Combining GPS Data Research Articles

AIMS for wildlife: Developing an automated interactive monitoring system to integrate real-time movement and environmental data for true adaptive management

To effectively manage species and habitats at multiple scales, population and land managers require rapid information on wildlife use of managed areas and responses to landscape conditions and management actions. GPS tracking studies of wildlife are particularly informative to species ecology, habitat use, and conservation. Combining GPS data with administrative data and a diverse suite of remotely sensed, geo-referenced environmental (e.g., climatic) data, would more comprehensively inform how animals interact with and utilize habitats and ecosystems and our goal was to create a conceptual model for a system that would accomplish this – the ‘Automated Interactive Monitoring System (AIMS) for Wildlife’. Our objective for this study was to develop a Customized Wildlife Report (CWR) - the first AIMS for Wildlife deliverable product. CWRs collate and summarize our 8-year GPS tracking dataset of ∼11 million locations from 1338 individual (16 species) avifauna and make actionable, real-time data on animal movements and trends in a specific area of interest available to managers and stakeholders for rapid application in day-to-day management. The CWR exemplar presented in this paper was developed to address needs identified by habitat managers of Sacramento National Wildlife Refuge and illustrates the highly specific, information offered and how it contributes to assessing the efficacy of conservation actions while allowing for near real-time adaptive management. The report can be easily customized for any of the thousands of wildlife refuges or regional areas of interest in the United States, emphasizing the broad application of an animal movement data stream. Utilizing diverse, extensive telemetry data streams through scientific collaboration can aid managers and conservation stakeholders with short and long-term research and conservation planning and help address a cadre of issues from local-scale habitat management to improving the understanding of landscape level impacts like drought, wildfire, and climate change on wildlife populations.

COVID-19 contact tracking by group activity trajectory recovery over camera networks

Contact tracking plays an important role in the epidemiological investigation of COVID-19, which can effectively reduce the spread of the epidemic. As an excellent alternative method for contact tracking, mobile phone location-based methods are widely used for locating and tracking contacts. However, current inaccurate positioning algorithms that are widely used in contact tracking lead to the inaccurate follow-up of contacts. Aiming to achieve accurate contact tracking for the COVID-19 contact group, we extend the analysis of the GPS data to combine GPS data with video surveillance data and address a novel task named group activity trajectory recovery. Meanwhile, a new dataset called GATR-GPS is constructed to simulate a realistic scenario of COVID-19 contact tracking, and a coordinated optimization algorithm with a spatio-temporal constraint table is further proposed to realize efficient trajectory recovery of pedestrian trajectories. Extensive experiments on the novel collected dataset and commonly used two existing person re-identification datasets are performed, and the results evidently demonstrate that our method achieves competitive results compared to the state-of-the-art methods.

Strain Distribution Along the Qilian Fold-and-Thrust Belt Determined From GPS Velocity Decomposition and Cluster Analysis: Implications for Regional Tectonics and Deformation Kinematics

The Qilian fold-and-thrust belt (QFTB) offers an excellent example to demonstrate the strain transition from strike–slip shearing to oblique crustal shortening, which plays an important role in dissecting the stress propagation of Indian–Eurasian convergence from the plateau interior to the surrounding blocks. Various geological or numerical models have attempted to describe the regional tectonic characteristics of the QFTB. However, these models only interpret one or part of the deformation behaviors in the QFTB, and the strain distribution across and along the QFTB as well as its deformation kinematics remains to be determined. Therefore, in this work, we applied the method of velocity decomposition and cluster analysis using combined GPS data to determine the strain partition or accommodation in different parts of the QFTB as well as tectonic relationships with surrounding blocks, which will contribute to distinguishing which model is more suitable for delineating the present-day deformation kinematics of the QFTB. Our analysis indicates that the western part of the QFTB is dominated mainly by crustal shortening perpendicular to the trend of the QFTB, coupled with lateral extension along the trend of the QFTB, while the eastern part of the QFTB is characterized mainly by lateral extrusion owing to the impact of two large eastward-striking left-slip faults (East Kunlun fault and Haiyuan fault), which are accommodated by an obvious velocity gradient boundary belt centered on two diamond basins (Qinghaihu and Gonghe basins) associated with their boundary faults. The active tectonics of the QFTB are obviously divided into two distinct groups: one group is a pure shear–strain pattern, accounting for strong crustal shortening in the western part of the QFTB, and the other group is a simple shear–strain pattern, accounting for the obvious lateral extrusion in the eastern part of the QFTB.

