2.4 203 2.27 10

provide telemetry to the ground systems (GS).

Payload The UAVs carry a modular set of sensors, defined according to the mission goals. We use a several types of EO payloads that range from small wireless cameras (36mm x 36mm x 33mm), capable of real time video feed (with Line-of-Sight transmission at 2.4GHz) over distances of up to 8Km, to multi-spectral cameras for thorough visual analysis. We also use Near Infrared (NIR) for river detection or visual light for standard missions. Our platforms are developed in a modular way in order that other type of sensors can be easily integrated. We are developing an onboard power generation system in order to be able to integrate the most demanding payloads such as SAR.

Command and Control Framework We use the Neptus/Seaware/Dune software tool set, developed at Porto University, to command our UAVs. Neptus is a distributed command, control, communications and intelligence framework for operations with networked vehicles, systems, and human operators (DIAS et al., 2005). The interactions with human operators are classified according to the phases of a mission life cycle: world representation; planning; simulation; execution and post-mission analysis. Seaware is a middleware framework that addresses the problem of communications in heterogeneous environments with diverse requirements (MARQUES et al., 2006). Dune supports the implementation of the vehicle control architecture in a predictable and efficient manner for real-time performance. Neptus supports concurrent operations. Vehicles, operators, and operator consoles come and go. Operators are able to plan and supervise missions concurrently. Additional consoles can be built and installed on the fly to display mission related data over a network. Figure 6 depicts a UAV operator console built with the Neptus Console Builder (CB) application. This facilitates the addition of new vehicles with new sensor suites to Neptus. Neptus supports the control of several UAVs, Autonomous Underwater Vehicles (AUVs) and Autonomous Surface Vehicles (ASV) concurrently. There is a Seaware node per vehicle and per operator console (one per vehicle). Each vehicle node is characterized by a topic domain identifying the vehicle to allow

Figure 5: Piccolo avionics installed on the Lusitânia UAV

Figure 6: Neptus UAV operator console for a set of messages to be exchanged with the corresponding operator console. The system is easily configured for deployment in heterogeneous UAVs to carry out coordinated missions. This is because of the modular design and of the use of the publish/subscribe framework for communication. In future releases, the user will be able to easily add maneuvers to the system; this includes maneuvers for coordinated missions. The abstract vehicle interface protocol facilitates interactions and inter-operability with the Seaware publish/subscribe framework. Seaware defines the message topics and syntax for coordinating vehicles in a network. This allows us to build a network system composed of different types of entities such as control consoles, heterogeneous (AUVs, ASVs, UAVs) physical or simulated vehicles and fixed systems, which may come and go in a transparent way to the network.

UAVS IN COASTAL AND ENVIRONMENTAL SURVEYS The project RAVEN (Remote Aerial Vehicle for Environmentmonitoring) (O'YOUNG AND HUBBARD 2007) intends to develop a Beyond Line Of Sight (BLOS) control technology to enable a long-endurance UAV to perform safe and effective maritime surveillance operations in an harsh coastal environment. The project is focused in developing techniques that allow a longendurance UAV to perform inspection and enforcement under extreme weather conditions, being at the same time able to obtain high-texture imagery and also capable of doing a broad-area coverage and close-proximity inspection. On-board the UAV there is a PC104 connected to a digital high resolution camera and a digital video camera. There is also a frame-grabber that allows the video to be stored in a hard-disk. Image processing is done in the PC104 on-board the UAV, being the video transmitted through a satellite phone (Iridium) for supervision purposes only. Currently they are working on target detection and tracking. There next step will be detect/see and avoid (DSA) technology, which will enable commercial UAVs to operate in beyond line of sigh missions in non-segregated airspace. The use of High Definition (HD) video cameras to obtain aerial mapping of local beach erosion was tested in (CHONG 2007). A typical 8.3 mega-pixel digital camera takes 4.25 seconds to save the photo on the camera memory stick, which restricts the aircraft to fly at a minimum altitude of 500 meters at 120 knots to obtain a nominal stereo-overlap of 60%. This could be solved by using two digital cameras, but they decided to use two HD video cameras to avoid having to operate the cameras manually in accurate time. The two HD video cameras provide stereo-images, which can be

