Individual Tree Detection Based on High-Resolution RGB Images for Urban Forestry Applications
Author:
Affiliation:
1. School of Geography and Planning, Sun Yat-sen University, Guangzhou, China
2. Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou, China
Funder
Guangzhou Postdoctoral Research Project
Special Project for Research and Development in Key areas of Guangdong Province
Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09765982.pdf?arnumber=9765982
Reference36 articles.
1. A new method for 3D individual tree extraction using multispectral airborne LiDAR point clouds
2. Open-Source tools in R for forestry and forest ecology
3. Airborne LiDAR Remote Sensing for Individual Tree Forest Inventory Using Trunk Detection-Aided Mean Shift Clustering Techniques
4. Individual Tree Detection in a Eucalyptus Plantation Using Unmanned Aerial Vehicle (UAV)-LiDAR
5. Detection of individual trees in urban alignment from airborne data and contextual information: A marked point process approach
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