Assessing the role of geographic context in transportation mode detection from GPS data

The increasing availability of health monitoring devices and smartphones has created an opportunity for researchers to access high-resolution (spatial and temporal) mobility data for understanding travel behavior in cities. Although information from GPS data has been used in several studies to detect transportation modes, there is a research gap in understanding the role of geographic context in transportation mode detection. Integrating the geography in which mobility occurs, provides context clues that may allow models predicting transportation modes to be more generalizable. Our goals are first, to develop a data-driven modeling framework for transportation mode detection using GPS mobility data along with geographic context, and second, to assess how model accuracy and generalizability varies upon adding geographic context. To this extent we extracted features from raw GPS mobility data (speed, altitude, turning angle and net displacement) and integrated context in the form of geographic features to classify active (i.e. walk/bike), public (i.e. bus/train), and private (i.e. car) transportation modes in three different Canadian cities - Montreal, St. Johns, and Vancouver. To assess the role of integrating geographic context in mode detection, we adopted two different modeling approaches – generalized and context-specific, and compared results using random forests, extreme gradient boost, and multilayer perceptron classifiers. Our results indicate that for context-specific models the highest classification accuracy improved by 64% for Montreal, by 74% for St. John's and by 77% for Vancouver compared to the generalized model. We also found that the multilayer perceptron (96%) achieved the highest classification accuracy upon adding contextual variables compared to random forests (94.6%) and extreme gradient boost (93.3%) classifier. Our study highlights that adding contextual information specific to a city's geography can improve the predictive accuracy of transportation mode detection models, however, in case of limited knowledge about the geographic setting of a study area, a generalized model combining GPS data from several cities may still be useful for predicting modes from trip data.

Analyzing the Performance of GPS Data for Earthquake Prediction

The results of earthquake prediction largely depend on the quality of data and the methods of their joint processing. At present, for a number of regions, it is possible, in addition to data from earthquake catalogs, to use space geodesy data obtained with the help of GPS. The purpose of our study is to evaluate the efficiency of using the time series of displacements of the Earth’s surface according to GPS data for the systematic prediction of earthquakes. The criterion of efficiency is the probability of successful prediction of an earthquake with a limited size of the alarm zone. We use a machine learning method, namely the method of the minimum area of alarm, to predict earthquakes with a magnitude greater than 6.0 and a hypocenter depth of up to 60 km, which occurred from 2016 to 2020 in Japan, and earthquakes with a magnitude greater than 5.5. and a hypocenter depth of up to 60 km, which happened from 2013 to 2020 in California. For each region, we compare the following results: random forecast of earthquakes, forecast obtained with the field of spatial density of earthquake epicenters, forecast obtained with spatio-temporal fields based on GPS data, based on seismological data, and based on combined GPS data and seismological data. The results confirm the effectiveness of using GPS data for the systematic prediction of earthquakes.

Staying at Home: Mobility Effects of COVID-19

We combine GPS data on changes in average distance traveled by individuals at the county level with COVID-19 case data and other demographic information to estimate how individual mobility is affected by local disease prevalence and restriction orders to stay-at-home. We find that a rise of local infection rate from 0% to 0.003% is associated with a reduction in mobility by 2.31%. An official stay-at-home restriction order corresponds to reducing mobility by 7.87%. Counties with larger shares of population over age 65, lower share of votes for the Republican Party in the 2016 Presidential Election, and higher population density are more responsive to disease prevalence and restriction orders.

Long seed dispersal distances by an inquisitive flightless rail (Gallirallus australis) are reduced by interaction with humans.