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used to produce digital topographic maps, Digital Terrain Models (DTM) and orthoimage or rectified photos. They tested the system with a Cessna single engine aircraft. Because of the aircraft vibration, double image of features is created, which they easily solved by applying a de-interlace filter to the video. They combine two frames of each camera with a 60% overlap between them and known GPS coordinates points in the images to produce a Digital Terrain Model of the area. The test results show that HD video cameras can provide good quality 3D measurement comparable in accuracy with measurement obtained using a still-frame good quality digital camera. They point out that further tests could be done using an UAV. An UAV produces more vibration than a normal aircraft, and they state that the de-interlace filter can be able to reduce the vibration effect in the video.

FUTURE OPERATIONS The last decades have witnessed unprecedented technological developments in computing, communications, navigation, control, composite materials and power systems, which have led to the design and deployment of the first generations of unmanned air vehicles. These developments enable scientists and engineers to develop visions for future systems, and applications, that could have not been imagined before. Transgenic biopolymers are a key technology for the development of ultra-lightweight airframes with lower Radar Cross Sections (RCS) suitable to use in the most dangerous combat missions such as the Strike/Suppression of Enemy Air Defenses (SEAD). UCAVs performing such missions could have their maneuverability increased by using smart materials to create morphing wings. The electrical and mechanical properties of carbon nano-tubes can be used to design antennas embedded in UAV airframes. The recent developments in fuel cells and solar panels will contribute to longer flight times. The goal of 24/7 missions is achievable with current technologies for some specific mission profiles, such as persistent coastal surveillance or communication relaying, The emergence of Microelectromechanical systems (MEMS) is leveraging the development of Micro-UAV systems (MAVs) to be used for stealth reconnaissance missions. These technologies pave the route to operations in urban areas and inside buildings. The cooperative control of unmanned vehicles is a new research area that will provide teams of unmanned vehicles with the capability to operate in a network environment with higher efficiency and effectiveness when compared with stand-alone systems. Swarms of networked low altitude MAVs will change the paradigm of surveillance missions by allowing high resolution imagery with low cost systems. Cooperative control will also provide autonomous reconfigurable teams in persistent surveillance missions. The advances on video imaging payloads together with multispectral image processing will allow UAVs to detect and track fixed and mobile features (e.g. cars, boats, roads, and coast border) based on their multispectral signature. This kind of systems has interesting coastal applications such as tracking of biological species, coastal patrol, pollution and coastal mapping.

CHALLENGES One of the most difficult challenges facing the operation of UAVs concerns the insertion of these systems in non-segregated airspace. This stems from the strict safety requirements for manned aircraft. The process of ensuring compliance to these requirements is commonly known as “Air Worthiness Certification”. The air worthiness certification depends on several factors such as the size

