Urban tree classification using discrete-return LiDAR and an object-level local binary pattern algorithm-Reference-Cited by-同舟云学术

Urban tree classification using discrete-return LiDAR and an object-level local binary pattern algorithm

Published:2019-10-24 Issue:16 Volume:36 Page:1785-1803
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Azeez Omer Saud¹^ORCID,Pradhan Biswajeet²^ORCID,Jena Ratiranjan²^ORCID

Affiliation:

1. Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, UPM, Serdang, Malaysia

2. The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and Information Technology, University of Technology Sydney, Australia

Funder

Centre for Advanced Modelling and Geospatial Information Systems CAMGIS)

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2019.1678675

Reference65 articles.

1. Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)

2. Modeling of CO Emissions from Traffic Vehicles Using Artificial Neural Networks

3. Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS

4. Classification and feature extraction for remote sensing images from urban areas based on morphological transformations

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