Human presence is becoming increasingly ubiquitous, but the influence this has on the seed dispersal services performed by frugivorous animals is largely unknown. The New Zealand weka (Gallirallus australis) is an inquisitive flightless rail that frequently congregates in areas of high human use. Weka are important seed dispersers, yet the seed dispersal services they provide are still poorly understood. We estimated seed dispersal distances of weka for two plant species (Prumnopitys ferruginea and Elaeocarpus dentatus) and tested how human interaction affected these dispersal distances. We estimated weka seed dispersal distances by combining GPS data from 39 weka over three sites with weka seed retention time data in a mechanistic model. The mean seed retention times were extremely long (38–125 h). Weka were highly effective dispersers, dispersing 93–96% of seeds away from parent canopies, and 1% of seeds over 1 km. However, we found evidence of a significant human impact on the seed dispersal distances of weka, with birds occupying areas of high human use performing 34.8–40.9% shorter distances than their more remote counterparts. This represents an example of cryptic function loss, where although weka are still present in the ecosystem, their seed dispersal services are impaired by human interaction.

Large-scale segregation of tourists and wild reindeer in three Norwegian national parks: Management implications

The challenge to harmonize nature-based tourism with species conservation is important both from an economic, cultural and ecological perspective. One approach for understanding this interaction is to compare the spatiotemporal overlap between tourism activities and the focal species’ space use, with the purpose to identify areas, periods, and conditions in which tourism exerts the highest negative impact. Here, we combine GPS data from 66 wild reindeer with on-site surveys of tourist (n = 13434 respondents at 66 locations) and trail use counters (n = 99 sites) in three Norwegian national parks. Our findings highlight a large-scale segregation during the summer season, as wild reindeer move to areas less prone to disturbance by humans. Based on these findings, we discuss a management model to segregate tourists from wild reindeer in space and/or time during summer with the goal of long-term sustainable coexistence.

Automation of Measuring Actual Productivity of Earthwork in Urban Area, a Case Study from Montreal

The construction of a new facility in an urban area, such as a downtown area, involves considerable earthwork excavation most of the time. Measuring the actual productivity of earthwork operations that involve heavy machinery can be a complex task for project managers. The complexity contributes to the impact of the many factors involved, the required accuracy, and the uncertainties associated with such operations. Traditionally, measuring actual productivity is carried out manually by measuring the actual quantities of the excavated earth. Measuring actual productivity manually is time-consuming and not necessarily accurate. The paper presents a case study project in Montreal to investigate the application of a developed methodology that is affordable for small to medium size contractors. It integrates the GPS and fuzzy set theory as an alternate effective methodology for measuring actual onsite productivity during the construction stage in an urban area. The developed methodology combines GPS data that are collected in near real time, fuzzy set theory (FST), and Google Earth. FST is used to define the variability and uncertainty which exists in the duration of the main activities of the earthwork (loading, traveling, dumping, and returning). Google Earth is used for graphical presentation and to store the collected GPS data of the moving hauling units. The productivity estimated by the developed methodology was compared with that provided by a simulation-based model, in which the collected GPS data are used to define the duration of earthmoving moving operations, and with that measured manually by contractor. The developed methodology proves that the utilization of GPS data and FST can yield a more accurate estimation of onsite actual productivity compared to that provided by simulation-based approaches, but in much a simpler way regarding the computation effort and time.

Revisiting Slow Slip Events Occurrence in Boso Peninsula, Japan, Combining GPS Data and Repeating Earthquakes Analysis

AbstractSlow slip events (SSEs) regularly occur near the Boso Peninsula, central Japan. Their time of recurrence has been decreasing from 6.4 to 2.2 years from 1996 to 2014. It is important to better constrain the slip history of this area, especially as models show that the recurrence intervals could become shorter prior to the occurrence of a large interplate earthquake nearby. We analyze the seismic waveforms of more than 2,900 events (M≥1.0) taking place in the Boso Peninsula, Japan, from 1 April 2004 to 4 November 2015, calculating the correlation and the coherence between each pair of events in order to define groups of repeating earthquakes. The cumulative number of repeating earthquakes suggests the existence of two slow slip events that have escaped detection so far. Small transient displacements observed in the time series of nearby GPS stations confirm these results. The detection scheme coupling repeating earthquakes and GPS analysis allow to detect small SSEs that were not seen before by classical methods. This work brings new information on the diversity of SSEs and demonstrates that the SSEs in Boso area present a more complex history than previously considered.

