Unmanned Aerial Mapping Solution for Small Island

Unmanned Aerial Mapping Solution for Small Island Developing States Raid Al-Tahir, Marcus Arthur Department of Geomatics Engineering and Land Management The University of the West Indies, TRINIDAD AND TOBAGO Abstract Developing countries are characterized by rapid urban growth and dynamic changes in land use patterns. The majority of this urban growth in small island developing states (SIDs) occurs in coastal areas and other environmentally sensitive areas. Knowledge and mapping of urbanization and other land use trends provides critical information in support of sustainable development and environmental protection. On the other hand, deficiencies in spatial data and their currency create challenges for informed decision making in these regards. Remote sensed data from airborne and space borne sensors provide a significant source of spatial information for the national medium/large scale topographic and land cover maps. Despite the obvious benefits and seeming ease of mapping using these techniques, they remain underutilized by the small islands due to mainly the high costs and the required specialized personnel and equipment. Unmanned Air Vehicle (UAV) provide a viable and affordable alternative, especially for small area coverage. When compared to conventional satellite and airborne imaging, unmanned air systems have the advantages of providing more flexible, rapid, efficient, and weather independent data acquisition. This paper presents an overview and appraisal of the technology considering the cost factor and the operational nature in the tropical small developing islands of the Caribbean. The paper proposes certain criteria for the consideration of a suitable system for the region with a focus on maintaining a low cost system while still achieving adequate accuracies and response speeds. Finally, the paper deliberates on the relevant workflow and photogrammetric aspects of image acquisition and processing. Keywords: Small Island Developing States, UAV, Aerial Mapping.

1 INTRODUCTION 1.1 Background It is predicted that by the year 2030, about 85% of the population in Latin America and the Caribbean will live in urban areas (Cohen, 2006). The majority of this urban growth in small island developing states (SIDs) occurs in coastal areas and other environmentally sensitive areas. The low-lying states of the Caribbean are already characterized by their highly fragile ecosystems and high dependency on their marine and coastal resources. These islands are also experiencing accelerated economic development coupled with a fast rate of industrialization, illegal settlement of agricultural prime lands, urbanization, and population growth (EMA, 2001). The vulnerability of the Caribbean islands to natural disasters and the pressure on their ecosystems are expected to be further exacerbated by climate change (altered rainfall patterns, more frequent or intense extreme weather events, and rising sea levels). Climate change will impact on the infrastructure, water management, agriculture, ecosystems (e.g., forests and coral reefs), land use, and the economy (WRI, 2011). Effective adaptation to climate change impacts, sustainable development, and protecting the environment require user-driven, sufficient, accurate, accessible, long-term, frequently updated, cost-effective and targeted information (WRI, 2011). More specifically, high quality and timely spatial information is imperative for monitoring the changes on land, understanding the dynamics of those changes, and drawing up governance and concerted management methods (FAO, 2002). The infrastructure and capacity of the Caribbean states to gather and distribute adequate and accurate information necessary for decision making are challenged by their small geographic size, financial constraints, and limited technological resources (UNDP, 2002). Information needed for accurate planning is often outdated, non-existent, or too expensive and laborious to acquire (Al-Tahir et al., 2006). Deficiencies in data currency create obstacles towards informed decision making and the formation of national planning policies for managing the environment in many Caribbean island states. 1.2 The Role of Geoinformatics and Unmanned Aerial Vehicles Remote sensed data from airborne and space borne sensors provide a significant source of spatial information for mapping and monitoring the surface of the Erath. Geo-imaging techniques offer various advantages: extensive

