Jonathan Li

Professor

EV1-232, ext. 40577
junli@uwaterloo.ca

Jonathan Li is a full professor of geospatial data science at the Department of Geography and environmental management and a professor of artificial intelligence cross-appointed at the Department of Systems Design Engineering, University of Waterloo. His research interests are in urban remote sensing and geospatial data science, especially in automated extraction of geometric and semantic information from earth observation images and LiDAR point clouds using artificial intelligence (AI) algorithms. His recent research focuses on the use of the inhomogeneous and unstructured point clouds acquired by LiDAR and photogrammetry to generate high-definite (HD) maps and digital terrain models to support the development in digital twin cities and autonomous vehicles. He is elected Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the Royal Society of Canada (RSC) Academy of Science, the Canadian Academy of Canada (CAE), and the Engineering Institute of Canada (EIC), respectively. He is currently elected President of the Canadian Institute of Geomatics (CIG), Editor-in-Chief of the International Journal of Applied Earth Observation and Geoinformation (JAG), Associate Editor of the IEEE Transactions on Geoscience and Remote Sensing (TGRS) and the Editorial Board member of the Elsevier’s journal of Geomatica. For more information, visit Prof. Jonathan Li's research group website.

Key Areas of Graduate Supervision

Urban remote sensing using images acquired by multispectral, hyperspectral, and SAR sensors and point clouds acquired by LiDAR and photogrammetry; machine learning and deep learning algorithms and software tools for extraction of geometric and semantic information from images and point clouds; applied research in geospatial data science for environmental monitoring, infrastructure inspection, green space inventory, and disaster management.

Recent Courses Taught

  • GEOG 215: China: Diverse and Dynamic
  • GEOG 310: Geodesy and Surveying
  • GEOG 316: Multivariate Statistics
  • GEOG 484 Machine Learning in Geospatial Science
  • GEOG 608: Urban Remote Sensing

Research Interests

Dr. Li’s research interests lie mainly in the areas of remote sensing and geospatial data science. The focus is placed on use of the-state-of-art Earth observation and mobile mapping systems to derive spatial and attribute information to support effective urban-suburban planning and environmental management activities; to extract geometric information of urban structures for developing theories and models of urban morphology; to detect land use and land cover changes to study spatiotemporal dynamics and consequences of urbanization as a major form of global changes.

Dr. Li’s recent research projects are about the development of innovative methods and software tools, including geospatial artificial intelligence (GeoAI) for multi-scale geospatial mapping and change detection, LiDAR point cloud processing for 3D urban modeling, mobile mapping solutions for outdoor and indoor mapping and 3D object detection, machine learning for intelligent processing of earth observation data, as well as novel remote sensing applications in transportation, utility, agriculture, resources and disaster management.

Selected Recent Publications (see Google Scholar for updated list)

