Relevant bibliographies by topics / GPS location data

Academic literature on the topic 'GPS location data'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "GPS location data"

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Cochrane, Madaline, Donald Brown, and Ron Moen. "GPS Technology for Semi-Aquatic Turtle Research." Diversity 11, no. 3 (March 1, 2019): 34. http://dx.doi.org/10.3390/d11030034.

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Global positioning system (GPS) telemetry units are now small enough to be deployed on terrestrial and semi-aquatic turtles. Many of these GPS units use snapshot technology which collects raw satellite and timestamp data during brief periods of data recording to minimize size. We evaluated locations from snapshot GPS units in stationary tests and on wood turtles (Glyptemys insculpta) in northeastern Minnesota. Stationary GPS units were placed in wood turtle habitat to evaluate location accuracy, fix success rate, and directional bias. The GPS fix success rate and accuracy were reduced in closed canopy conditions and when the stationary GPS unit was placed under a log to simulate wood turtle hiding behavior. We removed GPS location outliers and used a moving average calculation to reduce mean location error in stationary tests from 27 m (SD = 38) to 10 m (SD = 8). We then deployed GPS units and temperature loggers on wood turtles and collected 122,657 GPS locations and 242,781 temperature readings from 26 turtles from May to September 2015 and 2016. Location outliers accounted for 12% of locations when the GPS receiver was on a turtle. We classified each wood turtle location based on the GPS location and by comparing temperature profiles from river, sun, and shaded locations to the temperature logger on the turtle. We estimated that wood turtles were on land 68% (SD = 12) of the time from May to September. The fix success rate for land locations was 38% (SD = 9), indicating that wood turtles often use habitats with obstructed views of the sky. Mean net daily movement was 55 m (SD = 192). Our results demonstrate that snapshot GPS units and temperature loggers provide fine-scale GPS data useful in describing spatial ecology and habitat use of semi-aquatic turtles.
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Peng, X., C. Wang, K. Liu, A. Quinones, S. Li, and J. Shan. "EXPLORATION OF MUNICIPAL MOBILITY USING SMARTPHONE GPS DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-4-2020 (August 3, 2020): 209–15. http://dx.doi.org/10.5194/isprs-annals-v-4-2020-209-2020.

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Abstract. Due to the advances in location-acquisition techniques, smartphone GPS location data has emerged with opportunity for research, development, innovation, and business. A variety of research has been developed to study human behaviour through exploring patterns from these data. In this paper, we use smartphone GPS location data to investigate municipal mobility. Kernel density estimation and emerging hot spot analysis are used to the GPS dataset to demonstrate GPS user (point) distribution across space and time. Flow maps are capable of tracking clustering behaviours and direction maps drawn upon the orientation of vectors can precisely identify location of the events. Case study with Indianapolis metropolitan area traffic rush hour verifies the effectiveness of these methods. Furthermore, we identify smartphone GPS data of vehicles and develop a concise and effective method for traffic volume estimation for county highway network. It is shown that the developed smartphone GPS data analytics is powerful for predicting reliable annual average daily traffic estimation. The study showcases the capability of GPS location data in identifying municipal mobility patterns for both citizens and vehicles.
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Kunisada, Yugo, and Chinthaka Premachandra. "High Precision Location Estimation in Mountainous Areas Using GPS." Sensors 22, no. 3 (February 2, 2022): 1149. http://dx.doi.org/10.3390/s22031149.

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Outdoor recreation has become popular in recent years, against the backdrop of the new coronavirus epidemic that started in 2020. Mountaineering, in particular, has become a popular pastime for many people as an easy way to experience nature. However, the number of mountaineering accidents is increasing, owing to the inadequate knowledge and equipment for beginners. In particular, the lack of map-reading skills and experience often leads to the selection of wrong trails. The smartphones used for precise location information obtain correction information from radio waves from a base station, and the accuracy of using only the GPS in mountainous areas without radio waves is questionable. In general, the GPS position correction methods in the literature for such situations include complex processing of the GPS radio waves. Some of these methods have been proposed with complex hardware and are difficult to implement with portable hardware. In this study, we develop and demonstrate a method for obtaining accurate location information using GPS without the error correction of radio waves, even in mountainous areas. The multipath is the reason for most of the GPS errors in the mountains. In the mountains, depending on the locations, the correct GPS location can also be received. In the proposed method, the correct GPS data are used to detect the incorrect GPS locations. We present an experimental method for estimating the interrelationship between the GPS longitude and latitude data. Additionally, we demonstrate the effectiveness of our method by showing that the experimental mountain location data presented in this paper are more accurate than the GPS data alone.
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Zandbergen, Paul A., and Sean J. Barbeau. "Positional Accuracy of Assisted GPS Data from High-Sensitivity GPS-enabled Mobile Phones." Journal of Navigation 64, no. 3 (June 7, 2011): 381–99. http://dx.doi.org/10.1017/s0373463311000051.

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Utilizing both Assisted GPS (A-GPS) techniques and new high-sensitivity embedded GPS hardware, mobile phones are now able to achieve positioning in harsh environments such as urban canyons and indoor locations where older embedded GPS chips could not. This paper presents an empirical analysis of the positional accuracy of location data gathered using a high-sensitivity GPS-enabled mobile phone. The performance of the mobile phone is compared to that of regular recreational grade GPS receivers. Availability of valid GPS position fixes on the mobile phones tested was consistently close to 100% both outdoors and indoors. During static outdoor testing, positions provided by the mobile phones revealed a median horizontal error of between 5·0 and 8·5 m, substantially larger than those for regular autonomous GPS units by a factor of 2 to 3. Horizontal errors during static indoor testing were larger compared to outdoors, but the difference in accuracy between mobile phones and regular GPS receivers was reduced. Despite the modest performance of A-GPS on mobile phones, testing under various conditions revealed that very large errors are not very common. The maximum horizontal error during outdoor testing never exceeded 30 metres and during indoor testing never exceeded 100 metres. Combined with the relatively consistent availability of valid GPS position fixes under varying conditions, the current study has confirmed the reliability of A-GPS on mobiles phones as a source of location information for a range of different LBS applications.
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Saeb, Sohrab, Emily G. Lattie, Stephen M. Schueller, Konrad P. Kording, and David C. Mohr. "The relationship between mobile phone location sensor data and depressive symptom severity." PeerJ 4 (September 29, 2016): e2537. http://dx.doi.org/10.7717/peerj.2537.