coverage, reliable and current data, and cost efficiency. Besides, they provide a unique opportunity to study the impact of land-use changes as a dynamic process in time and space and to formulate, as a result, proactive solutions to environmental spatial issues. Despite the obvious benefits and seeming ease of mapping small island states using satellite and aerial imagery, this technology remains underutilized by the developing islands due to the high costs, specialized personnel, equipment, and availability of relevant imagery necessary for mapping (Al-Tahir et al., 2006; Gianinetto et al., 2004; Specter and Gayle, 1990). As such, and considering their sizes, none of the individual Caribbean states possess the indigenous capacity and means for acquiring aerial photography. Specific to tropical environments such as of the Caribbean region, a persistent cloud cover adds another hindrance to the use of satellite images (Al-Tahir et al., 2006). Valuable data are lost due to the clouds by directly obstruction the surface beneath them, and by the shadows they cast. These areas of obstruction represent information gaps and. As such, cloud cover poses a major challenge to the use of optical wavelength satellite images despite their worldwide successful use for mapping and monitoring. Unmanned aerial systems (UAS) provide a viable alternative to the use of conventional aerial photography. Such systems incorporate the use of a small unmanned aerial vehicle (UAV) and low cost imaging sensors such as off-theshelf digital cameras and GPS/IMU units. When compared to traditional airborne platforms, UAVs have the ability to provide data at a higher temporal resolution, more economic cost, avoid cloud obstructions, provide more flexible data acquisition, and still keeping high accuracy potential (Aber et al., 2010; Eisenbeiβ, 2009; Remondino et al., 2011). 2. UNMANNED AERIAL VEHICLES The term unmanned aerial vehicle refers to an aircraft without an on-board human pilot. UAVs can be remotely controlled aircraft (e.g. flown by a pilot at a ground station) or can fly autonomously based on pre-programmed flight plans or more complex dynamic automation systems. Unmanned aerial vehicles have seen unprecedented levels of growth in military and civilian application domains (Valavanis, 2007). In the last five years only, the total quantity of UAVs has more than doubled, and so is the quantity of producers and developers. In the same period, the number of civilian applications has increased three folds, while research applications grew two folds (UAV International, 2010). The increased demand for UAVs is typically attributed to the

low manufacturing and operational costs, flexibility of the platforms to accommodate the consumer’s particular needs and the elimination of the risk to pilots’ lives in difficult missions (Sarris, 2001). The continuous trend in the miniaturisation of electronics enables the production of smaller UAVs while simultaneously equipping them with cameras and other sensors to support aerial geo-data collection (Lemmens, 2011). With low cost, small, and lightweight integrated GNSS and inertial navigation systems, UAVs can be navigated with decimetre accuracy and the acquired orientation parameters can reduce the number of ground control points needed for postprocessing (Eisenbeiß, 2004). 2.1 Mapping Applications of UAVs Unmanned vehicles are being increasingly used for several areas of civilian and industrial applications and have the potential to be used in many more (Sarris, 2001; Skaloud et al., 2006; Valavanis, 2007). UAVs are being used in industrial and agricultural applications (such as crops spraying), facility management and construction (e.g, open-pit mines, power lines, and transportation infrastructure). UAVs are also of advantage to geoinformatics applications, such as cartography, corridor mapping, hydrologic monitoring, urban planning, fly-through, and archaeological mapping. Additionally, UAVs equipped with the appropriate payloads would have a tremendous impact on measuring parameters required for scientific researches of any nature (environmental, near-shore and marine, atmospheric, pollution etc) as they provide access to phenomena of interest far closer than previously possible (Skaloud et al., 2006). UAV platforms with cameras can quickly deliver high temporal and spatial resolution image information and to allow a rapid response in a number of critical situations where immediate access to 3D geo-information is crucial such as earthquakes, landslides, erosion, mud flows, floods, and fire detection, as well as real-time link for the search and rescue operations (Remondino et al., 2011). 2.2 Categorization of UAV Systems The variability of platforms presents unique challenges in categorizing the full range of available UAVs. The most commonly used criterion for classification is the range and altitude configuration. Based on these values, Table 1 lists the types of UAV relevant to this study, with additional information on the weight of the payload and endurance. Beyond these five categories lie several other classes with ranges (> 100km), altitudes (> 3km), and speeds that are more relevant to military strategic interests (UAV International, 2010).

Table 1: Extract of UAV Categories (UAV International, 2010)

UAV Categories Nano (η) Micro (µ) Mini Close Range Short Range

Range (km)