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Individual Tree Species Classification by Illuminated—Shaded Area Separation
Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, Geodeetinrinne 2, 02431 Kirkkonummi, Finland
* Author to whom correspondence should be addressed.
Received: 10 October 2009; in revised form: 11 December 2009 / Accepted: 16 December 2009 / Published: 28 December 2009
Abstract: A new method, called Illumination Dependent Colour Channels (IDCC), is presented to improve individual tree species classification. The method is based on tree crown division into illuminated and shaded parts on a digital aerial image. Colour values of both sides of the tree crown are then used in species classification. Tree crown division is achieved by comparing the projected location of an aerial image pixel with its neighbours on a Canopy Height Model (CHM), which is calculated from a synchronized LIDAR point cloud. The sun position together with the mapping aircraft position are also utilised in illumination status detection. The new method was tested on a dataset of 295 trees and the classification results were compared with ones measured with two other feature extraction methods. The results of the developed method gave a clear improvement in overall tree species classification accuracy.
Keywords: LIDAR; forestry; fusion; classification; aerial; imagery; multispectral
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MDPI and ACS Style
Puttonen, E.; Litkey, P.; Hyyppä, J. Individual Tree Species Classification by Illuminated—Shaded Area Separation. Remote Sens. 2010, 2, 19-35.
Puttonen E, Litkey P, Hyyppä J. Individual Tree Species Classification by Illuminated—Shaded Area Separation. Remote Sensing. 2010; 2(1):19-35.
Puttonen, Eetu; Litkey, Paula; Hyyppä, Juha. 2010. "Individual Tree Species Classification by Illuminated—Shaded Area Separation." Remote Sens. 2, no. 1: 19-35.