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BackgroundSmartphones offer the hope that depression can be detected using passively collected data from the phone sensors. The aim of this study was to replicate and extend previous work using geographic location (GPS) sensors to identify depressive symptom severity.MethodsWe used a dataset collected from 48 college students over a 10-week period, which included GPS phone sensor data and the Patient Health Questionnaire 9-item (PHQ-9) to evaluate depressive symptom severity at baseline and end-of-study. GPS features were calculated over the entire study, for weekdays and weekends, and in 2-week blocks.ResultsThe results of this study replicated our previous findings that a number of GPS features, including location variance, entropy, and circadian movement, were significantly correlated with PHQ-9 scores (r’s ranging from −0.43 to −0.46,p-values < .05). We also found that these relationships were stronger when GPS features were calculated from weekend, compared to weekday, data. Although the correlation between baseline PHQ-9 scores with 2-week GPS features diminished as we moved further from baseline, correlations with the end-of-study scores remained significant regardless of the time point used to calculate the features.DiscussionOur findings were consistent with past research demonstrating that GPS features may be an important and reliable predictor of depressive symptom severity. The varying strength of these relationships on weekends and weekdays suggests the role of weekend/weekday as a moderating variable. The finding that GPS features predict depressive symptom severity up to 10 weeks prior to assessment suggests that GPS features may have the potential as early warning signals of depression.
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Desai, Pooja, Parth Desai, Komal Ajmera, Khushbu Mehta, and Amit Deshmukh. "Data Logger and Accident Location using GSM and GPS." International Journal of Computer Applications 101, no. 8 (September 18, 2014): 37–40. http://dx.doi.org/10.5120/17711-8730.

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Laha, Arnab Kumar, and Sayan Putatunda. "Real time location prediction with taxi-GPS data streams." Transportation Research Part C: Emerging Technologies 92 (July 2018): 298–322. http://dx.doi.org/10.1016/j.trc.2018.05.005.

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Liang, Yi, Zhipeng Cai, Qilong Han, and Yingshu Li. "Location Privacy Leakage through Sensory Data." Security and Communication Networks 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/7576307.

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Mobile devices bring benefits as well as the risk of exposing users’ location information, as some embedded sensors can be accessed without users’ permission and awareness. In this paper, we show that, only by using the data collected from the embedded sensors in mobile devices instead of GPS data, we can infer a user’s location information with high accuracy. Three issues are addressed which are route identification, user localization in a specific route, and user localization in a bounded area. The Dynamic Time Warping based technique is designed and we develop a Hidden Markov Model to solve the localization problem. Real experiments are performed to evaluate our proposed methods.
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Gao, Guangyuan, and Mario Wüthrich. "Convolutional Neural Network Classification of Telematics Car Driving Data." Risks 7, no. 1 (January 10, 2019): 6. http://dx.doi.org/10.3390/risks7010006.

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The aim of this project is to analyze high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, deceleration, and changes of direction from this high-frequency GPS location data. Time series of this feature information allow us to appropriately allocate individual car driving trips to selected drivers using convolutional neural networks.
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Oliver, Melody, Hannah Badland, Suzanne Mavoa, Mitch J. Duncan, and Scott Duncan. "Combining GPS, GIS, and Accelerometry: Methodological Issues in the Assessment of Location and Intensity of Travel Behaviors." Journal of Physical Activity and Health 7, no. 1 (January 2010): 102–8. http://dx.doi.org/10.1123/jpah.7.1.102.

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Background:Global positioning systems (GPS), geographic information systems (GIS), and accelerometers are powerful tools to explain activity within a built environment, yet little integration of these tools has taken place. This study aimed to assess the feasibility of combining GPS, GIS, and accelerometry to understand transport-related physical activity (TPA) in adults.Methods:Forty adults wore an accelerometer and portable GPS unit over 7 consecutive days and completed a demographics questionnaire and 7-day travel log. Accelerometer and GPS data were extracted for commutes to/from workplace and integrated into a GIS database. GIS maps were generated to visually explore physical activity intensity, GPS speeds and routes traveled.Results:GPS, accelerometer, and survey data were collected for 37 participants. Loss of GPS data was substantial due to a range of methodological issues, such as low battery life, signal drop out, and participant noncompliance. Nonetheless, greater travel distances and significantly higher speeds were observed for motorized trips when compared with TPA.Conclusions:Pragmatic issues of using GPS monitoring to understand TPA behaviors and methodological recommendations for future research were identified. Although methodologically challenging, the combination of GPS monitoring, accelerometry and GIS technologies holds promise for understanding TPA within the built environment.
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Dissertations / Theses on the topic "GPS location data"

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Griffin, Terry W. "GPS CaPPture: a System for GPS Trajectory Collection, Processing, and Destination Prediction." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc115089/.

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In the United States, smartphone ownership surpassed 69.5 million in February 2011 with a large portion of those users (20%) downloading applications (apps) that enhance the usability of a device by adding additional functionality. a large percentage of apps are written specifically to utilize the geographical position of a mobile device. One of the prime factors in developing location prediction models is the use of historical data to train such a model. with larger sets of training data, prediction algorithms become more accurate; however, the use of historical data can quickly become a downfall if the GPS stream is not collected or processed correctly. Inaccurate or incomplete or even improperly interpreted historical data can lead to the inability to develop accurately performing prediction algorithms. As GPS chipsets become the standard in the ever increasing number of mobile devices, the opportunity for the collection of GPS data increases remarkably. the goal of this study is to build a comprehensive system that addresses the following challenges: (1) collection of GPS data streams in a manner such that the data is highly usable and has a reduction in errors; (2) processing and reduction of the collected data in order to prepare it and make it highly usable for the creation of prediction algorithms; (3) creation of prediction/labeling algorithms at such a level that they are viable for commercial use. This study identifies the key research problems toward building the CaPPture (collection, processing, prediction) system.
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Padmanabhan, Vijaybalaji. "Developing an operational procedure to produce digitized route maps using GPS vehicle location data." Thesis, Virginia Tech, 2000. http://hdl.handle.net/10919/32202.

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Advancements in Global Positioning System (GPS) technology now make GPS data collection for transportation studies and other transportation applications a reality. Base map for the application can be obtained by importing the road centerline map into GIS software like AutoCAD Map, or Arc/Info or MapixTM. However, such kinds of Road Centerline maps are not available for all places. Therefore, it may be necessary to collect the data using GPS units. This thesis details the use of GPS technology to produce route maps that can be used to predict arrival time of a bus. This application is particularly useful in rural areas, since the bus headway in a rural area is generally larger than that in an urban area. The information is normally communicated through various interfaces such as internet, cable TV, etc., based on the GPS bus location data. The objective of this thesis is to develop an operational procedure to obtain the digitized route map of any desired interval or link length and to examine the accuracy of the digitized map. The operational procedure involved data collection, data processing, algorithm development and coding to produce the digitized route maps. An algorithm was developed produce the digitized route map from the base map of the route, coded in MATLAB, and can be used to digitize the base map into any desired interval of distance. The accuracy comparison is made to determine the consistency between the digitized route map and the base map.
Master of Science
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Jeong, Ran Hee. "The prediction of bus arrival time using Automatic Vehicle Location Systems data." Texas A&M University, 2004. http://hdl.handle.net/1969.1/1458.

