Object-based classification of QuickBird image and low point density LIDAR for tropical trees and shrubs mapping
This paper assessed the performance of object-based supervised support vector machine (SVM) and rule-based techniques in classifying tropical vegetated floodplain using 0.6m QuickBird image and LIDAR dataset of 1.4 points per square meter (PPSM). This is particularly significant in hydraulic modelli...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Associazione Italiana di Telerilevamento
2015
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Online Access: | http://psasir.upm.edu.my/id/eprint/45638/1/LIDAR.pdf http://psasir.upm.edu.my/id/eprint/45638/ https://www.researchgate.net/publication/283420893_Object-based_classification_of_QuickBird_image_and_low_point_density_LIDAR_for_tropical_trees_and_shrubs_mapping/link/56379cf308ae30cbeff4d2a3/download |
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Institution: | Universiti Putra Malaysia |
Language: | English |
Internet
http://psasir.upm.edu.my/id/eprint/45638/1/LIDAR.pdfhttp://psasir.upm.edu.my/id/eprint/45638/
https://www.researchgate.net/publication/283420893_Object-based_classification_of_QuickBird_image_and_low_point_density_LIDAR_for_tropical_trees_and_shrubs_mapping/link/56379cf308ae30cbeff4d2a3/download