scholarly journals Estimating velocity from noisy GPS data for investigating the temporal variability of slope movements

2014 ◽  
Vol 14 (9) ◽  
pp. 2503-2520 ◽  
Author(s):  
V. Wirz ◽  
J. Beutel ◽  
S. Gruber ◽  
S. Gubler ◽  
R. S. Purves
Keyword(s):  
Global Positioning System ◽  
Temporal Variability ◽  
Synthetic Data ◽  
Gps Data ◽  
Positioning System ◽  
Signal To Noise ◽  
Slope Movements ◽  
Global Positioning ◽  
System Data ◽  
Full Knowledge

Abstract. Detecting and monitoring of moving and potentially hazardous slopes requires reliable estimations of velocities. Separating any movement signal from measurement noise is crucial for understanding the temporal variability of slope movements and detecting changes in the movement regime, which may be important indicators of the process. Thus, methods capable of estimating velocity and its changes reliably are required. In this paper we develop and test a method for deriving velocities based on noisy GPS (Global Positioning System) data, suitable for various movement patterns and variable signal-to-noise-ratios (SNR). We tested this method on synthetic data, designed to mimic the characteristics of diverse processes, but where we have full knowledge of the underlying velocity patterns, before applying it to explore data collected.

Subsidence is determined in the heart of the Central Valley using Post Processed Static and Precise Point Positioning techniques

2020 ◽  
Vol 14 (1) ◽  
pp. 113-118 ◽  
Author(s):  
Y. Facio ◽  
M. Berber
Keyword(s):  
Data Processing ◽  
Global Positioning System ◽  
Precise Point Positioning ◽  
Central Valley ◽  
Gps Data ◽  
Positioning System ◽  
Online Services ◽  
Global Positioning ◽  
System Data ◽  
Point Positioning

AbstractPost Processed Static (PPS) and Precise Point Positioning (PPP) techniques are not new; however, they have been refined over the decades. As such, today these techniques are offered online via GPS (Global Positioning System) data processing services. In this study, one Post Processed Static (OPUS) and one Precise Point Positioning (CSRS-PPP) technique is used to process 24 h GPS data for a CORS (Continuously Operating Reference Stations) station (P565) duration of year 2016. By analyzing the results sent by these two online services, subsidence is determined for the location of CORS station, P565, as 3–4 cm for the entire year of 2016. In addition, precision of these two techniques is determined as ∼2 cm. Accuracy of PPS and PPP results is 0.46 cm and 1.21 cm, respectively. Additionally, these two techniques are compared and variations between them is determined as 2.5 cm.

Car-Following and Collision Constraint Models for Uninterrupted Traffic: Reexamination Using High-Precision Global Positioning System Data

2000 ◽  
Vol 1710 (1) ◽  
pp. 37-46 ◽  
Author(s):  
Sarosh Khan ◽  
Pawan Maini ◽  
Kittichai Thanasupsin
Keyword(s):  
High Precision ◽  
Global Positioning System ◽  
Critical Evaluation ◽  
Gps Data ◽  
Positioning System ◽  
Velocity Data ◽  
Car Following ◽  
Location Data ◽  
Global Positioning ◽  
System Data

In the last few decades several car-following models have been proposed and tested using mainly vehicle location data. The use of high-precision Global Positioning System (GPS) data to test several car-following and collision constraint models is reported, with a critical evaluation of these models and proposal of a modified collision constraint formulation. GPS receivers typically report time-stamped location or position fixes and velocity. For a pair of leading and following vehicles, location and velocity data were used to examine estimates of acceleration, velocity, and headway by Pipes’s; modified Pitt’s, or FRESIM; CARSIM; and INTELSIM car-following models. The important aspects of collecting accurate GPS data are also highlighted.

scholarly journals Parking Places to Moped-Style Scooter Sharing Services Using GIS Location-Allocation Models and GPS Data

2021 ◽  
Vol 10 (4) ◽  
pp. 230
Author(s):  
Onel Pérez-Fernández ◽  
Juan Carlos García-Palomares
Keyword(s):  
Global Positioning System ◽  
Catchment Area ◽  
Public Spaces ◽  
Gps Data ◽  
Positioning System ◽  
Urban Centers ◽  
Location Allocation ◽  
Global Positioning ◽  
The City

Moped-style scooters are one of the most popular systems of micro-mobility. They are undoubtedly good for the city, as they promote forms of environmentally-friendly mobility, in which flexibility helps prevent traffic build-up in the urban centers where they operate. However, their increasing numbers are also generating conflicts as a result of the bad behavior of users, their unwarranted use in public spaces, and above all their parking. This paper proposes a methodology for finding parking spaces for shared motorcycle services using Geographic information system (GIS) location-allocation models and Global Positioning System (GPS) data. We used the center of Madrid and data from the company Muving (one of the city’s main operators) for our case study. As well as finding the location of parking spaces for motorbikes, our analysis examines how the varying distribution of demand over the course of the day affects the demand allocated to parking spaces. The results demonstrate how reserving a relatively small number of parking spaces for scooters makes it possible to capture over 70% of journeys in the catchment area. The daily variations in the distribution of demand slightly reduce the efficiency of the network of parking spaces in the morning and increase it at night, when demand is strongly focused on the most central areas.

scholarly journals Development of Time-location Weighted Spatial Measures Using Global Positioning System Data

2013 ◽  
Vol 28 ◽  
pp. e2013005 ◽  
Author(s):  
Daikwon Han ◽  
Kiyoung Lee ◽  
Jongyun Kim ◽  
Deborah H. Bennett ◽  
Diana Cassady ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Global Positioning ◽  
Spatial Measures ◽  
System Data

scholarly journals Concurrent Measurement of Global Positioning System and Event-Based Physical Activity Data: A Methodological Framework for Integration

2020 ◽  
pp. 1-14
Author(s):  
Anna M.J. Iveson ◽  
Malcolm H. Granat ◽  
Brian M. Ellis ◽  
Philippa M. Dall
Keyword(s):  
Physical Activity ◽  
Outcome Measures ◽  
Global Positioning System ◽  
Gps Data ◽  
Positioning System ◽  
Activity Data ◽  
Data Set ◽  
Physical Activity Data ◽  
Global Positioning ◽  
Event Based

Objective: Global positioning system (GPS) data can add context to physical activity data and have previously been integrated with epoch-based physical activity data. The current study aimed to develop a framework for integrating GPS data and event-based physical activity data (suitable for assessing patterns of behavior). Methods: A convenience data set of concurrent GPS (AMOD) and physical activity (activPAL) data were collected from 69 adults. The GPS data were (semi)regularly sampled every 5 s. The physical activity data output was presented as walking events, which are continuous periods of walking with a time-stamped start time and duration (to nearest 0.1 s). The GPS outcome measures and the potential correspondence of their timing with walking events were identified and a framework was developed describing data integration for each combination of GPS outcome and walking event correspondence. Results: The GPS outcome measures were categorized as those deriving from a single GPS point (e.g., location) or from the difference between successive GPS points (e.g., distance), and could be categorical, scale, or rate outcomes. Walking events were categorized as having zero (13% of walking events, 3% of walking duration), or one or more (52% of walking events, 75% of walking duration) GPS points occurring during the event. Additionally, some walking events did not have GPS points suitably close to allow calculation of outcome measures (31% of walking events, 22% of walking duration). The framework required different integration approaches for each GPS outcome type, and walking events containing zero or more than one GPS points.

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