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Advanced Traveler Information System (ATIS) is one component of Intelligent Transportation Systems (ITS), and a major component of ATIS is travel time information. The provision of timely and accurate transit travel time information is important because it attracts additional ridership and increases the satisfaction of transit users. The cost of electronics and components for ITS has been decreased, and ITS deployment is growing nationwide. Automatic Vehicle Location (AVL) Systems, which is a part of ITS, have been adopted by many transit agencies. These allow them to track their transit vehicles in real-time. The need for the model or technique to predict transit travel time using AVL data is increasing. While some research on this topic has been conducted, it has been shown that more research on this topic is required. The objectives of this research were 1) to develop and apply a model to predict bus arrival time using AVL data, 2) to identify the prediction interval of bus arrival time and the probabilty of a bus being on time. In this research, the travel time prediction model explicitly included dwell times, schedule adherence by time period, and traffic congestion which were critical to predict accurate bus arrival times. The test bed was a bus route running in the downtown of Houston, Texas. A historical based model, regression models, and artificial neural network (ANN) models were developed to predict bus arrival time. It was found that the artificial neural network models performed considerably better than either historical data based models or multi linear regression models. It was hypothesized that the ANN was able to identify the complex non-linear relationship between travel time and the independent variables and this led to superior results. Because variability in travel time (both waiting and on-board) is extremely important for transit choices, it would also be useful to extend the model to provide not only estimates of travel time but also prediction intervals. With the ANN models, the prediction intervals of bus arrival time were calculated. Because the ANN models are non parametric models, conventional techniques for prediction intervals can not be used. Consequently, a newly developed computer-intensive method, the bootstrap technique was used to obtain prediction intervals of bus arrival time. On-time performance of a bus is very important to transit operators to provide quality service to transit passengers. To measure the on-time performance, the probability of a bus being on time is required. In addition to the prediction interval of bus arrival time, the probability that a given bus is on time was calculated. The probability density function of schedule adherence seemed to be the gamma distribution or the normal distribution. To determine which distribution is the best fit for the schedule adherence, a chi-squared goodness-of-fit test was used. In brief, the normal distribution estimates well the schedule adherence. With the normal distribution, the probability of a bus being on time, being ahead schedule, and being behind schedule can be estimated.
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Hennessey, Daniel R. "Buses as traffic probes empirical investigation using GPS-based location data on the OSU Campus Area Bus Service system /." Connect to resource, 2007. http://hdl.handle.net/1811/25080.

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Thesis (Honors)--Ohio State University, 2007.
Title from first page of PDF file. Document formatted into pages: contains x, 74 p.; also includes graphics. Includes bibliographical references (p. 58-59). Available online via Ohio State University's Knowledge Bank.
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Woywitka, Robin John. "Archaeological site location data implications for GIS /." online access from Digital Dissertation Consortium access full-text, 2002. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?MQ81330.

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Toledo, Moreo Rafael. "Un sistema de navegación de alta integridad para vehículos en entornos desfavorables." Doctoral thesis, Universidad de Murcia, 2006. http://hdl.handle.net/10803/10923.

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Algunas aplicaciones de carretera actuales, tales como los servicios de información al viajero, llamadas de emergencia automáticas, control de flotas o telepeaje eletrónico, requieren una solución de calidad al problema del posicionamiento de un vehículo terrestre, que funcione en cualquier entorno y a un coste razonable. Esta tesis presenta una solución a este problema, fusionando para ello la información procedente principalmente de sensores de navegación por satélite y sensores inerciales. Para ello emplea un nuevo filtro de fusion multisensorial IMM-EKF. El comportamiento del sistema ha sido analizado en entornos reales y controlados, y comparado con otras soluciones propuestas. Finalmente, su aplicabilidad al problema planteado ha sido verificada.
Road applications such as traveller information, automatic emergency calls, freight management or electronic fee, collection require a onboard equipment (OBE) capable to offer a high available accurate position, even in unfriendly environments with low satellite visibility at low cost. Specifically in life critical applications, users demand from the OBEs accurate continuous positioning and information of the reliability of this position. This thesis presents a solution based on the fusion of Global Navigation Satellite Systems (GNSS) and inertial sensors (GNSS/INS), running an Extended Kalman Filter combined with an Interactive Multi-Model method (IMM-EKF). The solution developed in this work supplies continuous positioning in marketable conditions, and a meaningful trust level of the given solution. A set of tests performed in controlled and real scenarios proves the suitability of the proposed IMM-EKF implementation, as compared with low cost GNSS based solutions, dead reckoning systems and single model extended Kalman filter (SM-EKF) solutions.
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Jurečka, Jan. "Analýza BI dat pomocí geografického systému." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-197063.

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The topic of the current Master's thesis is Business Intelligence's data presentation using maps. Through integrating BI and geographic information systems a new discipline is emerging - Location Intelligence. The main goal of this thesis is to highlight and analyse reporting possibilities of the BI tools in the framework of maps. The theoretical part of this paper is dedicated to the foundation and principles of geographic information systems and their intersection with BI, where such field as Location Intelligence is being created. In the practical part of the thesis the BI tools IBM Cognos and Oracle BI are compared. The comparison is based on the following criteria: field of implementation, visualization, map external sources and performance. The evaluating criteria are defined in the beginning of the practical part as well as the evaluation method. The methods of analysis and information collecting were used to extract and revise the knowledge from specific electronic and printed sources in Czech or English. Sources for the practical part origin from my technical knowledge of the field of BI, as well as practical experience with implementation of map sources as a feature of Business Intelligence. Statistical methods are used for evaluation of the criteria results. The practical and theoretical value of the thesis lies in creating the lucid comparison of implementation of the map sources into the selected BI tools and options for reporting or visualization of BI data over map. Apart from comparison the framework for implementation of maps into the selected BI tools is established in the above mentioned work.
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Almuzaini, Khalid. "Qualitative modelling of place location on the linked data web and GIS." Thesis, Cardiff University, 2017. http://orca.cf.ac.uk/106368/.

