Modeling Taxi Customer Searching Behavior Using High-Resolution GPS Data

2020 ◽  
Author(s):  
Zhen Guo ◽  
Mengyan Hao ◽  
Bin Yu
Keyword(s):  
High Resolution ◽  
Gps Data ◽  
Searching Behavior

scholarly journals Supra-glacial debris cover changes in the Greater Caucasus from 1986 to 2014

2020 ◽  
Vol 14 (2) ◽  
pp. 585-598 ◽  
Author(s):  
Levan G. Tielidze ◽  
Tobias Bolch ◽  
Roger D. Wheate ◽  
Stanislav S. Kutuzov ◽  
Ivan I. Lavrentiev ◽  
...  
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Google Earth ◽  
Gps Data ◽  
Glacier Area ◽  
Greater Caucasus ◽  
Abstract Knowledge ◽  
Covered Area ◽  
Debris Cover ◽  
Automated Methods

Abstract. Knowledge of supra-glacial debris cover and its changes remain incomplete in the Greater Caucasus, in spite of recent glacier studies. Here we present data of supra-glacial debris cover for 659 glaciers across the Greater Caucasus based on Landsat and SPOT images from the years 1986, 2000 and 2014. We combined semi-automated methods for mapping the clean ice with manual digitization of debris-covered glacier parts and calculated supra-glacial debris-covered area as the residual between these two maps. The accuracy of the results was assessed by using high-resolution Google Earth imagery and GPS data for selected glaciers. From 1986 to 2014, the total glacier area decreased from 691.5±29.0 to 590.0±25.8 km2 (15.8±4.1 %, or ∼0.52 % yr−1), while the clean-ice area reduced from 643.2±25.9 to 511.0±20.9 km2 (20.1±4.0 %, or ∼0.73 % yr−1). In contrast supra-glacial debris cover increased from 7.0±6.4 %, or 48.3±3.1 km2, in 1986 to 13.4±6.2 % (∼0.22 % yr−1), or 79.0±4.9 km2, in 2014. Debris-free glaciers exhibited higher area and length reductions than debris-covered glaciers. The distribution of the supra-glacial debris cover differs between the northern and southern and between the western, central and eastern Greater Caucasus. The observed increase in supra-glacial debris cover is significantly stronger on the northern slopes. Overall, we have observed up-glacier average migration of supra-glacial debris cover from about 3015 to 3130 m a.s.l. (metres above sea level) during the investigated period.

Mt. Etna volcano high-resolution topography: airborne LiDAR modelling validated by GPS data

2016 ◽  
Vol 9 (7) ◽  
pp. 710-732 ◽  
Author(s):  
Marina Bisson ◽  
Claudia Spinetti ◽  
Marco Neri ◽  
Alessandro Bonforte
Keyword(s):  
High Resolution ◽  
Airborne Lidar ◽  
Gps Data ◽  
Etna Volcano ◽  
Mt Etna

scholarly journals Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

2017 ◽  
Vol 2645 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Lei Zhu ◽  
Jacob R. Holden ◽  
Jeffrey D. Gonder
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Longest Common Subsequence ◽  
Gps Data ◽  
Map Matching ◽  
Trajectory Data ◽  
Data Set ◽  
Matching Algorithm ◽  
Gps Trajectory ◽  
Trajectory Segmentation

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similarity score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.

scholarly journals Coastal Wetland Shoreline Change Monitoring: A Comparison of Shorelines from High-Resolution WorldView Satellite Imagery, Aerial Imagery, and Field Surveys

2021 ◽  
Vol 13 (15) ◽  
pp. 3030
Author(s):  
Kathryn E. L. Smith ◽  
Joseph F. Terrano ◽  
Jonathan L. Pitchford ◽  
Michael J. Archer
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Coastal Wetland ◽  
Shoreline Change ◽  
Gps Data ◽  
Change Analysis ◽  
High Resolution Satellite Imagery ◽  
Vulnerable Habitats ◽  
High Wave Energy ◽  
Change Monitoring

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into shoreline monitoring. Geospatial shoreline data created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020 were compared to contemporaneous field-surveyed Global Position System (GPS) data. WV-derived shorelines were found to have a mean difference of 2 ± 0.08 m of GPS data, but accuracy decreased at high-wave energy shorelines that were unvegetated, bordered by sandy beach or semi-submergent sand bars. Shoreline change rates calculated from WV imagery were comparable to those calculated from GPS surveys and geospatial data derived from aerial remote sensing but tended to overestimate shoreline erosion at highly erosive locations (greater than 2 m yr−1). High-resolution satellite imagery can increase the spatial scale-range of shoreline change monitoring, provide rapid response to estimate impacts of coastal erosion, and reduce cost of labor-intensive practices.

scholarly journals Fine-scale movement patterns and habitat selection of little owls (Athene noctua) from two declining populations