The role of landscape characteristics for forage maturation and nutritional benefits of migration in red deer

SummaryLarge herbivores gain nutritional benefits from following the sequential flush of newly emergent, high‐quality forage along environmental gradients in the landscape, termed green wave surfing. Which landscape characteristics underlie the environmental gradient causing the green wave and to what extent landscape characteristics alone explain individual variation in nutritional benefits remain unresolved questions. Here, we combine GPS data from 346 red deer (Cervus elaphus) from four partially migratory populations in Norway with the satellite‐derived normalized difference vegetation index (NDVI), an index of plant phenology. We quantify whether migratory deer had access to higher quality forage than resident deer, how landscape characteristics within summer home ranges affected nutritional benefits, and whether differences in landscape characteristics could explain differences in nutritional gain between migratory and resident deer. We found that migratory red deer gained access to higher quality forage than resident deer but that this difference persisted even after controlling for landscape characteristics within the summer home ranges. There was a positive effect of elevation on access to high‐quality forage, but only for migratory deer. We discuss how the landscape an ungulate inhabits may determine its responses to plant phenology and also highlight how individual behavior may influence nutritional gain beyond the effect of landscape.

Coupling bio-logging with nutritional geometry to reveal novel insights into the foraging behaviour of a plunge-diving marine predator

ABSTRACTIt is widely believed that predators maximise their energy intake while foraging and consume prey that are nutritionally similar. We combined GPS data loggers, miniaturised cameras, dietary sampling and nutritional geometry to examine the nutritional variability in the prey and selected diet, and foraging performance, of the masked booby (Sula dactylatra tasmani), a wild carnivore and marine top predator. Data loggers also revealed no significant differences between sexes in the foraging performance of chick-rearing adults. Females provided more food to their chicks than the males and, regardless of the nutritional variability of prey consumed, both sexes showed similar amounts of protein and lipid in their diets. Miniaturised cameras combined with nutritional analysis of prey provided, for the first time, fine-scale detail of the amounts of macronutrients consumed in each plunge dive and the overall foraging trip. Our methodology could be considered for future studies that aim to contribute to the general understanding of the behavioural and physiological mechanisms and ecological and evolutionary significance of animal foraging (e.g. energy expenditure budgets and prey selection for self- and offspring-feeding that could lead to sex-specific foraging strategies).

Analysing hiker movement patterns using GPS data: Implications for park management

In natural areas, park management organisations need to cater for economic, environmental, recreation and social demands and values. However, multifunctional land use also creates conflicts. Increased numbers of people using an area could exceed its ecological carrying capacity. The recreational quality of areas could be negatively impacted by conflicts in recreational behaviour. Therefore, park managers require spatio-temporal data on visitor flows, but there appears to be a shortage of suitable visitor data. If there are data available, these often do not deliver the information required by managers and there is little guidance on appropriate monitoring variables. This paper therefore combines user movement analysis with environmental and ecological factors for natural resource management. Through a case study we describe the entire working process from field data acquisition to usable park management information. GPS and itinerary data from 138 visitors to the Drents-Friese Wold National Park (the Netherlands) were collected to estimate visitor densities and distribution patterns within the park. Data acquisition is efficient in the working process, but careful error handling is a time consuming but necessary part of it. We introduce the definition of ‘hard’ and ‘soft’ errors to make spatial analysis more flexible. We show that walking speed, trip time and spatial distributions varied between park visitor groups. Classification and Regression Tree (CART) analysis showed that factors such as the presence of marked trails, distance to facilities but not land use (such as forest or arable land) explained visitor distributions. Patterns differ between respondent groups based on group size and composition, which is also true for itinerary variables such as walking speed and trip time. The combination of high resolution location data with itinerary information from respondents provides a good impression of the different walking preferences of different respondent groups. We conclude therefore that combining GPS data with itinerary information is a useful tool in profiling different natural park visitors. This is useful information for park managers in steering tourists and in catering for different visitor demands in natural parks.

Neighbourhood for Playing: Using GPS, GIS and Accelerometry to Delineate Areas within which Youth are Physically Active

Despite the documented importance of the neighbourhood environment on youth physical activity, little empirical research exists regarding the geographical boundaries of neighbourhoods within which youth are physically active around their homes. Studies and public policies often arbitrarily assume the extent of these boundaries, which vary from study to study. This paper combines GPS data, diaries and accelerometry to delineate empirically the local area and distance within which youth play in Erie County, New York. The study found that youth tend to be physically active within a quarter-mile radius around their homes and to focus on one section of the often assumed circled neighbourhood.