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When asked to define where a geographic place is, people normally resort to using qualitative expressions of location, such as north of and near to. This is evident in the domain of social geography, where qualitative research methods are used to gauge people’s understanding of their neighbourhood. Using a GIS to represent and map the location of neighbourhood boundaries is needed to understand and compare people’s perceptions of the spatial extent of their neighbourhoods. Extending the GIS to allow for the qualitative modelling of place will allow for the representation and mapping of neighbourhoods. On the other hand, a collaborative definition of place on the web will result in the accumulation of large sets of data resources that can be considered “location-poor”, where place location is defined mostly using single point coordinates and some random combinations of relative spatial relationships. A qualitative model of place location on the Linked Data Web (LDW) will allow for the homogenous representation and reasoning of place resources. This research has analysed the qualitative modelling of place location on the LDW and in GIS. On the LDW, a qualitative model of place is proposed, which provides an effective representation of individual place location profiles that allow place information to be enriched and spatially linked. This has been evaluated using the application of qualitative spatial reasoning (QSR) to automatic reasoning over place profiles, to check the completeness of the representation, as well as to derive implicit links not defined by the model. In GIS, a qualitative model of place is proposed that provides a basis for mapping qualitative definitions of place location in GIS, and this has been evaluated using an implementation-driven approach. The model has been implemented in a GIS and demonstrated through a realistic case study. A user-centric approach to development has been adopted, as users were involved throughout the design, development and evaluation stages.
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Jalali, Jalal. "Artificial neural networks for reservoir level detection of CO₂ seepage location using permanent down-hole pressure data." Morgantown, W. Va. : [West Virginia University Libraries], 2010. http://hdl.handle.net/10450/11137.

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Thesis (Ph. D.)--West Virginia University, 2010.
Title from document title page. Document formatted into pages; contains xii, 140 p. : ill. (some col.), col. maps. Includes abstract. Includes bibliographical references (p. 99-104).
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Zhou, Guoqing. "Co-Location Decision Tree for Enhancing Decision-Making of Pavement Maintenance and Rehabilitation." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/26059.

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A pavement management system (PMS) is a valuable tool and one of the critical elements of the highway transportation infrastructure. Since a vast amount of pavement data is frequently and continuously being collected, updated, and exchanged due to rapidly deteriorating road conditions, increased traffic loads, and shrinking funds, resulting in the rapid accumulation of a large pavement database, knowledge-based expert systems (KBESs) have therefore been developed to solve various transportation problems. This dissertation presents the development of theory and algorithm for a new decision tree induction method, called co-location-based decision tree (CL-DT.) This method will enhance the decision-making abilities of pavement maintenance personnel and their rehabilitation strategies. This idea stems from shortcomings in traditional decision tree induction algorithms, when applied in the pavement treatment strategies. The proposed algorithm utilizes the co-location (co-occurrence) characteristics of spatial attribute data in the pavement database. With the proposed algorithm, one distinct event occurrence can associate with two or multiple attribute values that occur simultaneously in spatial and temporal domains. This research dissertation describes the details of the proposed CL-DT algorithms and steps of realizing the proposed algorithm. First, the dissertation research describes the detailed colocation mining algorithm, including spatial attribute data selection in pavement databases, the determination of candidate co-locations, the determination of table instances of candidate colocations, pruning the non-prevalent co-locations, and induction of co-location rules. In this step, a hybrid constraint, i.e., spatial geometric distance constraint condition and a distinct event-type constraint condition, is developed. The spatial geometric distance constraint condition is a neighborhood relationship-based spatial joins of table instances for many prevalent co-locations with one prevalent co-location; and the distance event-type constraint condition is a Euclidean distance between a set of attributes and its corresponding clusters center of attributes. The dissertation research also developed the spatial feature pruning method using the multi-resolution pruning criterion. The cross-correlation criterion of spatial features is used to remove the nonprevalent co-locations from the candidate prevalent co-location set under a given threshold. The dissertation research focused on the development of the co-location decision tree (CL-DT) algorithm, which includes the non-spatial attribute data selection in the pavement management database, co-location algorithm modeling, node merging criteria, and co-location decision tree induction. In this step, co-location mining rules are used to guide the decision tree generation and induce decision rules. For each step, this dissertation gives detailed flowcharts, such as flowchart of co-location decision tree induction, co-location/co-occurrence decision tree algorithm, algorithm of colocation/co-occurrence decision tree (CL-DT), and outline of steps of SFS (Sequential Feature Selection) algorithm. Finally, this research used a pavement database covering four counties, which are provided by NCDOT (North Carolina Department of Transportation), to verify and test the proposed method. The comparison analyses of different rehabilitation treatments proposed by NCDOT, by the traditional DT induction algorithm and by the proposed new method are conducted. Findings and conclusions include: (1) traditional DT technology can make a consistent decision for road maintenance and rehabilitation strategy under the same road conditions, i.e., less interference from human factors; (2) the traditional DT technology can increase the speed of decision-making because the technology automatically generates a decision-tree and rules if the expert knowledge is given, which saves time and expenses for PMS; (3) integration of the DT and GIS can provide the PMS with the capabilities of graphically displaying treatment decisions, visualizing the attribute and non-attribute data, and linking data and information to the geographical coordinates. However, the traditional DT induction methods are not as quite intelligent as oneâ s expectations. Thus, post-processing and refinement is necessary. Moreover, traditional DT induction methods for pavement M&R strategies only used the non-spatial attribute data. It has been demonstrated from this dissertation research that the spatial data is very useful for the improvement of decision-making processes for pavement treatment strategies. In addition, the decision trees are based on the knowledge acquired from pavement management engineers for strategy selection. Thus, different decision-trees can be built if the requirement changes.
Ph. D.
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Books on the topic "GPS location data"

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Cai, Liang, Kathleen Cagney, Christopher Browning, Erin Cornwell, and Naomi Sugie. How to Analyze GPS/Location Data. 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529610079.

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Mark, Mehrer, and Wescott Konnie, eds. GIS and archaeological site location modeling. Boca Raton, FL: Taylor & Francis, 2005.

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InfoNetrix. North American Electric Utility GIS & Mobile Computing (GMC). New Orleans: InfoNetrix, 2002.

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Wilken, Rowan. Cultural Economies of Locative Media. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190234911.001.0001.

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Cultural Economies of Locative Media examines the manifold ways that location, location-awareness, and location data have all become familiar yet increasingly significant parts of our mobile-mediated experiences of everyday life. The book explores the complex of interrelationships that mutually define the new business models and economic factors that emerge around and structure locative media services, their diverse social uses and cultures of consumption, and their policy implications and impacts. It offers a detailed, in-depth account of how location-based services, such as GPS-enabled mobile smartphones and associated applications, are socially, culturally, economically, and politically produced and shaped, as much as technically designed and manufactured. The result is a rich, composite portrait of locative media in all its cultural economic complexity.
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(Editor), Mark W. Mehrer, and Konnie L. Wescott (Editor), eds. GIS and Archaeological Site Location Modeling. CRC, 2005.

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(Editor), Thomas Strang, and Claudia Linnhoff-Popien (Editor), eds. Location- and Context-Awareness: First International Workshop, LoCA 2005, Oberpfaffenhofen, Germany, May 12-13, 2005, Proceedings (Lecture Notes in Computer Science). Springer, 2005.

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H, Castle Gilbert, ed. Geographic Information Systems: GIS in real estate : integrating, analyzing, and presenting locational information. Chicago: Appraisal Institute, 1998.

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Romsom, Etienne, and Kathryn McPhail. Capturing economic and social value from hydrocarbon gas flaring and venting: solutions and actions. 6th ed. UNU-WIDER, 2021. http://dx.doi.org/10.35188/unu-wider/2021/940-2.

