Next Article in Journal / Special Issue
Enhanced Map-Matching Algorithm with a Hidden Markov Model for Mobile Phone Positioning
Previous Article in Journal
An Efficient Query Algorithm for Trajectory Similarity Based on Fréchet Distance Threshold
Previous Article in Special Issue
Development of a Safety Index to Identify Differences in Safety Performance by Postal Delivery Motorcyclists Based either in Different Regional Post Offices or within the Same Regional Office
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle

Simplifying GPS Trajectory Data with Enhanced Spatial-Temporal Constraints

Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou 450052, Henan, China
Department of Geography, Texas State University, San Marcos, TX 78666, USA
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2017, 6(11), 329;
Received: 27 July 2017 / Revised: 9 October 2017 / Accepted: 24 October 2017 / Published: 30 October 2017
PDF [5526 KB, uploaded 31 October 2017]


Raw GPS trajectory data are often very large and use up excessive storage space. The efficiency and accuracy of activity patterns analysis or individual–environment interaction modeling using such data may be compromised due to data size and computational needs. Line generalization algorithms may be used to simplify GPS trajectories. However, traditional algorithms focus on geometric characteristics of linear features. Trajectory data may record information beyond location. Examples include time and elevation, and inferred information such as speed, transportation mode, and activities. Effective trajectory simplification should preserve these characteristics in addition to location and orientation of spatial-temporal movement. This paper proposes an Enhanced Douglas–Peucker (EDP) algorithm that implements a set of Enhanced Spatial-Temporal Constraints (ESTC) when simplifying trajectory data. These constraints ensure that the essential properties of a trajectory be preserved through preserving critical points. Further, this study argues that speed profile can uniquely identify a trajectory and thus it can be used to evaluate the effectiveness of a trajectory simplification. The proposed ESTC-EDP simplification method is applied to two examples of GPS trajectory. The results of trajectory simplification are reported and compared with that from traditional DP algorithm. The effectiveness of simplification is evaluated. View Full-Text
Keywords: GPS trajectory; line simplification; spatial-temporal constraints; critical points; speed profile GPS trajectory; line simplification; spatial-temporal constraints; critical points; speed profile

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Qian, H.; Lu, Y. Simplifying GPS Trajectory Data with Enhanced Spatial-Temporal Constraints. ISPRS Int. J. Geo-Inf. 2017, 6, 329.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top