Abstract

The aim of this study was to investigate to which degree the accuracy of vegetation classification could be improved by combining optical satellite data and airborne laser scanner (ALS) data, compared with using satellite data only. A Satellite Pour l'Observation de la Terre (SPOT) 5 scene and Leica ALS 50-II data from 2009, covering a test area in the mid-Sweden (latitude 60 degrees 43' N, longitude 16 degrees 43' E), were used in maximum likelihood and decision tree classifications. Training and validation data were obtained from the interpretation of digital aerial photo stereo models. Combination of SPOT and ALS data gave classification accuracies up to 72%, compared with 56% using only SPOT data. This indicates that integrating features from large area laser scanning may lead to significant improvements in satellite data-based vegetation classifications.

Keywords

Vegetation classification; Airborne laser scanning; SPOT

Published in

Remote Sensing Letters
2012, Volume: 3, number: 5, pages: 393-401
Publisher: TAYLOR & FRANCIS LTD

SLU Authors

• Nordkvist, Karin

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Granholm, Ann-Helen

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Holmgren, Johan

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Olsson, Håkan

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Nilsson, Mats

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Forest Science
Remote Sensing


Publication identifier

DOI: https://doi.org/10.1080/01431161.2011.606240

Permanent link to this page (URI)

https://res.slu.se/id/publ/56604