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This second paper on hydrocarbon gas flaring and venting builds on our first, which evaluated the economic and social cost (SCAR) of wasted natural gas. These emissions must be reduced urgently for natural gas to meet its potential as an energy-transition fuel under the Paris Agreement on Climate Change and to improve air quality and health. Wide-ranging initiatives and solutions exist already; the selection of the most suitable ones is situation-dependent. We present solutions and actions in a four-point (‘Diamond’) model involving: (1) measurement of chemicals emitted, (2) accountability and transparency of emissions through disclosure and reporting, (3) economic deployment of technologies for (small-scale) gas monetization, and (4) an ‘all-of-government’ approach to regulation and fiscal measures. Combining these actions in an integrated framework can end routine flaring and venting in many oil and gas developments. This is particularly important for low- and middle-income countries: satellite data since 2005 show that 85 per cent of total gas flared is in developing countries. Satellite data in 2017 identified location and amount of natural gas burned for 10,828 individual flares in 94 countries. Particular focus is needed to improve flare quality and capture natural gas from the 1 per cent ‘super-emitter’ flares responsible for 23 per cent of global natural gas flared.
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Wright, Dawn J., and Christian Harder, eds. GIS for Science, Volume 3: Maps for Saving the Planet. Esri Press, 2021. http://dx.doi.org/10.17128/9781589486713.

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GIS for Science: Maps for Saving the Planet, Volume 3, highlights real-world examples of scientists creating maps about saving life on Earth and preserving biodiversity. With Earth and the natural world at risk from various forces, geographic information system (GIS) mapping is essential for driving scientifically conscious decision-making about how to protect life on Earth. In volume 3 of GIS for Science, explore a collection of maps from scientists working to save the planet through documenting and protecting its biodiversity. In this volume, learn how GIS and data mapping are used in tandem with: global satellite observation forestry marine policy artificial intelligence conservation biology, and environmental education to help preserve and chronicle life on Earth. This volume also spotlights important global action initiatives incorporating conservation, including Half-Earth, 30 x 30, AI for Earth, the Blue Nature Alliance, and the Sustainable Development Solutions Network. The stories presented in this third volume are ideal for the professional scientist and conservationist and anyone interested in the intersection of technology and the conservation of nature. The book’s contributors include scientists who are applying geographic data gathered from the full spectrum of remote sensing and on-site technologies. The maps and data are brought to life using ArcGIS® software and other spatial data science tools that support research, collaboration, spatial analysis, and science communication across many locations and within diverse communities. The stories shared in this book and its companion website present inspirational ideas so that GIS users and scientists can work toward preserving biodiversity and saving planet Earth before time runs out.
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Books, Safi. Astronomy Observation: Log Book a Night Sky Journal and Tracker to Complement Your Telescope, Keep Record of Date, Time, Location, GPS, Observer, Sky ... Independently Published, 2021.

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Book chapters on the topic "GPS location data"

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Cooke, Tommy. "Smartphones, APIs & GNSS (Not GPS) Location Data." In Privacy, 78–106. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003173335-4.

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Liu, Huichuan, Yong Zeng, Jiale Liu, Zhihong Liu, Jianfeng Ma, and Xiaoyan Zhu. "Perosonalized Differentially Private Location Collection Method with Adaptive GPS Discretization." In Communications in Computer and Information Science, 175–90. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-33-4922-3_13.

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AbstractIn recent years, with the development of mobile terminals, geographic location has attracted the attention of many researchers because of its convenience in collection and its ability to reflect user profile. To protect user privacy, researchers have adopted local differential privacy in data collection process. However, most existing methods assume that location has already been discretized, which we found, if not done carefully, may introduces huge noise, lowering collected result utility. Thus in this paper, we design a differentially private location division module that could automatically discretize locations according to access density of each region. However, as the size of discretized regions may be large, if directly applying existing local differential privacy based attribute method, the overall utility of collected results may be completely destroyed. Thus, we further improve the optimized binary local hash method, based on personalized differential privacy, to collect user visit frequency of each discretized region. This solution improve the accuracy of the collected results while satisfying the privacy of the user’s geographic location. Through experiments on synthetic and real data sets, this paper proves that the proposed method achieves higher accuracy than the best known method under the same privacy budget.
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Pradhan, Sudip, Birendra Bajracharya, Kiran Shakya, and Bikram Shakya. "Geospatial Information Technology for Information Management and Dissemination." In Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region, 251–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73569-2_13.

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AbstractOver the last few decades, the development of geospatial technologies has converged with a variety of formal information technology disciplines (Zwartjes in Eur J Geogr 9(4):138–151, 2018; Jackson and Schell in Directions Magazine, 2009). The rapidly growing location-based services seamlessly integrate data and technologies from Earth observation (EO), Geographic Information System (GIS), Geographic Position System (GPS), and wireless and mobile communications (Huang et al. in J Location Based Servi 12(2):63–93, 2018).
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Thalmann, Tomas, and Amin Abdalla. "Assessing the Influence of Preprocessing Methods on Raw GPS-Data for Automated Change Point Detection." In Connecting a Digital Europe Through Location and Place, 123–39. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03611-3_8.

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Aboushelbaya, Ramy, Taimir Aguacil, Qiuting Huang, and Peter A. Norreys. "Efficient Location-Based Tracking for IoT Devices Using Compressive Sensing and Machine Learning Techniques." In High-Dimensional Optimization and Probability, 373–93. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-00832-0_12.

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AbstractIn this chapter, a scheme based on compressive sensing (CS) for the sparse reconstruction of down-sampled location data is presented for the first time. The underlying sparsity properties of the location data are explored and two algorithms based on LASSO regression and neural networks are shown to be able to efficiently reconstruct paths with only ∼20% sampling of the GPS receiver. An implementation for iOS devices is discussed and results from it are shown as proof of concept of the applicability of CS in location-based tracking for Internet of Things (IoT) devices.
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D’Angelo, Nicoletta, Mauro Ferrante, Antonino Abbruzzo, and Giada Adelfio. "Determinants of spatial intensity of stop locations on cruise passengers tracking data." In Proceedings e report, 159–64. Florence: Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.31.

