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Conference paper2011Peer reviewed

Change detection of mountain vegetation using multi-temporal ALS point clouds

Nyström, Mattias; Holmgren, Johan; Olsson, Håkan

Abstract

Multi-temporal laser scanner data to be used in change detection studies will most likely be acquired with different sensors, flying altitudes, and system parameters. Therefore, calibration is probably needed in order to make laser returns from vegetation comparable between two laser data acquisitions. In this study, two ALS point clouds were acquired with different sensors and flying altitudes. The first data set had 11.5 points m-2 and was obtained in 2008 with a TopEye MKII scanner and the second with a density of 1.1 points m-2 was obtained in 2010 with an Optech ALTM Gemini scanner. The test site was located in Abisko in northern Sweden with forest dominated by mountain birch. Six meter radius sample plots were placed in the forest-tundra ecotone and assigned one of the following treatments: (1) reference with no removal of trees, (2) removal of 50% of the total number of stems above 1.5 m, and (3) removal of 100% of the total number of stems above 1.5 m. Histogram matching was used to calibrate the two data sets and sample plots were then classified into the three treatments. The overall classification accuracy was 82% using only the proportion of vegetation returns from the canopy as explanatory variable. Features created from gridded laser data had overall higher classification accuracy than laser features created directly from the point cloud. Histogram matching made the two data sets comparable by reducing the difference between them. These early results show how changes can be detected even with different sensors, flying altitudes, and system parameters

Keywords

Airborne laser scanning; histogram matching; multi-temporal; LiDAR; change detection

Published in


Publisher: SilviLaser

Conference

SilviLaser 2011 : 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: Applications for Assessing Forest Ecosystems