Basic personal information

        Jing Liu, female, Associate Professor, Master's Degree Supervisor, Doctor of Double Creation of Jiangsu Province. She is a member of Lidar Committee of International Society for Digital Earth, Resource Mapping Committee of Chinese Society for Natural Resources, Women Science and Technology Workers Working Committee of Chinese Association of Remote Sensing Application, Remote Sensing and Environment Committee of Suzhou, Hong Kong and Macao Universities, and Youth Editorial Board member of Plant Phenomics Journal.Remote Sensing of Environment, ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, Agricultural Science and Technology. She is a reviewer for ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, Agricultural and Forest Meteorology, etc.

Research direction

(1) Lidar remote sensing: R&D and application of algorithms applying multi-scale (ground-based, airborne and satellite-based) Lidar for earth observation, such as forest resources survey, topographic mapping, urban land cover classification, etc.

(2) Remote sensing of vegetation: quantitative inversion of forest structural parameters based on multi-source remote sensing technology, virtual forest environment modeling, and its application in forestry resource management and terrestrial ecosystem carbon cycle.

(3) Intelligent processing of point cloud: R&D of algorithms for point cloud feature extraction, segmentation and classification, and three-dimensional modeling.

We welcome students with remote sensing, mapping or GIS background who are interested in scientific research to apply for master's and doctoral degree in our team.

Specialties: Cartography and GIS, Surveying and Mapping Science and Technology, Remote Sensing of Geographic Environment, Master of Resource and Environmental Engineering.

Work experience

• 2020.07-present, Nanjing Normal University, School of Geographical Sciences, Associate Professor
• 2019.09~2020.07, Nanjing Normal University, School of Geographical Sciences, Lecturer

Educational experience

• 2014.09~2019.05, ITC, Natural Resources, Ph.D.
• 2015.09~2019.05, School of Science, RMIT University, Australia, Geospace Science, Ph.D.
• 2011.09~2014.06, School of Earth and Space Sciences, Peking University, Photogrammetry and Remote Sensing, Master of Engineering
• 2007.09~2011.06, School of Geography and Marine Sciences, Nanjing University, Geographic Information System, Bachelor of Science

Honors and Awards

• 1) 2023, Young Teacher Lecture Competition of Teaching Innovation and Nurturing Ability in Surveying and Mapping Disciplines in National Colleges and Universities, Grand Prize
• 2) 2023, The Seventh National Lidar Conference Data Processing Competition, Grand Prize (Instructor)
• 3) 2020, The Ninth National College Students' GIS Application Skills Competition, Grand Prize (Instructor)
• 4) 2024, Innovation Development Competition of the National College Students' Innovation and Entrepreneurship Intelligence Competition in Surveying and Mapping Disciplines, Second Prize (Instructor)
• 5) 2023, Nanjing Normal University Graduate Student Science and Technology Cultural Activities, Excellent Instructor

Major scientific research projects undertaken (participated in)

• (1) National Natural Science Foundation of China (NSFC), top-level project, Vertical distribution inversion of forest leaf area by joint on-board full-waveform and photon-counting LiDAR, 2025.01-2028.12, under research, presided by
• (2) Jiangsu Provincial Basic Research Program, Top-level Project, Remote Sensing Monitoring of Total Primary Productivity of Terrestrial Ecosystems by Integrating Lidar and Hyperspectral Data, 2024.07-2027.06, under research, presided over.
• (3) National Natural Science Foundation of China, Young Science Foundation Program, Vertical Distribution Detection of Leaf Area Index (LAI) Taking into Account the Heterogeneity of Internal Structure and External Contour of Forest Canopy, 2021.01-2023.12, completed, presided over.
• (4) Jiangsu Provincial Basic Research Program, Young Science Foundation Project, Detection of three-dimensional distribution of vegetation in the Yangtze River Delta region based on multi-source remote sensing data, 2020.07 to 2023.06, completed, presided over.
• 5）Nanjing Normal University, Scientific Research Initiation Program for Introduced Talents, Research on Ground Measurement Methods of Forest Leaf Area Index Based on Ground-Based LiDAR, 2019.10 to 2022.10, completed, presided over
• (6) National Natural Science Foundation of China, NSFC-Xinjiang Joint Fund Key Project, Research on Synergy and Optimization of Ecosystem Water Consumption, Socio-economic Water Use and Water Resources in the Tarim River Basin, from 2021.01 to 2024.12, under research and participation.
• (7) Excellent Science and Technology Innovation Team of Jiangsu Universities, Coupled Modeling and Sustainability Assessment of Human-Earth Systems, 2021.09 to 2024.12, under research, participation
• (8) National Natural Science Foundation of China, top-level project, change detection based on the fusion of category multi-point spatio-temporal transition probability and decision-making, 2014.01 to 2017.12, finalized, participation