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This paper aims at analyzing the spatial intensity in the distribution of stop locations of cruise passengers during their visit at the destination through a stochastic point process modelling approach on a linear network. Data collected through the integration of GPS tracking technology and questionnaire-based survey on cruise passengers visiting the city of Palermo are used, to identify the main determinants which characterize their stop locations pattern. The spatial intensity of stop locations is estimated through a Gibbs point process model, taking into account for both individual-related variables, contextual-level information, and for spatial interaction among stop points. The Berman-Turner device for maximum pseudolikelihood is considered, by using a quadrature scheme generated on the network. The approach used allows taking into account the linear network determined by the street configuration of the destination under analysis. The results show an influence of both socio-demographic and trip-related characteristics on the stop location patterns, as well as the relevance of distance from the main attractions, and potential interactions among cruise passengers in stop configuration. The proposed approach represents both improvements from the methodological perspective, related to the modelling of spatial point process on a linear network, and from the applied perspective, given that better knowledge of the determinants of spatial intensity of visitors’ stop locations in urban contexts may orient destination management policy.
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Xiong, Yan, Ze Luo, Baoping Yan, Diann J. Prosser, and John Y. Takekawa. "GPS Location History Data Mining and Anomalous Detection: The Scenario of Bar-Headed Geese Migration." In Lecture Notes in Electrical Engineering, 413–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34522-7_44.

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Xiong, Yan, Ze Luo, Baoping Yan, Diann J. Prosser, and John Y. Takekawa. "Erratum to: GPS Location History Data Mining and Anomalous Detection: The Scenario of Bar-Headed Geese Migration." In Lecture Notes in Electrical Engineering, E1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34522-7_106.

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Shekhar, Shashi, and Hui Xiong. "Locational Data Analysis." In Encyclopedia of GIS, 630. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_723.

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Kato, Haruka. "Development of a Spatio-Temporal Analysis Method to Support the Prevention of COVID-19 Infection: Space-Time Kernel Density Estimation Using GPS Location History Data." In Urban Informatics and Future Cities, 51–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76059-5_4.

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Conference papers on the topic "GPS location data"

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Xie, Yusheng, Yu Cheng, Ankit Agrawal, and Alok Choudhary. "Estimating Online User Location Distribution without GPS Location." In 2014 IEEE International Conference on Data Mining Workshop (ICDMW). IEEE, 2014. http://dx.doi.org/10.1109/icdmw.2014.30.

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Zheng, Yu, and Xing Xie. "Learning Location Correlation from GPS Trajectories." In 2010 Eleventh International Conference on Mobile Data Management. IEEE, 2010. http://dx.doi.org/10.1109/mdm.2010.42.

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Al Kukhun, Dana, Bouchra Soukkarieh, Erick Lopez-Ornelas, and Florence Sedes. "LA-GPS : A location-aware geographical pervasive system." In 2008 IEEE 24th International Conference on Data Engineeing workshop (ICDE Workshop 2008). IEEE, 2008. http://dx.doi.org/10.1109/icdew.2008.4498308.

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Jiang, Changhui, Shuai Chen, Yuwei Chen, Yuming Bo, Qingyuan Xia, and Boya Zhang. "Analysis of the baseline data based GPS spoofing detection algorithm." In 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS). IEEE, 2018. http://dx.doi.org/10.1109/plans.2018.8373406.

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Dourmashkin, Steven J., Nisar R. Ahmed, Dennis M. Akos, and William W. Whitacre. "GPS-limited cooperative localization using scalable approximate decentralized data fusion." In 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS). IEEE, 2018. http://dx.doi.org/10.1109/plans.2018.8373541.

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Alamleh, Hosam, and Ali Abdullah S. AlQahtani. "A Cheat-proof System To Validate GPS Location Data." In 2020 IEEE International Conference on Electro Information Technology (EIT). IEEE, 2020. http://dx.doi.org/10.1109/eit48999.2020.9208243.

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Zheng, Vincent W., Yu Zheng, Xing Xie, and Qiang Yang. "Collaborative location and activity recommendations with GPS history data." In the 19th international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1772690.1772795.

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Yaguang Xuan and Jin Xu. "GPS location data reducing based on turning point judgment method." In 2011 Second International Conference on Mechanic Automation and Control Engineering (MACE). IEEE, 2011. http://dx.doi.org/10.1109/mace.2011.5988759.

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Kuang, Da, Willy Bertiger, Shailen Desai, Bruce Haines, Byron Iijima, and Thomas Meehan. "Precise orbit determination for COSMIC satellites using GPS data from two on-board antennas." In 2008 IEEE/ION Position, Location and Navigation Symposium. IEEE, 2008. http://dx.doi.org/10.1109/plans.2008.4570030.

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Zhang, Yong, Donghuan Feng, Rui Zhang, and Nana Geng. "Multi-stage optimization of taxi service stations location using GPS data." In 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA). IEEE, 2017. http://dx.doi.org/10.1109/icbda.2017.8078832.

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Reports on the topic "GPS location data"

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Mathew, Jijo K., Christopher M. Day, Howell Li, and Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.

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Agencies use a variety of technologies and data providers to obtain travel time information. The best quality data can be obtained from second-by-second tracking of vehicles, but that data presents many challenges in terms of privacy, storage requirements and analysis. More frequently agencies collect or purchase segment travel time based upon some type of matching of vehicles between two spatially distributed points. Typical methods for that data collection involve license plate re-identification, Bluetooth, Wi-Fi, or some type of rolling DSRC identifier. One of the challenges in each of these sampling techniques is to employ filtering techniques to remove outliers associated with trip chaining, but not remove important features in the data associated with incidents or traffic congestion. This paper describes a curated data set that was developed from high-fidelity GPS trajectory data. The curated data contained 31,621 vehicle observations spanning 42 days; 2550 observations had travel times greater than 3 minutes more than normal. From this baseline data set, outliers were determined using GPS waypoints to determine if the vehicle left the route. Two performance measures were identified for evaluating three outlier-filtering algorithms by the proportion of true samples rejected and proportion of outliers correctly identified. The effectiveness of the three methods over 10-minute sampling windows was also evaluated. The curated data set has been archived in a digital repository and is available online for others to test outlier-filtering algorithms.
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Shamblin, Robert, Kevin Whelan, Mario Londono, and Judd Patterson. South Florida/Caribbean Network early detection protocol for exotic plants: Corridors of invasiveness. National Park Service, July 2022. http://dx.doi.org/10.36967/nrr-2293364.

