World's Best Scientists 2026 revealed!
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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
77
Citations
21204
World Ranking
1288
National Ranking
43

Research.com Recognitions

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2023 - IEEE Fellow for contributions to point cloud analytics in LiDAR remote sensing
  • 2023 - Research.com Computer Science in Canada Leader Award
  • 2022 - Fellow of the Engineering Institute of Canada
  • 2022 - Fellow of the Canadian Academy of Engineering
  • 2022 - Fellow of the Asia-Pacific Artificial Intelligence Association
  • 2022 - Research.com Computer Science in Canada Leader Award

Overview

Jonathan Li is a researcher affiliated with the University of Waterloo in Canada. Their work spans multiple fields, with a focus on engineering, environmental science, and computer science. They have contributed extensively to subfields such as environmental engineering, computer vision and pattern recognition, geology, computational mechanics, and media technology.

Li's research covers a range of topics, particularly centered on remote sensing and LiDAR applications. Other main research themes include 3D surveying and cultural heritage, 3D shape modeling and analysis, automated road and building extraction, advanced neural network applications, remote-sensing image classification, and remote sensing in agriculture.

The scientist has published frequently in several venues, including:

  • International Journal of Applied Earth Observation and Geoinformation
  • arXiv (Cornell University)
  • IEEE Transactions on Geoscience and Remote Sensing
  • ISPRS Journal of Photogrammetry and Remote Sensing
  • IEEE Transactions on Intelligent Transportation Systems

Some recent papers authored or co-authored by Li include:

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review (2020), published in IEEE Transactions on Neural Networks and Learning Systems
  • Review: Deep Learning on 3D Point Clouds (2020), published in Remote Sensing
  • A random forest ranking approach to predict yield in maize with uav-based vegetation spectral indices (2020), published in Computers and Electronics in Agriculture
  • The global carbon sink potential of terrestrial vegetation can be increased substantially by optimal land management (2022), published in Communications Earth & Environment
  • The Segment Anything Model (SAM) for remote sensing applications: From zero to one shot (2023), published in International Journal of Applied Earth Observation and Geoinformation

Jonathan Li collaborates frequently with several researchers, including José Marcato, Cheng Wang, Lingfei Ma, Wesley Nunes Gonçalves, and Kyle Gao. Their collaborative efforts have resulted in numerous publications.

Best Publications

  • Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

    Zilong Zhong;Jonathan Li;Zhiming Luo;Michael Chapman

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

    Ying Li;Lingfei Ma;Zilong Zhong;Fei Liu

  • A Review on Deep Learning in UAV Remote Sensing

    Lucas Prado Osco;José Marcato Junior;Ana Paula Marques Ramos;Lúcio André de Castro Jorge

  • Review: deep learning on 3D point clouds

    Saifullahi Aminu Bello;Shangshu Yu;Cheng Wang;Jibril Muhmmad Adam

  • Squeeze-and-Attention Networks for Semantic Segmentation

    Zilong Zhong;Zhong Qiu Lin;Rene Bidart;Xiaodan Hu

  • A study on DEM-derived primary topographic attributes for hydrologic applications: Sensitivity to elevation data resolution

    Simon Wu;Jonathan Li;G.H. Huang

  • Using mobile laser scanning data for automated extraction of road markings

    Haiyan Guan;Jonathan Li;Jonathan Li;Yongtao Yu;Cheng Wang

  • Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds

    Bisheng Yang;Lina Fang;Jonathan Li

  • Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways

    Weikai Tan;Nannan Qin;Lingfei Ma;Ying Li

  • A random forest ranking approach to predict yield in maize with uav-based vegetation spectral indices

    Ana Paula Marques Ramos;Lucas Prado Osco;Danielle Elis Garcia Furuya;Wesley Nunes Gonçalves

  • Fractional vegetation cover estimation in arid and semi-arid environments using HJ-1 satellite hyperspectral data

    Xianfeng Zhang;Chunhua Liao;Jonathan Li;Quan Sun

  • Use of mobile LiDAR in road information inventory: a review

    Haiyan Guan;Jonathan Li;Shuang Cao;Yongtao Yu

  • LO-Net: Deep Real-Time Lidar Odometry

    Qing Li;Shaoyang Chen;Cheng Wang;Xin Li

  • Mobile Laser Scanned Point-Clouds for Road Object Detection and Extraction: A Review

    Lingfei Ma;Ying Li;Jonathan Li;Cheng Wang

  • Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A Factorized Architecture Search Framework

    Zilong Zhong;Ying Li;Lingfei Ma;Jonathan Li

  • Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Cheng Wang

  • Integration of orthoimagery and lidar data for object-based urban thematic mapping using random forests

    Haiyan Guan;Jonathan Li;Michael Chapman;Fei Deng

  • Fully convolutional networks for building and road extraction: Preliminary results

    Zilong Zhong;Jonathan Li;Weihong Cui;Han Jiang

  • Deep learning-based tree classification using mobile LiDAR data

    Haiyan Guan;Yongtao Yu;Zheng Ji;Jonathan Li

  • A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery

    Lucas Prado Osco;Mauro dos Santos de Arruda;José Marcato Junior;Neemias Buceli da Silva

  • Automated Extraction of Road Markings from Mobile Lidar Point Clouds

    Bisheng Yang;Lina Fang;Qingquan Li;Jonathan Li

  • Learning Hierarchical Features for Automated Extraction of Road Markings From 3-D Mobile LiDAR Point Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Fukai Jia

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

    Ying Li;Lingfei Ma;Zilong Zhong;Fei Liu

Frequent Co-Authors

Yongtao Yu
Yongtao Yu Huaiyin Institute of Technology
Yulan Guo
Yulan Guo Sun Yat-sen University
Jun Yu
Jun Yu Hangzhou Dianzi University
Bisheng Yang
Bisheng Yang Wuhan University
Guohe Huang
Guohe Huang University of Regina
Sisi Zlatanova
Sisi Zlatanova University of New South Wales
Alexander Wong
Alexander Wong University of Waterloo
Qingquan Li
Qingquan Li Shenzhen University
Peng Cui
Peng Cui Chinese Academy of Sciences
Yongfei Bai
Yongfei Bai Chinese Academy of Sciences

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