Journal papers published in the past five years (*corresponding author)

• Wang, Z., Liu, J.*, Sheng, Y., et al. 2024. Intercomparison of the DART model and GEDI simulator for simulating GEDI waveforms in forests. International Journal of Applied Earth Observation and Geoinformation 134, 104148
• He, Z.,  Liu, J.*, Yang, S. 2024. DE-Net: A Dual-Encoder Network for Local and Long-Distance Context Information Extraction in Semantic Segmentation of Large-Scale Scene Point Clouds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 15914-15926. 
• Wang Z., Chen H.*, Liu J.*, et al. Multilevel intuitive attention neural network for airborne LiDAR point cloud semantic segmentation. International Journal of Applied Earth Observation and Geoinformation, 2024; 132:104020.   
• Han D., Liu J.*, Zhang R., et al. Evaluation of the SAIL Radiative Transfer Model for Simulating Canopy Reflectance of Row Crop Canopies. Remote Sensing. 2023; 15(23):5433. https://doi.org/10.3390/rs15235433
• Wang J., Liu J.*, Li L. Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data. Remote Sensing. 2022; 14(24):6296. https://doi.org/10.3390/rs14246296
• Lei Qiujia, Liu Jing*, Cao Xinyun. Accuracy Assessment of Open DEM Products Using Airborne LiDAR Data. Journal of Wuhan University (Information Science Edition). https://doi.org/10.13203/j.whugis20220421
• Liu, J.*, Li, L., Akerblom, M., Wang, T., Skidmore, A., Zhu, X., & Heurich, M. 2021. Comparative Evaluation of Algorithms for Leaf Area Index Estimation from Digital Hemispherical Photography through Virtual Forests. Remote Sensing, 2021, 13(16), 3325
• Liu, J.*, Wang, T., Skidmore, A.K., Jones, S., Heurich, M., Beudert, B., Premier, J., 2019. Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests, ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 158: 76-89.
• Liu, J.*, Skidmore, A.K., Wang, T., Zhu, X., Premier, J., Heurich, M., Beudert, B., Jones, S., 2019. Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest. ISPRS Journal of Photogrammetry and Remote Sensing, 148, 208-220.
• Liu, J.*, Skidmore, A.K., Jones, S., Wang, T., Heurich, M., Zhu, X., Shi, Y., 2018. Large off-nadir scan angle of airborne LiDAR can severely affect the estimates of forest structure metrics. ISPRS Journal of Photogrammetry and Remote Sensing, 136, 13-25.
• Liu, J.*, Skidmore, A.K., Heurich, M., Wang, T.*, 2017. Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests. ISPRS Journal of Photogrammetry and Remote Sensing, 132, 77-87.
• Liu, J., Li, P.*, Wang, X., 2015.A new segmentation method for very high resolution imagery using spectral and morphological information. ISPRS Journal of Photogrammetry and Remote Sensing, 101, 145-162.
• Yang, P.*, van der Tol, C., Liu, J., & Liu, Z. 2025. Separation of the direct reflection of soil from canopy spectral reflectance. Remote Sensing of Environment, 316, 114500 https://doi.org/10.1016/j.rse.2024.114500
• Zhu, X.*, Liu, J., Skidmore, A.K., Premier, J., Heurich, M., 2020. A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data. Remote Sensing of Environment, 240, 111696.
• Wang, D., Wan, B.*,Liu, J., Su, Y., Guo, Q., Qiu, P., Wu, X., 2020. Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery. International Journal of Applied Earth Observation and Geoinformation, 85, 101986.
• Zhu, X.*, Skidmore, A.K., Wang, T., Liu, J., Darvishzadeh, R., Shi, Y., Premier, J., Heurich, M., 2018. Improving leaf area index (LAI) estimation by correcting for clumping and woody effects using terrestrial laser scanning. Agricultural and Forest Meteorology, 263, 276-286.
• Zhu, X., Skidmore, A.K., Darvishzadeh., R., Niemann, K., Liu, J., Shi, Y., Wang, T., 2018. Foliar and woody materials discriminated using terrestrial LiDAR in a mixed natural forest. International Journal of Applied Earth Observation and Geoinformation, 64, 43-50.
• Zhu, X., Wang, T., Skidmore, A.K., Darvishzadeh., R., Niemann, K., Liu, J., 2017. Canopy leaf water content estimated using terrestrial LiDAR. Agricultural and Forest Meteorology, 232, 152-162.