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Exotic plant populations can be potentially catastrophic to the natural communities of South Florida. Aggressive exotics such as Brazillian Pepper (Schinus terebinthifolius) and Melaleuca (Melaleuca quinquinervia) have displaced native habitats and formed monocultures of exotic stands (Dalrymple et al. 2003). Nearby plant nurseries, especially the ones outside the boundaries of Biscayne National Park (BISC) and Everglades National Park (EVER), are a continuous source of new exotic species that may become established within South Florida’s national parks. Early detection and rapid response to these new species of exotic plants is important to maintaining the integrity of the parks’ natural habitats and is a cost-effective approach to management. The South Florida/Caribbean Network (SFCN) developed the South Florida/Caribbean Network Early Detection Protocol for Exotic Plants to target early detection of these potential invaders. Three national parks of South Florida are monitored for invasive, exotic plants using this protocol: Big Cypress National Preserve (BICY), Biscayne National Park (BISC), and Everglades National Park (EVER). These national parks include some 2,411,000 acres (3,767.2 square miles [mi2]) that encompass a variety of habitat types. To monitor the entire area for new species would not be feasible; therefore the basic approach of this protocol is to scan major “corridors of invasiveness,” e.g., paved and unpaved roads, trails, trail heads, off road vehicle (ORV) trails, boat ramps, canals, and campgrounds, for exotic plant species new to the national parks of South Florida. Sampling is optimized using a two- to three-person crew: a trained botanist, a certified herbicide applicator, and optionally a SFCN (or IPMT [Invasive Plant Management Team]) staff member or park staff to take photographs and help with data collection. If infestations are small, they are treated immediately by the herbicide applicator. If large, they are reported to park staff and the Invasive Plant Management Team. The sampling domain is partitioned into five regions, with one region sampled per year. Regions include the terrestrial habitats of Biscayne National Park, the eastern region of Everglades National Park, the western region of Everglades National Park, the northern region of Big Cypress National Preserve, and the southern region of Big Cypress National Preserve. Monitoring of roads, trails, and canals occurs while traveling into and through the parks (i.e., travel at 2–10 mph) using motorized vehicles, airboats, and/or hiking. Campgrounds, boat launches, trailheads, and similar areas, involve complete searches. When an exotic plant is observed, a GPS location is obtained, and coordinates are taken of the plant. Photographs are not taken for every exotic plant encountered, but photographs will be taken for new and unusual species (for example a coastal exotic found in inland habitats). Information recorded at each location includes the species name, size of infestation, abundance, cover class, any treatment/control action taken, and relevant notes. During the surveys, a GPS “track” is also recorded to document the areas surveyed and a field of view is estimated. Field notes, pictures, and GPS data are compiled, entered, and analyzed in a Microsoft Access database. Resource briefs (and optional data summary reports) and associated shapefiles and data are then produced and sent to contacts within the corresponding national parks.
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Goyeneche, Laura, Cynthia Boruchowicz, Florencia Lopez Boo, Luis Tejerina, Benjamin Roseth, and Jennifer Nelson. Pandemics, privacy, and adoption of technology: Perceptions of the use of digital tools and data sharing during COVID-19 from 10 Latin American countries. Inter-American Development Bank, December 2022. http://dx.doi.org/10.18235/0004546.

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This study describes the perception, adoption, and acceptance factors involved in the deployment of digital technologies for public health in Latin America and considers the implications for future digital health interventions. We conducted a descriptive analysis using nationally representative data from a phone survey conducted in 2020 in 10 countries in Latin America. We found that early in the pandemic, in countries with existing applications, 74% of the population used a smartphone, 47% had knowledge of the government app to report symptoms, but only 2% reported using it. Those interviewed reported that they are willing to share their personal data during a pandemic (61%) 50 percentage points higher than in non-pandemic times, although understanding how their personal data was used by the government and private companies was extremely low. More than 70% reported that they would use an application to report symptoms and would use an app that accesses their location or that uses contact tracing technology to alert them about possible exposure. Also, at least half of the users agree with preventive measures against COVID-19 such as daily follow-up calls, tracking via GPS for quarantine enforcement, and daily visits. In all countries, adoption of digital technologies increases if individuals or their relatives report they are infected; it decreases when end-users do not trust the anonymity policies or are concerned about government surveillance. Yet, encouraging greater adoption of digital technologies strongly depends on who designed the technology. Results show that 73% of users would prefer an app designed by an international organization such as the WHO to an app designed by the local government (64%) or a telephone company (56%). The study concludes with a reflection on the promising results of digital technologies and discusses the importance of considering users perceptions, factors for acceptance, and trust when pursuing adoption of digital technologies.
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Cheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li, and Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.

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This research considers the detection, location, and classification of patches in concrete and asphalt-on-concrete pavements using data taken from ground penetrating radar (GPR) and the WayLink 3D Imaging System. In particular, the project seeks to develop a patching table for “inverted-T” patches. A number of deep neural net methods were investigated for patch detection from 3D elevation and image observation, but the success was inconclusive, partly because of a dearth of training data. Later, a method based on thresholding IRI values computed on a 12-foot window was used to localize pavement distress, particularly as seen by patch settling. This method was far more promising. In addition, algorithms were developed for segmentation of the GPR data and for classification of the ambient pavement and the locations and types of patches found in it. The results so far are promising but far from perfect, with a relatively high rate of false alarms. The two project parts were combined to produce a fused patching table. Several hundred miles of data was captured with the Waylink System to compare with a much more limited GPR dataset. The primary dataset was captured on I-74. A software application for MATLAB has been written to aid in automation of patch table creation.
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Cheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li, and Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.

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This research considers the detection, location, and classification of patches in concrete and asphalt-on-concrete pavements using data taken from ground penetrating radar (GPR) and the WayLink 3D Imaging System. In particular, the project seeks to develop a patching table for “inverted-T” patches. A number of deep neural net methods were investigated for patch detection from 3D elevation and image observation, but the success was inconclusive, partly because of a dearth of training data. Later, a method based on thresholding IRI values computed on a 12-foot window was used to localize pavement distress, particularly as seen by patch settling. This method was far more promising. In addition, algorithms were developed for segmentation of the GPR data and for classification of the ambient pavement and the locations and types of patches found in it. The results so far are promising but far from perfect, with a relatively high rate of false alarms. The two project parts were combined to produce a fused patching table. Several hundred miles of data was captured with the Waylink System to compare with a much more limited GPR dataset. The primary dataset was captured on I-74. A software application for MATLAB has been written to aid in automation of patch table creation.
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Lever, James, Allan Delaney, Laura Ray, E. Trautman, Lynette Barna, and Amy Burzynski. Autonomous GPR surveys using the polar rover Yeti. Engineer Research and Development Center (U.S.), March 2022. http://dx.doi.org/10.21079/11681/43600.

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The National Science Foundation operates stations on the ice sheets of Antarctica and Greenland to investigate Earth’s climate history, life in extreme environments, and the evolution of the cosmos. Understandably, logistics costs predominate budgets due to the remote locations and harsh environments involved. Currently, manual ground-penetrating radar (GPR) surveys must preceed vehicle travel across polar ice sheets to detect subsurface crevasses or other voids. This exposes the crew to the risks of undetected hazards. We have developed an autonomous rover, Yeti, specifically to conduct GPR surveys across polar ice sheets. It is a simple four-wheel-drive, battery-powered vehicle that executes autonomous surveys via GPS waypoint following. We describe here three recent Yeti deployments, two in Antarctica and one in Greenland. Our key objective was to demonstrate the operational value of a rover to locate subsurface hazards. Yeti operated reliably at −30 ◦C, and it has good oversnow mobility and adequate GPS accuracy for waypoint-following and hazard georeferencing. It has acquired data on hundreds of crevasse encounters to improve our understanding of heavily crevassed traverse routes and to develop automated crevasse-detection algorithms. Importantly, it helped to locate a previously undetected buried building at the South Pole. Yeti can improve safety by decoupling survey personnel from the consequences of undetected hazards. It also enables higher-quality systematic surveys to improve hazard-detection probabilities, increase assessment confidence, and build datasets to understand the evolution of these regions. Yeti has demonstrated that autonomous vehicles have great potential to improve the safety and efficiency of polar logistics.
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Aguilar, G., H. Waqa-Sakiti, and L. Winder. Using Predicted Locations and an Ensemble Approach to Address Sparse Data Sets for Species Distribution Modelling: Long-horned Beetles (Cerambycidae) of the Fiji Islands. Unitec ePress, December 2016. http://dx.doi.org/10.34074/book.008.

