Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery-Reference-Cited by-同舟云学术

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Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery

Published:2017-04 Issue: Volume:126 Page:129-145
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Dechesne Clément,Mallet Clément,Le Bris Arnaud,Gouet-Brunet Valérie

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference54 articles.

1. Normalization of the directional effects in NOAA–AVHRR reflectance measurements for an improved monitoring of vegetation cycles;Bacour;Remote Sensing Environ.,2006

2. Random forest in remote sensing: a review of applications and future directions;Belgiu;ISPRS J. Photogr. Remote Sensing,2016

3. Learning OpenCV: Computer Vision with the OpenCV Library;Bradski,2008

4. A graph cut optimization guided by 3d-features for surface height recovery;Chehata;ISPRS J. Photogr. Remote Sensing,2009

5. Semi-supervised SVM for individual tree crown species classification;Dalponte;ISPRS J. Photogr. Remote Sensing,2015

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