Object-Based Canopy Gap Segmentation and Classification: Quantifying the Pros and Cons of Integrating Optical and LiDAR Data

Object-Based Canopy Gap Segmentation and Classification: Quantifying the Pros and Cons of Integrating Optical and LiDAR Data

Delineating canopy gaps and quantifying gap characteristics (e.g., size, shape, and dynamics) are essential for understanding regeneration dynamics and understory species diversity in structurally complex forests. Both high spatial resolution optical and light detection and ranging (LiDAR) remote se...

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Bibliographic Details
Main Authors: Jian Yang, Trevor Jones, John Caspersen, Yuhong He
Format: Article
Language:English
Published: MDPI AG 2015-11-01
Series:Remote Sensing
Subjects:
canopy gap segmentation
classification
Object-Based Image Analysis (OBIA)
high spatial resolution
multispectral image
LiDAR
data integration
Online Access:http://www.mdpi.com/2072-4292/7/12/15811

Internet

http://www.mdpi.com/2072-4292/7/12/15811

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