Next Article in Journal
Global Analysis of Burned Area Persistence Time with MODIS Data
Next Article in Special Issue
Spatial Accessibility of Urban Forests in the Pearl River Delta (PRD), China
Previous Article in Journal
Preliminary Investigation of a New AHI Aerosol Optical Depth (AOD) Retrieval Algorithm and Evaluation with Multiple Source AOD Measurements in China
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle

A New Algorithm for MLS-Based DBH Mensuration and Its Preliminary Validation in an Urban Boreal Forest: Aiming at One Cornerstone of Allometry-Based Forest Biometrics

1,* and 2
1
Institute of Remote Sensing & GIS, Beijing Key Lab of Spatial Information Integration and Its Applications, School of Earth and Space Sciences, Peking University, Beijing 100871, China
2
Institute of Mineral Resources Research, China Metallurgical Geology Bureau, Beijing 100025, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(5), 749; https://doi.org/10.3390/rs10050749
Received: 31 March 2018 / Revised: 28 April 2018 / Accepted: 9 May 2018 / Published: 14 May 2018
(This article belongs to the Special Issue Remote Sensing of Urban Forests)
  |  
PDF [3690 KB, uploaded 14 May 2018]
  |  

Abstract

This study aimed to improve one basic circle of allometry-based forest biometrics—diameter at breast height (DBH) mensuration. To address its common shortage of low efficiency in field measurement, this study attempted mobile laser scanning (MLS) as an efficient alternative and proposed a new MLS-based DBH mensuration algorithm to further exclude the effect of stem bending. That is, prior to the procedure of cone-based geometric modeling of a tree stem, an operation of Aligning the local stem axis series that is calculated by the Successive Cone-based Fitting of those continuously equi-height-layered laser points on the stem (ASCF) is appended. In the case of an urban boreal forest, tests showed that the proposed algorithm worked better (the coefficient of determination, R2 = 0.81 and root mean square error, RMSE = 52.1 mm) than the circle- (0.16 and 189.4 mm), cylinder- (0.77 and 58.7 mm), and cone-based (0.77 and 56.7 mm) geometric modeling algorithms. From a methodological viewpoint, the new ASCF algorithm was preliminarily validated for MLS-based tree DBH mensuration, with the “cornerstone-rebuilding” significance for allometry-based forest biometrics. With the development of MLS variants available for complex forest environments, this study will contribute fundamental implications for advancements in forestry. View Full-Text
Keywords: diameter at breast height (DBH); mobile laser scanning (MLS); mensuration; allometry; forest biometrics diameter at breast height (DBH); mobile laser scanning (MLS); mensuration; allometry; forest biometrics
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Lin, Y.; Jiang, M. A New Algorithm for MLS-Based DBH Mensuration and Its Preliminary Validation in an Urban Boreal Forest: Aiming at One Cornerstone of Allometry-Based Forest Biometrics. Remote Sens. 2018, 10, 749.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top