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256608
Author(s):  
Martin Mayer ◽  
Martin Šálek ◽  
Anthony David Fox ◽  
Frej Juhl Lindhøj ◽  
Lars Bo Jacobsen ◽  
...  
Keyword(s):  
Czech Republic ◽  
High Resolution ◽  
Habitat Selection ◽  
Bird Species ◽  
Space Use ◽  
Gps Data ◽  
The Czech Republic ◽  
Movement Trajectories ◽  
Athene Noctua ◽  
Little Owl

Advances in bio-logging technology for wildlife monitoring have expanded our ability to study space use and behavior of many animal species at increasingly detailed scales. However, such data can be challenging to analyze due to autocorrelation of GPS positions. As a case study, we investigated spatiotemporal movements and habitat selection in the little owl (Athene noctua), a bird species that is declining in central Europe and verges on extinction in Denmark. We equipped 6 Danish food-supplemented little owls and 6 non-supplemented owls in the Czech Republic with high-resolution GPS loggers that recorded one position per minute. Nightly space use, measured as 95% kernel density estimates, of Danish male owls were on average 62 ha (± 64 SD, larger than any found in previous studies) compared to 2 ha (± 1) in females, and to 3 ± 1 ha (males) versus 3 ± 5 ha (females) in the Czech Republic. Foraging Danish male owls moved on average 4-fold further from their nest and at almost double the distance per hour than Czech males. To create availability data for the habitat selection analysis, we accounted for high spatiotemporal autocorrelation of the GPS data by simulating correlated random walks with the same autocorrelation structure as the actual little owl movement trajectories. We found that habitat selection was similar between Danish and Czech owls, with individuals selecting for short vegetation and areas with high structural diversity. Our limited sample size did not allow us to infer patterns on a population level, but nevertheless demonstrates how high-resolution GPS data can help to identify critical habitat requirements to better formulate conservation actions on a local scale.

scholarly journals Impact of high-resolution data assimilation of GPS zenith delay on Mediterranean heavy rainfall forecasting

2009 ◽  
Vol 27 (7) ◽  
pp. 2739-2753 ◽  
Author(s):  
K. Boniface ◽  
V. Ducrocq ◽  
G. Jaubert ◽  
X. Yan ◽  
P. Brousseau ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Good Description ◽  
Weather Prediction ◽  
Precipitation Forecast ◽  
Convective Precipitation ◽  
Tropospheric Delay ◽  
Gps Data ◽  
Convective System ◽  
First Case

Abstract. Impact of GPS (Global Positioning System) data assimilation is assessed here using a high-resolution numerical weather prediction system at 2.5 km horizontal resolution. The Zenithal Tropospheric Delay (ZTD) GPS data from mesoscale networks are assimilated with the 3DVAR AROME data assimilation scheme. Data from more than 280 stations over the model domain have been assimilated during 15-day long assimilation cycles prior each of the two studied events. The results of these assimilation cycles show that the assimilation of GPS ZTD with the AROME system performs well in producing analyses closer to the ZTD observations in average. Then the impacts of assimilating GPS data on the precipitation forecast have been evaluated. For the first case, only the AROME runs starting a few hours prior the triggering of the convective system are able to simulate the convective precipitation. The assimilation of GPS ZTD observations improves the simulation of the spatial extent of the precipitation, but slightly underestimates the heaviest precipitation in that case compared with the experiment without GPS. The accuracy of the precipitation forecast for the second case is much better. The analyses from the control assimilation cycle provide already a good description of the atmosphere state that cannot be further improved by the assimilation of GPS observations. Only for the latest day (22 November 2007), significant differences have been found between the two parallel cycles. In that case, the assimilation of GPS ZTD allows to improve the first 6 to 12 h of the precipitation forecast.

scholarly journals HIGH RESOLUTION INTERFEROMETRIC DIGITAL ELEVATION MODEL GENERATION AND VALIDATION

2018 ◽  
Vol XLII-5 ◽  
pp. 755-756
Author(s):  
K. Malik ◽  
D. Kumar
Keyword(s):  
High Resolution ◽  
Stability Index ◽  
Gps Data ◽  
Model Generation ◽  
New Delhi ◽  
Quality Estimation ◽  
Stable Point ◽  
Digital Elevation ◽  
Elevation Model ◽  
Time Series Images

<p><strong>Abstract.</strong> In this paper high-resolution DEM generation has been attempted using the Cosmo-skymed data over the New Delhi, India area. The study area is an urban area filled with lots of building and settlement which was helpful to get the stable point in the time series images data. This DEM generation is based on the highly stable permanents scatter candidate (PSC). This PSC was selected on the basis of amplitude stability index which was generated/calculated using the 25 images of the cosmo-skymed acquired over the time. A sufficient number of field GPS data has been used for result validation. Interpolated output DEM at 10-meter resolution has also been compared with the available SRTM and ASTER DEM for further quality estimation. Presented result demonstrate the capabilities of the technique in constructing a high-resolution quality DEM.</p>

Sign in / Sign up

Export Citation Format

Share Document