Haozhou Wang (王浩舟)

Haozhou Wang (王浩舟)

Ph.D Candidate

The University of Tokyo

International Field Phenomics Research Laboratory

Remote Sensing Plant Phenotyping


A graduate student in 3D high-throughput phenotyping of agriculture, deploy skills in UAV 3d reconstruction data analysis and Python programming.

主要研究方向为农业三维高通量表型, 负责三维重建后的数据分析以及Python编程。

Research Interest (研究方向)

  • Plant phenotyping by 3D reconstruction (三维植物重建表型)
  • Non-structural 3D data analysis, e.g. point cloud data (非结构化三维数据处理, 如点云数据)
  • Forest mensuration by spherical camera (全景相机测树)

Education (教育背景)

  • MSc in Forestry, The University of New Brunswick, 2019.12
  • BSc in Ecology, The Nanjing Forestry University (南京林业大学), 2017.06



The University of New Brunswick (新不伦瑞克大学)


A Python Program to measure tree attributes (Basal Area, DBH, Height, Gap Fraction) from two Ricoh Theta spherical image pair taken at different height.

通过不同高度的全景图像(Ricoh theta)像对,测量胸高断面积、胸径、树高、郁闭度等参数

Chinese Academy of Forestry (中国林业科学研究院)


Unmanned Aerial Vehicles - High Resolution imagery Analysis Platform (UAV-HiRAP), is an open-source, web-based platform which provides service for image classification (maintenance suspended).




Wang, H., Kershaw, J.A., Yang, T.-R., Hsu, Y.-H., Ma, X., Chen, Y., 2020. An Integrated System for Estimating Forest Basal Area from Spherical Images. Mathematical and Computational Forestry & Natural-Resource Sciences 12(0), 0–14.

Wang, H., Han, D., Mu, Y., Jiang, L., Yao, X., Bai, Y., Lu, Q., Wang, F., 2019. Landscape-level vegetation classification and fractional woody and herbaceous vegetation cover estimation over the dryland ecosystems by unmanned aerial vehicle platform. Agricultural and Forest Meteorology 278, 107665.

Wang, H., 2019. Estimating Forest Attributes from Spherical Images (MSc Forestry thesis). The University of New Brunswick.

Han, D., Wang, H., Zheng B., Wang, F., 2018. Vegetation type classification and fractional vegetation coverage estimation for an open elm (Ulmus pumila ) woodland ecosystem during a growing season based on an unmanned aerial vehicle platform coupled with decision tree algorithms (基于无人机和决策树算法的榆树疏林草原植被类型划分和覆盖度生长季动态估计). Acta Ecologica Sinica (生态学报) 38(18), 6655-6663.

Wang, H., 2017. Extracting DBH Measurements from RGB Photo Images (BSc Ecology thesis). The Nanjing University of Forestry.
Feldman, A., Wang, H., Fukano, Y., Kato, Y., Ninomiya, S., Guo, W., February 24-27, 2020. Affordable high-throughput processing of handheld camera images of container plants to phenotypic data (poster), Phenome 2020, Tucson Convention Center, Tucson, Arizona, U.S.

Feldman, A., Wang, H., Fukano, Y., Guo, W., October 22-25, 2019. Affordable high-throughput processing of multi-scale images to phenotypic data (poster). The 6th International Plant Phenotyping Symposium, Nanjing Dongjiao State Guesthouse, Nanjing, Jiangsu, China.

Wang, H., Kershaw, J.A., June 23-25, 2019. Estimating Forest Attributes from Spherical Images (oral, poster). The Western Mensurationists 2019 Annual Meeting, Kamloops Hotel and Conf. Center, Kamloops, British Columbia, Canada.

Wang, H., Kershaw, J.A., March 23, 2018. Measuring Plant Area Index (PAI) from panorama photo images (oral). The 25th Annual UNB Graduate Research Conference (GRC), Wu Conference Center, Fredericton, New Brunswick, Canada.

Wang, H., Kershaw, J.A., November 5-7, 2017. Extracting DBH Measurements from RGB Photo Images (oral). The Northeastern Mensurationists 2017 Annual Meeting, The Inn at Saratoga. Saratoga Springs, New York, U.S.

Wang, H., Wang, F., Yao, X., Mu, Y., Bai, Y., Lu, Q., August 20-25, 2017 . UAV-HiRAP: A novel method to improve landscape-level vegetation classification and coverage fraction estimation with unmanned aerial vehicle platform (oral). The 12th International Congress of Ecological (INTECOL), China National Convention Center, Beijing, China.
王锋,韩东,王浩舟,卢琦,潘绪斌,一种基于无人机的景观尺度植被覆盖度的计算方法及系统:2019. CN 201610913357

无人机高精度影像分析平台[简称: UAV-HiRAP] v3.0, 2019. 软著登字第 2019SR0286422.

无人机高精度影像分析平台[简称: UAV-HiRAP] v2.0, 2017. 软著登字第 2017SR558256.

无人机高精度影像分析平台[简称: UAV-HiRAP] v1.0, 2016. 软著登字第 2016SR198498.

Yaira 实测数据多维可视化软件[简称:Yaira] v1.0, 2016. 软著登字第 2016SR178462.

Experience Timeline


Apr, 2020

The University of Tokyo | 东京大学

The Doctoral Student in Agricultural | 农学博士在读

The research proposal is "Development of 3D high-throughput close-range remote sensing phenotyping applications for agronomy".


Sept, 2017
Dec, 2019

The University of New Brunswick | 新不伦瑞克大学

Master of Science in Forestry | 林学研究型硕士

Focus on the area of distorted analyzing forest images taken by fisheye and spherical camera. Participated several university and international oral presentation and competition. The title of Thesis is "Estimating Forest Attributes from Spherical Images"


May, 2016
Aug, 2016

The Chinese Academy of Forestry | 中国林业科学研究院

Internship | 实习

Developing software for UAV image analysis in sparse Elm grassland. Registor software copyright for Matlab based UAV-HiRAP and Web-based UAV-HiRAP (www.uav-hirap.org) for semi-automatic classify plants and backgrounds. The achievements were extended to a patent, an oral presentation on The 12th International Congress of Ecological, and pulished on top journal "Acta Ecologica Sinica" and "Agricultural and Forest Meteorology", respectively.


Sept, 2013
June, 2017

The Nanjing Forestry University | 南京林业大学

Bachelor of Science in Ecology | 生态学学士

During the study period, participated all kinds of activaties during study period, envolved in the College Student Innovation Training Projects and applied two software copyrights. The last year as a transfer student in the University of New Brunsiwick. The titile of dissertation is "Extracting DBH Measurements from RGB Photo Images"