Wildlife tracking data management: a new vision

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioral data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals’ environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

Evaluation of a Passive Millimeter Wave (PMMW) imager for wire detection in degraded visual conditions

Ground vehicle tests have been performed to evaluate the performance of a Passive Millimeter Wave (PMMW) imager in reduced visibility conditions and in particular, the ability to detect power lines and cables. A PMMW imager was
compared with Long Wave Infrared (LWIR) and visible imaging cameras. The three sensors were mounted on a Land Rover, together with GPS and digital recording system. All three sensors plus the GPS data were recorded simultaneously in order to provide direct comparisons. The vehicle collected imagery from a number of sites in the vicinity of Malvern, UK, in January, 2008. Imagery was collected both while the vehicle was stationary at specific sites
and while it was moving. Weather conditions during the data collection included clear, drizzle, rain and fog. Imagery was collected during the day, at night, and during dusk/dawn transition periods. The PMMW imager was a prototype which operated at 94 GHz and was based on a conically scanned folded Schmidt camera and the LWIR and visible sensors were commercial off the shelf items.

Assessing modern ground survey methods and airborne laser scanning for digital terrain modelling:A case study from the Lake District, England

This paper compares the applicability of three ground survey methods for modelling terrain: one man electronic tachymetry (TPS), real time kinematic GPS (GPS), and terrestrial laser scanning (TLS). Vertical accuracy of digital terrain models (DTMs) derived from GPS, TLS and airborne laser scanning (ALS) data is assessed. Point elevations acquired by the four methods represent two sections of a mountainous area in Cumbria, England. They were chosen so that the presence of non-terrain features is constrained to the smallest amount. The vertical accuracy of the DTMs was addressed by subtracting each DTM from TPS point elevations. The error was assessed using exploratory measures including statistics, histograms, and normal probability plots. The results showed that the internal measurement accuracy of TPS, GPS, and TLS was below a centimetre. TPS and GPS can be considered equally applicable alternatives for sampling the terrain in areas accessible on foot. The highest DTM vertical accuracy was achieved with GPS data, both on sloped terrain (RMSE 0.16. m) and flat terrain (RMSE 0.02. m). TLS surveying was the most efficient overall but veracity of terrain representation was subject to dense vegetation cover. Therefore, the DTM accuracy was the lowest for the sloped area with dense bracken (RMSE 0.52. m) although it was the second highest on the flat unobscured terrain (RMSE 0.07. m). ALS data represented the sloped terrain more realistically (RMSE 0.23. m) than the TLS. However, due to a systematic bias identified on the flat terrain the DTM accuracy was the lowest (RMSE 0.29. m) which was above the level stated by the data provider. Error distribution models were more closely approximated by normal distribution defined using median and normalized median absolute deviation which supports the use of the robust measures in DEM error modelling and its propagation. © 2012 Elsevier Ltd.

Foraging trip time-activity budgets and reproductive success in the black-legged kittiwake

Seabirds are central place foragers during the breeding season and, as marine food resources are often patchily distributed, flexibility in foraging behaviour may be important in maintaining prey delivery rates to chicks. We developed a methodological approach using a combination of GPS data loggers and temperature-depth recorders that allowed us to describe the behaviour of surface-feeding seabirds. Specifically, we tested whether differences in foraging behaviour of black-legged kittiwakes Rissa tridactyla could be linked with reproductive success by comparing 2 consecutive years at 2 sites. At Rathlin Island (Northern Ireland) during 2010, foraging differed markedly from that during 2009 and from that at Lambay Island (Republic of Ireland) during both years. Birds exhibited foraging trips of greater duration, travelled a greater total distance, spent more time in transit and spent longer recuperating on the surface of the water. This notable shift was associated with a decline in breeding success, with greater loss of eggs to predation and lower prey delivery rates, resulting in the starvation of 15 % of chicks. We suggest that food resources were reduced or geographically less accessible during 2010, with suitable foraging areas located further from the colony. Birds did not invest greater amounts of time attempting to catch prey. Thus, our results indicate that kittiwakes at Rathlin modulated their foraging behaviour not by increasing foraging effort through feeding more intensively within prey patches but by extending their range to increase the probability of encountering more profitable prey patches. © Inter-Research 2012.

Classifying pedestrian movement behaviour from GPS trajectories using visualization and clustering

The quantity and quality of spatial data are increasing rapidly. This is particularly evident in the case of movement data. Devices capable of accurately recording the position of moving entities have become ubiquitous and created an abundance of movement data. Valuable knowledge concerning processes occurring in the physical world can be extracted from these large movement data sets. Geovisual analytics offers powerful techniques to achieve this. This article describes a new geovisual analytics tool specifically designed for movement data. The tool features the classic space-time cube augmented with a novel clustering approach to identify common behaviour. These techniques were used to analyse pedestrian movement in a city environment which revealed the effectiveness of the tool for identifying spatiotemporal patterns. © 2014 Taylor & Francis.

Smartphone and GPS technology for freeroaming dog population surveillance -a methodological study (Studio metodologico sull’applicazione di smartphone e tecnologia GPS alla sorveglianza delle popolazioni di cani vaganti)

Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.