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Forest and Grassland Resources Research >

2021 , Vol. 0 >Issue 1: 173 - 179

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2021.01.022

Technical Application

Research on Crown Extraction Based on Improved Faster R-CNN Model

  • Yanxiao HUANG ,
  • Luming FANG ,
  • Siqi HUANG ,
  • Haili GAO ,
  • Laibang YANG ,
  • Xiongwei LOU
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  • 1. School of Information Engineering,Zhejiang A & F University,Hangzhou Zhejiang 311300,China
    2. Key Laboratory of State Forestry and Grassland Administration on Forestry Sensing Technology and Intelligent Equipment,Hangzhou Zhejiang 311300,China
    3. Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province,Hangzhou Zhejiang 311300,China
    4. Jiyang College of Zhejiang A & F University,Zhuji Zhejiang 311800,China
    5. College of Forestry and Biotechnology,Zhejiang A & F University,Hangzhou Zhejiang 311300,China

Received date: 2020-10-07

  Revised date: 2020-12-18

  Online published: 2021-03-30

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Abstract

Canopy information is an important part of forest resources investigation.The traditional method of crown width measurement is through field survey,which may result in a significant error in the specific terrain and forest environment,along with great labor force,cumbersome and time-consuming operation procedure.The development of UAV imaging technology and machine learning provides a new method and realization idea for crown measurement.This paper employed UAV to obtain the orthophoto images of two pure Metasequoia glyptostroboides in the greenway of Qingshanhu in the east of Lin'an District.An advanced object detection method,Faster R-CNN,was improved to recognize the tree crown and extract the crown width.The Accuracy and R 2 of the improved Faster R-CNN model are 92.92% and 0.84 respectively,which are 5.31% and 0.12 higher than those of the original model.This shows that the UAV and object detection technology are feasible to identify the tree crown.Compared with the traditional survey method,it has the advantages of high efficiency,convenience and low cost.

Key words： UAV images; crown recognition; crown width measurement; object detection; Faster R-CNN

Cite this article

Yanxiao HUANG , Luming FANG , Siqi HUANG , Haili GAO , Laibang YANG , Xiongwei LOU . Research on Crown Extraction Based on Improved Faster R-CNN Model[J]. Forest and Grassland Resources Research, 2021 , 0(1) : 173 -179 . DOI: 10.13466/j.cnki.lyzygl.2021.01.022

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