Accuracy Assessment of Stem Classification Obtained from Forest Point Cloud Using FSCT Algorithm-Reference-Cited by-同舟云学术

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Accuracy Assessment of Stem Classification Obtained from Forest Point Cloud Using FSCT Algorithm

Published:2023-07-16 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Kushwaha Sunni Kanta Prasad¹,Singh Arunima²,Jain Kamal¹,Cabo Carlos³,Mokros Martin²

Affiliation:

1. Indian Institute of Technology Roorkee,Geomatics Group,Department of Civil Engineering,Roorkee,India,247667

2. Czech University of Life Sciences,Faculty of Forestry and Wood Sciences,Prague,Czech Republic,16500

3. University of Oviedo,Department of Mining Exploitation,Campus de Mieres,Spain,33600

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10283148.pdf?arnumber=10283148

Reference9 articles.

1. Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory

2. An approach for tree volume estimation using RANSAC and RHT algorithms from TLS dataset

3. Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds

4. Point-cloud segmentation of individual trees in complex natural forest scenes based on a trunk-growth method

5. Terrestrial Laser Scanning for Plot-Scale Forest Measurement

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