of the UAVs, the type of the mission, the operational altitude and the maximum endurance. Several civil and military organizations are working, individually or in joint groups, in order to define the air worthiness requirements to certificate several types of UAVs. In 2005, the United States Federal Aviation Administration (FAA) published a memorandum (AFS-400 UAS Policy 05-01) with some technical and operational requirements. The European Organization for Civil Aviation Equipment (EuroCAE) established a working group (WG73) that aims at the definition of the operational concepts for UAVs. WG73 also wants to develop capabilities to supervise and monitor the standards, equipment requirements, and production processes regarding civilian UAVs. In the military field, the North Atlantic Treaty Organization (NATO) under the joint working group “Flight In Non-Segregated Air Space” (FINAS) is working on several Standard Agreements (STANAGs) in order to recommend and document NATO-wide guidelines to allow the cross-border operation of UAVs in nonsegregated airspace. UAV Systems Airworthiness Requirements are defined at the STANAG 46711. Besides airworthiness requirements, FINAS is also working on UAV Operator Training (STANAG 4670), on the application of human-interface engineering for UAV systems (“Study” 4685), and on the functional requirements for the Sense & Avoid systems. Achieving a widely accepted Sense & Avoid system is probably the most important technological challenge concerning the safe operation of UAVs in non-segregated airspace. In conventional aviation, the Traffic Collision Avoidance System (TCAS) is widely used in the world. However, TCAS puts the final responsibility of the execution of the resolution maneuvers on the hands of the pilot. Thus, UAVs should have a “sense and avoid” system that emulates the human behavior facing TCAS warnings. Documents, such as the NATO STANAGs, are crucial to enable the interoperability of systems, allowing a faster certification of new UAV systems or sub-systems, such as command and control interfaces. The STANAG 4586 establishes a common protocol to facilitate the interoperability of various, heterogeneous vehicles from a common control station. It is an effective standard for both military and emerging commercial unmanned vehicle applications. The problem of navigation in environments with denied GNSS (Acronym for Global Navigation Satellite System) is also challenging both the academic and the industrial communities. Vision-based and Inertial-based navigation techniques have been developed to allow the operation of UAVs in indoor and urban environments lacking reliable GNSS (see HE et al., 2008). In (BENCATEL et al., 2008) we find a set of river-tracking control algorithms based solely on video signals.

PREDICTIVE ESSAY This section outlines an operational scenario, involving networks of UAVs with mixed-initiative interactions, which could take place in the next 5 to 10 years. By mixed initiative interactions it is meant the intervention of human operators in the planning and control loops. We focus on an environmental monitoring mission using evolutions of the current AFA/FEUP UAS. Our scenario is motivated by the persistent surveillance of an environmental disaster such as the oil spill from the “Prestige” tanker that took place in November 2002, 45km off the coast of Galicia, Spain. The Portuguese Air Force monitored the evolution of this disaster by performing 81 missions with C212-300 Aviocar aircrafts. Figure 7 depicts the evolution with time of the oil spills. 1

More about air worthiness certification can be found in http://www.uavm.com/uavregulatory/airworthinesscertification.ht ml.

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The year is 2015. The maritime authorities trigger an alarm about an incident with an oil tanker 50 km off the coast of Ovar, Portugal. A Joint Task Force (JTF) with members from the Air Force, Navy, local authorities, and civil protection is created to address the control and surveillance of the oil spill. The JTF Command and Control Center (CCC) is located at the Ovar Air Force Base. In order to have a quick evaluation of the situation, the JTF designated the following means to perform the first site survey: • 1 CASA C-295 aircraft from the Portuguese Air Force; • 1 frigate from the Portuguese Navy, with 5 ANTEXX02 UAVs (with 3.5 m wingspan and endurance of ~15hours) equipped with EO/IR payloads. The two C-295 take-off from Montijo Air Base, fly to the disaster area and identify the precise location of the tanker. This information is sent through a military tactical data link (link-22) to the CCC and to the frigate. JTF gives orders to the frigate to move to that location. When the frigate reaches the tanker, one X02 is launched with a catapult. The mission goal is to identify, track and provide imagery data of the oil spill for an initial assessment. On-board image processing is used to detect and monitor the evolution of the spill. The X02 autonomously tracks the spill, and sends imagery data to the frigate. The data is then sent by a satellite link to the CCC. Experts at the CCC decide that the disaster zone has to be constantly surveyed by at least two UAVs until the oil spill is fully contained. The UAVs from the frigate are not able to accomplish this mission due to limited endurance and capabilities. The Portuguese Air Force is contacted and the following means are dispatched to Ovar Air Base: • 5 ANTEX-X03 (with 7m wingspan and 30 hours of minimum endurance) with EO/IR and SAR payloads; • 1 Ground Station (GS); • A team of operators and maintenance technicians; • Logistics (power shelters, maintenance utilities…); The operator at the GS is responsible for UAV mission planning and supervision, for accepting or denying replacement procedures, and for examining the data packages. In the event of an unforeseen situation, the operator can change the mission plans, remotely control an UAV, or even handover the UAVs to another GS. With the available intel the operator first plans the missions to be executed by the UAVs. Prior to take-off, the operator asks for authorization from the local Air Traffic Control (ATC) to fly in a non-segregated airspace. When the authorization is granted, the operator commands three X03 to take-off and fly to the disaster zone. The other two X03 stay at a high readiness level in the airfield to replace the first UAVs during refueling. When the three X03 reach a predetermined distance from the disaster zone, they start loitering and the operator at the GS asks