1. LiDAR remote sensing and point cloud analytics

  • Tan W, Qin N, Zhang Y, McGrath H, Fortin M, *Li J, 2024. A rapid high-resolution multi-sensory urban flood mapping framework via DEM upscaling, Remote Sensing of Environment, 301, 113956.
  • Qin N, Tan W, Guan H, Wang L, Fatholahi SN, *Hu X, *Li J, 2023. Towards intelligent ground filtering of large-scale topographic point clouds: A comprehensive survey, International Journal of Applied Earth Observation and Geoinformation, 125, 103566.
  • Qin N, Tan W, Ma L, Zhang D, *Guan H, *Li J, 2023. Deep learning for filtering the ground from ALS point clouds: A dataset, evaluations and issues, ISPRS Journal of Photogrammetry and Remote Sensing, 202, 246-261.
  • Luo Z, Xiang H, *Li J, 2023. Road object detection for HD maps: Full-element survey, analysis, and perspectives, ISPRS Journal of Photogrammetry and Remote Sensing, 197, 122-144.
  • Sun W, Luo Z, *Chen Y, Marcato Jr J, Gonçalves W, *Li J, 2023. A click-based interactive segmentation network for point clouds, IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2023.3323735.
  • Lu D, Xie Q, Gao K, *Xu L, *Li J, 2022. 3DCTN: 3D convolution-transformer network for point cloud classification, IEEE Transactions on Intelligent Transportation Systems, 23(12), 24854–24865.
  • Feng H, *Chen Y, Luo Z, Sun W, Li W, *Li J, 2022. Automated extraction of building instances from dual-channel airborne LiDAR point clouds, International Journal of Applied Earth Observation and Geoinformation, 114, 103042.
  • Ma L, *Li J, 2022. SD-GCN: Saliency-based dilated graph convolution network for pavement crack extraction from 3D point clouds, International Journal of Applied Earth Observation and Geoinformation,112, 102836.
  • Ma L, *Li J, Li Y, Marcato Jr J, Gonçalves WN, Chapman MA, 2022. BoundaryNet: Extraction and completion of road boundaries with deep learning using mobile laser scanning point clouds and satellite imagery, IEEE Transactions on Intelligent Transportation Systems, 23(6), 5638-5654.
  • Ye C, Zhao H, Ma L, Jiang H, Li H, Wang R, Chapman M, Marcato Jr J, *Li J, 2022. Robust lane extraction from MLS point clouds towards HD maps especially in curved roads, IEEE Transactions on Intelligent Transportation Systems, 23(2), 1505-1518.
  • Gao J, *Chen Y, Marcato Jr J, Wang C, *Li J, 2022. Rapid extraction of urban road guardrails from mobile LiDAR Point Clouds, IEEE Transactions on Intelligent Transportation Systems, 23(2), 1572-1577.
  • Feng H, Li W, Luo Z, *Chen Y, Fatholahi SN, Cheng M, Wang C, Marcato Jr J, *Li J, 2022. GCN-based pavement crack detection using mobile LiDAR point clouds, IEEE Transactions on Intelligent Transportation Systems, 23(8), 11052-11061.
  • Luo Z, Zhang Z, Li W, *Chen Y, Wang C, Nurunnabi, A, *Li J, 2021. Detection of individual trees in UAV LiDAR point clouds using a deep learning framework based on multi-channel representation, IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2021.3130725.
  • Li W, Luo Z, *Xiao Z, Chen Y, Wang, C, *Li J, 2021. A GCN-based method for extracting power lines and pylons from airborne LiDAR data, IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2021.3076107.
  • Ma L, Li Y, *Li J, Yu Y, Marcato Jr J, Goncalves W, Chapman MA, 2021. Capsule-based networks for road marking extraction and classification from mobile LiDAR point clouds, IEEE Transactions on Intelligent Transportation Systems, 22(4),1981-1995.
  • Gong Z, Lin H, *Li J, Luo Z, Wang C, Zelek J, 2021. Mapping and semantic modeling of underground parking lots using a backpack LiDAR system, IEEE Transactions on Intelligent Transportation Systems, 22(2), 734-746.
  • Li Y, Ma L, Cao D, Chapman M, *Li J, 2021. Deep learning for LiDAR point clouds in autonomous driving: A review, IEEE Transactions on Neural Networks and Learning Systems, doi:10.1109/TNNLS.2020.3015992.
  • Ma L, Li Y, *Li J, Tan W, Yu Y, Chapman M, 2021. Multi-scale point-wise convolutional neural networks for 3D object segmentation from LiDAR point clouds in large-scale urban environments, IEEE Transactions on Intelligent Transportation Systems, doi:10.1109/TITS.2019.2961060.
  • Lin H, Wu S, *Chen Y, Li W, Luo Z, Guo Y, Wang C, *Li J, 2021. Semantic segmentation of 3D indoor LiDAR point clouds through feature pyramid architecture search, ISPRS Journal of Photogrammetry and Remote Sensing,177, 279-290.
  • Luo Z, Liu D, *Li J, Chen Y, Xiao Z, Wang C, Marcato Jr J, Gonçalves, WN, 2020. Learning sequential slice representation with an attention-embedding network for 3D shape analysis in MLS point clouds, ISPRS Journal of Photogrammetry and Remote Sensing, 161, 147-163.
  • Ye C, *Li J, Jiang H, Zhao H, Ma L, Chapman M, 2020. Semi-automated generation of road transition lines using mobile laser scanning data, IEEE Transactions on Intelligent Transportation Systems, 21(5), 1877-1890.
  • Gong Z, Lin H, Zhang D, Luo Z, Zelek J, Chen Y, Wang C, *Li J, 2020. A frustum-based probabilistic framework for 3D object detection by fusion of LiDAR and camera, ISPRS Journal of Photogrammetry and Remote Sensing, 159, 90-100.
  • Li Y, Ma L, Zhong Z, Cao D, *Li J, 2020. TGNet: Geometric graph CNN on 3D point cloud segmentation, IEEE Transactions on Geoscience and Remote Sensing, 58(5), 3588-3600.
  • Ye C, *Li J, Jiang H, Zhao H, Ma L, Chapman M, 2020. Semi-automated generation of road transition lines using mobile laser scanning data, IEEE Transactions on Intelligent Transportation Systems, 21(5), 1877-1890.
  • Zhang Z, *Li J, Guo Y, Yang C, Wang C, 2020. 3D highway curve reconstruction from mobile laser scanning point clouds, IEEE Transactions on Intelligent Transportation Systems, 21(11), 4762-4772.
  • Li Y, Ma L, Tan W, Sun C, Cao D, *Li J, 2020. GRNet: Geometric relation network for 3D object detection from point clouds, ISPRS Journal of Photogrammetry and Remote Sensing, 165, 43-53.