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In response to unique species in Fiji which are threatened or endangered, and in critical need of effective conservation measures to ensure their survival, author Glenn Aguilar has produced an eMedia publication and learning research tool, called GIS For Conservation.The eMedia website hosts tutorial material, videos and modelling results for conservation management and planning purposes. Users will learn spatial analytical skills, species distribution modelling and other relevant GIS tools, as well as enhance ArcMap skills and the species distribution modelling tool Maxent. Accompanying the GIS For Conservation website is a peer-reviewed research report. The report details the case study and research methods that have informed the eMedia publication, focusing on the development of maps predicting the suitability of the Fiji Islands for longhorned beetles (Cerambycidae) that include endemic and endangered species such as the Giant Fijian Beetle Xixuthrus heros.
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Weinschenk, Craig, and Jack Regan. Analysis of Search and Rescue Tactics in Single-Story Single-Family Homes Part II: Kitchen and Living Room Fires. UL's Fire Safety Research Institute, May 2022. http://dx.doi.org/10.54206/102376/zkxw6893.

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Prior full-scale fire service research on the residential fireground has focused the impact of ventilation and suppression tactics on fire dynamics. This study builds upon prior research by conducting 10 experiments a purpose-built single-story, single-family residential structure to quantify the im- pact of how search and rescue tactics are coupled with ventilation and suppression actions and timing. Each fully furnished structure included four bedrooms, 2 bathrooms and an open-floor kitchen and living room. The structures were instrumented to quantify post-ignition toxic gas and thermal conditions. Temperature, velocity, and pressure were measured to evaluate the fire dynamics. Gas concentrations and heat fluxes were measured to quantify toxic and thermal exposures. Across this series of experiments, the impact of isolation of fire and non-fire compartments, the timing of search actions relative to suppression actions, and the influence of isolation, elevation, and path of travel during rescue were examined with respect to firefighter safety and occupant tenability. Similar to previous experiments in both purpose-built and acquired structure, the data showed that prior intervention locations lower in elevation and/or behind closed doors had lower toxic gas and thermal exposures compared to locations at higher elevations or locations that were not isolated. Lower elevations were also shown to have lower toxic gas and thermal exposures during the removal of occupants as part of rescue operations. For scenarios where search operations occurred prior to suppression, isolation of spaces from flow paths connected to the fire compartment was shown to be effective at reducing the thermal operating class for firefighters and the toxic and thermal exposure rates compared to spaces that were not isolated. Following isolation, exterior ventilation was found to further reduce the toxic gas and thermal exposures in the protected space. Suppression, from either interior and exterior positions, was effective at reducing the thermal operating class for searching firefighters and the rate of thermal exposure increase to occupants. Following suppression, additional exterior ventilation increased the rate at which gas concentrations returned to pre-ignition levels.
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Weinschenk, Craig. Analysis of Search and Rescue Tactics in Single-Story Single-Family Homes Part I: Bedroom Fires. UL's Fire Safety Research Institute, May 2022. http://dx.doi.org/10.54206/102376/dptn2682.

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Prior full-scale fire service research on the residential fireground has focused the impact of ventilation and suppression tactics on fire dynamics. This study builds upon prior research by conducting 11 experiments a purpose-built single-story, single-family residential structure to quantify the im- pact of how search and rescue tactics are coupled with ventilation and suppression actions and timing. Each fully furnished structure included four bedrooms, 2 bathrooms and an open-floor kitchen and living room. The structures were instrumented to quantify post-ignition toxic gas and thermal conditions. Temperature, velocity, and pressure were measured to evaluate the fire dynamics. Gas concentrations and heat fluxes were measured to quantify toxic and thermal exposures. Across this series of experiments, the impact of isolation of fire and non-fire compartments, the timing of search actions relative to suppression actions, and the influence of isolation, elevation, and path of travel during rescue were examined with respect to firefighter safety and occupant tenability. Similar to previous experiments in both purpose-built and acquired structure, the data showed that prior intervention locations lower in elevation and/or behind closed doors had lower toxic gas and thermal exposures compared to locations at higher elevations or locations that were not isolated. Lower elevations were also shown to have lower toxic gas and thermal exposures during the removal of occupants as part of rescue operations. For scenarios where search operations occurred prior to suppression, isolation of spaces from flow paths connected to the fire compartment was shown to be effective at reducing the thermal operating class for firefighters and the toxic and thermal exposure rates compared to spaces that were not isolated. Following isolation, exterior ventilation was found to further reduce the toxic gas and thermal exposures in the protected space. Suppression, from either interior and exterior positions, was effective at reducing the thermal operating class for searching firefighters and the rate of thermal exposure increase to occupants. Following suppression, additional exterior ventilation increased the rate at which gas concentrations returned to pre-ignition levels.
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Callaghan, Caitlin, Matthew Bigl, Brandon Booker, Kyle Elliott, Paulina Lintsai, Marissa Torres, Kathryn Trubac, and Jacqueline Willan. Energy Atlas—mapping energy-related data for DoD lands in Alaska : Phase 1—assembling the data and designing the tool. Engineer Research and Development Center (U.S.), October 2021. http://dx.doi.org/10.21079/11681/42226.

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The U.S. Army is the largest Department of Defense (DoD) land user in Alaska, including remote areas only accessible by air, water, or wintertime ice roads. Understanding where energy resources and related infrastructure exist on and adjacent to DoD installations and training lands can help in-form Army decision-makers, especially in remote locations like Alaska. The Energy Atlas–Alaska provides a value-added resource to support decision-making for investments in infrastructure and diligent energy management, helping Army installations become more resilient and sustainable. The Energy Atlas–Alaska utilizes spatial information and provides a consistent GIS (geographic information system) framework to access and examine energy and related resource data such as energy resource potential, energy corridors, and environmental information. The database can be made accessible to DoD and its partners through an ArcGIS-based user interface that provides effective visualization and functionality to support analysis and to inform DoD decision-makers. The Energy Atlas–Alaska helps DoD account for energy in contingency planning, acquisition, and life-cycle requirements and ensures facilities can maintain operations in the face of disruption.
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