Vol. 16, No. 1, 9-20, 2017

ALS for terrain mapping in forest environments: an analysis of lidar filtering algorithms
Mihnea Cățeanu, and Ciubotaru Arcadie

Abstract
Remote sensing enables the recording of accurate geomorphological data with the capability to efficiently cover large areas. However, the presence of vegetation makes the use of remote methods for terrain mapping difficult. LiDAR (Light Detection And Ranging) data collection by means of ALS (Airborne Laser Scanning) can be a solution for forestry projects, as the laser pulses cross the entire forest canopy and reach the soil underneath. In order to obtain an accurate digital terrain model, the ALS data must be processed, so as to determine which returns are at ground level. This process is called filtering or classification.

This paper aims to provide a performance analysis of nine algorithms for ALS data classification. The algorithm performance is reviewed for the case of mountainous terrain, characterised by moderate and steep slopes and forest vegetation of a generally high consistency. Out of the nine algorithms tested, two are commercial ones and the others are free.

Our findings suggest that the Lasground-new algorithm implemented in the LAStools (Rapidlasso) software package provides the most accurate results, with a Root Mean Square Error of elevation values for the study site of 0.34 metres (with over 80 percent of the area having an elevation error of less than 0.20 metres) and an average RMSE for the field plots of 0.66 metres. Reference data for RMSE calculation is a DTM interpolated from the ALS point cloud, as classified by the data provider. Some of the free algorithms tested provide relatively similar results in terms of RMSE (for example, MLS and SMRF have RMSE values of 0.56 metres and 0.60 metres, respectively). The correlation between ground slope and RMSE of elevation values is considered for the eight field surveyed plots, with R² having a value of 0.89.

Taking into account the difficult test conditions (topographically complex surface with dense canopy cover) we consider ALS data to be a possible solution for collecting geomorphological data for forestry applications, as long as data at a relatively low spatial resolution is sufficient.

View Full Text (pdf file, 600 kB) previous page
DOI: 10.12760/01-2017-1-02

History
Submitted: 30 Nov 2016
Revised: 08 Mar 2017
Accepted: 03 Apr 2017
Published: 05 May 2017
Responsible editor: Rainer Reuter

Citation
Cățeanu M & C Arcadie, 2017. ALS for terrain mapping in forest environments: an analysis of lidar filtering algorithms. EARSeL eProceedings, 16(1): 9-20
EARSeL-logo

EARSeL European Association of Remote Sensing Laboratories, Strasbourg, France

   
BIS-logo

BIS-Verlag
BIS Library and Information System, Carl von Ossietzky University of Oldenburg

   
Scopus-logo

Indexed in Scopus

   
DOAJ logo

DOAJ
Directory of Open Access Journals

   
SPERPA/RoMEO logo

SHERPA/RoMEO
Opening access to research

   
JournalGuide logo

JournalGuide
Find the best journal for your research

Creative Commons License

ISSN 1729-3782