Influence of mobile light detecting and ranging data quality in road runoff evaluation

Higinio González-Jorge; Lucia Díaz-Vilariño; Joaquin Martínez-Sánchez; Pedro Arias

doi:10.1117/1.JRS.10.044001

7 October 2016 Influence of mobile light detecting and ranging data quality in road runoff evaluation

Higinio González-Jorge, Lucia Díaz-Vilariño, Joaquin Martínez-Sánchez, Pedro Arias

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 10, Issue 4, 044001 (October 2016). https://doi.org/10.1117/1.JRS.10.044001

Abstract

A mobile light detecting and ranging (LiDAR) system is used to provide point cloud datasets as a topographic base for runoff studies. The point clouds are rasterized to evaluate road runoff using the D8 algorithm. Gaussian noise is artificially induced in the point cloud to simulate inaccuracies in geopositioning and determine its influence in the evaluation of runoff direction. Accuracy in the determination of flow direction decreases with the increase of Gaussian noise. Accuracy also decreases with the decrease of the cell size of the raster dataset. Flow direction shows inaccuracies up to 47 deg with a cell resolution of 0.5 m and Gaussian noise of 0.15 m (standard deviation). On the other hand, cell resolutions of 5 m show a maximum difference of 15 deg with the same noise.

Citation Download Citation

Higinio González-Jorge, Lucia Díaz-Vilariño, Joaquin Martínez-Sánchez, and Pedro Arias "Influence of mobile light detecting and ranging data quality in road runoff evaluation," Journal of Applied Remote Sensing 10(4), 044001 (7 October 2016). https://doi.org/10.1117/1.JRS.10.044001

Published: 7 October 2016

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available