Spatio-temporal dynamics of a fish spawning aggregation and its fishery in the Gulf of California

We engaged in cooperative research with fishers and stakeholders to characterize the fine-scale, spatio-temporal characteristics of spawning behavior in an aggregating marine fish (Cynoscion othonopterus: Sciaenidae) and coincident activities of its commercial fishery in the Upper Gulf of California. Approximately 1.5–1.8 million fish are harvested annually from spawning aggregations of C. othonopterus during 21–25 days of fishing and within an area of 1,149 km2 of a biosphere reserve. Spawning and fishing are synchronized on a semi-lunar cycle, with peaks in both occurring 5 to 2 days before the new and full moon, and fishing intensity and catch are highest at the spawning grounds within a no-take reserve. Results of this study demonstrate the benefits of combining GPS data loggers, fisheries data, biological surveys, and cooperative research with fishers to produce spatio-temporally explicit information relevant to the science and management of fish spawning aggregations and the spatial planning of marine reserves.

The GPS ionospheric working group

The first GPS ionospheric working group workshop was held 10–11 November 2003 at the MIT Haystack observatory in Westford, MA. The purpose of this workshop was to foster an environment of collaboration on scientific projects, software development and long-range planning issues involving GPS. A prime motivation of this group is to integrate the use of GPS data more completely within the larger sphere of atmospheric research. For example, a primary goal is a closer coupling of GPS measurements with data from other atmospheric sensors, such as atmospheric imagers and the incoherent scatter radar observations. It is also desirable to make GPS data more accessible to atmospheric researchers. GPS is at the forefront of utilizing information from integrated ground-based atmospheric systems. By combining GPS data from the ground-based and space-based network of receivers, spatial and temporal changes in the global distribution of the total electron content (TEC) can be monitored, providing a new view of the large and meso-scale characteristics and dynamics of the plasmas of the extended ionosphere. GPS observations when processed this way are helping to increase the understanding of the driving forces between the coupled spheres of Earth’s upper atmosphere. The workshop drew participation from approximately 25 ionospheric researchers, including several from the international community. Topics discussed at the workshop included the development of new software receivers, the impact of ionospheric phenomena on operational systems, and GPS observations of ionospheric redistribution and implications for magnetospheric–ionospheric (MI) coupling. The format of this meeting was informal, and a workshop environment was adhered to. Workshop participants included representatives from MIT’s Haystack observatory, the Jet Propulsion Laboratory (JPL), Cornell University, Boston College, the University of Colorado, the Air Force Research Laboratory, the Naval Research Laboratory, and the University of Texas at Austin. International participants included representatives from the University of Calgary, the University of New Brunswick, the Institute for Research on Electromagnetics of the Italian National Research Council (IROE-CNR), the University of Bath, and the Technical University of Catalonia. The workshop began with each of the participants presenting a short summary of their current efforts. These efforts included numerous TEC and scintillation studies using GPS, studies of equatorial anomaly dynamics using multi-instruments, ionospheric storm modeling, ionospheric storm studies using GPS networks, ionospheric tomography, near-real time TEC map generation, ionospheric studies in support of WAAS, data assimilation, scintillation receiver development, Traveling Ionospheric Disturbances (TIDs) studies, data processing, software development, and the development of new receivers. Following the introductions, longer presentations were given. The first was given by Dr. Bruce Tsuratani of the JPL and he discussed the relationship of the ionosphere to interplanetary shock electric fields. He has been analyzing the 5–6 November 2001 interplanetary shock/electric field event using space-borne GPS receiver data and altimeter data from TOPEX/Poseidon. In particular he is interested in the magnetospheric convection electric fields and the convection of ionospheric plasmas by these electric fields. Much discussion ensued on the myriad of unusual effects. Dr. Brent Ledvina of Cornell University gave a brief presentation on Global Navigation Satellite System (GNSS) receivers, which include GPS and Galileo receivers. The Received: 16 March 2004 / Accepted: 26 March 2004 Published online: 14 July 2004 a Springer-Verlag 2004