for a mission handover to the X02 Command and Control located at the frigate. The operator in the frigate accepts the handover and the X02 is autonomously recovered with a net mounted on the frigate. The X03s start tracking the oil spill using multispectral and SAR imagery. The imagery data is sent to the GS for data fusion into a map for situational awareness. The map is available in real-time to the CCC. By accessing other sources of information, the operator has positive identification for other affected areas and reconfigures the team’s plan to include the new areas.

CONCLUSIONS AND FUTURE WORK This paper is aimed at fostering the development of UAV based solutions to environmental and coastal problems using networked teams of UAVs. In order to achieve this objective, we provide a short background on UAVs and outline the main challenges concerning the utilization of these systems in civil missions, particularly on environmental and coastal missions. In order to better illustrate the advantages of having UAVs in such missions, we give an example of a prospective mission in an environmental disaster scenario. This discussion is aimed at promoting the public and institutional awareness of UAV systems, thus contributing to the development of new initiatives with high societal interest. The problem of flying in non restricted airspace is still a major constraint. However, efforts from several organizations are starting to produce results and we believe that in a near future we will UAVs performing civil missions.

LITERATURE CITED ALMEIDA, P.; BENCATEL, R.; GONÇALVES, G. M.; SOUSA, J. B., RUETZ, C., September 2007. Experimental results on Command and Control of Unmanned Air Vehicle Systems. 6th IFAC Symposium on Intelligent Autonomous Vehicles (IAV’07), France. BENCATEL, R., JOÃO, C., SOUSA, J., GONÇALVES, G., PEREIRA, E., October 20-22, 2008. Video tracking control algorithms for Unmanned Air Vehicles. 1st Annual Dynamic Systems and Control Conference, Ann Arbor, Michigan, USA. DIAS, P.S.; FRAGA, S.L.; GOMES, R.M.F.; GONÇALVES, G.M.; PEREIRA, F.L.; PINTO, J.; SOUSA, J.B., 20-23 June 2005. Neptus - a framework to support multiple vehicle operation. Oceans 2005 – Europe, Volume 2, Page(s): 963 – 968. CHONG, A.K., 2007. HD aerial video for coastal zone ecological mapping. The 19th Annual Colloquium of the Spatial Information Research Centre. HE, R., PRENTICE S., AND ROY N., May 19-23, 2008. Planning in Information Space for a Quadrotor Helicopter in a GPS-denied Environment. IEEE Int. Conf. on Robotics and Automation Pasadena, CA, USA. MARQUES, EDUARDO; GONÇALVES, GIL; SOUSA, JOÃO, 2006. Seaware: A Publish/Subscribe Middleware for Networked Vehicle Systems, 7th Conf. on Manoeuvreing and Control of Marine Craft (MCMC’2006), Lisboa, Portugal. MATEUS, P., April 2003. The Portuguese Air Force in operation Prestige. Revista Mais Alto. Micropilot User’s Manual, www.micropilot.com, 2005 O'YOUNG, S. AND HUBBARD, P., 2007. RAVEN: A maritime surveillance project using small UAV. 2007. IEEE Conf. on Emerging Technologies & Factory Automation, pp. 904-907. VAGLIENTI, B.; HOAG, R.; NICULESCU M., Piccolo system user guide, July 2004, www.cloudcaptech.com

Figure 7: Evolution of the oil spots of “Prestige” leakage Source: MATEUS, 2003. Journal of Coastal Research, Special Issue 56, 2009