2. Environmental monitoring using optical and SAR images

  • He H, Ma L, *Li J, 2024. HigherNet-DST: Higher resolution network with dynamic scale training for rooftop delineation, IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2024.3362601.
  • Xu H, He H, Zhang Y, Ma L, *Li J, 2023. A comparative study of loss functions for road segmentation in remotely sensed road datasets, International Journal of Applied Earth Observation and Geoinformation, 116, 103159.
  • Li L, *Han L, Liu M, Gao K, He H, Wang L, *Li J, 2023.Coarse-to-fine matching via cross fusion of satellite images, International Journal of Applied Earth Observation and Geoinformation, 125, 103574.
  • Li L, *Han L, Liu M, Gao K, He H, Wang L, *Li J, 2023. SAR-optical image matching with semantic position probability distribution, IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2023.3330856.
  • Liu X, *Chen Y, Wang C, Tan K, *Li J, 2023. A lightweight building instance extraction method based on adaptive optimization of mask contours, International Journal of Applied Earth Observation and Geoinformation, 122, 103420.
  • Xu H, He H, Zhang Y, *Ma L, *Li J, 2023. A comparative study of loss functions for road segmentation in remotely sensed road datasets, International Journal of Applied Earth Observation and Geoinformation, 116, 103159.
  • He H, Xu H, Zhang Y, Gao K, Li H, Ma L, *Li J, 2022. Mask R-CNN based automated identification and extraction of oil well sites, International Journal of Applied Earth Observation and Geoinformation, 112, 102875.
  • He H, Gao K, Tan W, Wang L, Chen N, *Ma L, *Li J, 2022. Super-resolving and composing building dataset using a momentum spatial-channel attention residual feature aggregation network, International Journal of Applied Earth Observation and Geoinformation, 111, 102826.
  • Yu Q, Liu W, Gonçalves WN, José Marcato Jr J, *Li J, 2021. Spatial resolution enhancement for large-scale land cover mapping via weakly supervised deep learning, Photogrammetric Engineering and Remote Sensing, 87(6), 405–412.
  • Chen N, *Sui L, Zhang B, He H, Gao K, Li Y, Marcato Jr J, *Li J, 2021. Fusion of hyperspectral-multispectral images joining spatial-spectral dual-dictionary and structured sparse low-rank representation, International Journal of Applied Earth Observation and Geoinformation, 104,102570.
  • Chen N, *Sui L, Zhang B, He H, Marcato Jr J, *Li J, 2021. Single image super-resolution reconstruction based on Bayesian nonparametric and nonlocally self-similar convolution sparse coding, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi:101109/JSTARS.2020.3028774.
  • Zhong Z, *Li J, Clausi D, Wong A, 2020. Generative adversarial networks and conditional random fields for hyperspectral image classification, IEEE Transactions on Cybernetics, 50(7), 3318-3329.
  • Chen F, Fan Q, Lou S, Yang L, Wang C, Claverie M, Wang C, Marcato Jr J, Gonçalves WN, *Li, J, 2020. Characterization of MSS channel reflectance and derived spectral indices for building consistent Landsat 1-5 data record, IEEE Transactions on Geoscience and Remote Sensing, 58(12), 8967-8984.
  • Liu M, *Saari R, Zhou G, Liu X, *Li J, 2020. Size-differentiated patterns of exposure to submicron particulate matter across regions and seasons in China, Atmospheric Environment, 238, 117745.
  • Cai Y, He H, Yang K, Fatholahi SN, Ma L, Xu L, *Li J, 2021. A comparative study of deep learning approaches to rooftop detection in aerial images, Canadian Journal of Remote Sensing, 47(3), 413-431.
  • He H, Yang K, Wang S, Petrosians HA, Liu M, Marcato Jr J, Li J, Gonçalves WN, *Li J, 2021. Deep learning approaches to spatial downscaling of GRACE terrestrial water storage using EALCO model over Canada, Canadian Journal of Remote Sensing, 47(4), 657-675.