Cahalane, Conor
(2015)
Combining 2D Mapping and Low Density Elevation Data in
a GIS for GNSS Shadow Prediction.
ISPRS International Journal of Geo-Information, 4.
pp. 2769-2791.
ISSN 2220-9964
Abstract
The number of satellites visible to a Global Navigation Satellite System (GNSS)
receiver is important for high accuracy surveys. To aid with this, there are software packages
capable of predicting GNSS visibility at any location of the globe at any time of day. These
prediction packages operate by using regularly updated almanacs containing positional data
for all navigation satellites; however, one issue that restricts their use is that most packages
assume that there are no obstructions on the horizon. In an attempt to improve this, certain
planning packages are now capable of modelling simple obstructions whereby portions of the
horizon visible from one location can be blocked out, thereby simulating buildings or other
vertical structures. While this is useful for static surveys, it is not applicable for dynamic
surveys when the GNSS receiver is in motion. This problem has been tackled in the past by
using detailed, high-accuracy building models and designing novel methods for modelling
satellite positions using GNSS almanacs, which is a time-consuming and costly approach.
The solution proposed in this paper is to use a GIS to combine existing, freely available
GNSS prediction software to predict pseudo satellite locations, incorporate a 2.5D model
of the buildings in an area created with national mapping agency 2D vector mapping and
low density elevation data to minimise the need for a full survey, thereby providing savings
in terms of cost and time. Following this, the ESRI ArcMap viewshed tool was used to
ascertain what areas exhibit poor GNSS visibility due to obstructions over a wide area, and
an accuracy assessment of the procedure was made.
Item Type: |
Article
|
Additional Information: |
© 2015 by the author; licensee MDPI, Basel, Switzerland. This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution license
(http://creativecommons.org/licenses/by/4.0/). |
Keywords: |
GNSS shadowing; GNSS prediction; mobile surveys; viewshed; |
Academic Unit: |
Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG |
Item ID: |
6939 |
Identification Number: |
https://doi.org/10.3390/ijgi4042769 |
Depositing User: |
Conor Cahalane
|
Date Deposited: |
01 Feb 2016 15:32 |
Journal or Publication Title: |
ISPRS International Journal of Geo-Information |
Publisher: |
MDPI |
Refereed: |
Yes |
Funders: |
Irish Research Council (IRC), Pavement Management Services Ltd., National Roads Authority (ERA-NET SR01 projects), Science Foundation Ireland (SFI) |
URI: |
|
Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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