Name
KANG, Jing
Degree
Ph.D.
HP (URL)
https://sites.google.com/view/giser/j-k
Status
Assistant Professor
Research Topic
Carbon neutral – Evaluation of the Nonlinear Effects of Land Use/Land Cover Changes on CO2 Emissions using Machine Learning –
Land use and land cover changes (LULCC) contribute to significant uncertainty in the global carbon budget, crucial for achieving carbon neutrality. This study explores the nonlinear relationship between net carbon exchange and LULCC, identifying CO2 uptake or emission thresholds. Leveraging satellite remote sensing and innovative geospatial machine learning, it aims to understand how land management can act as effective carbon sinks, informing resilient climate solutions.
Education and Academic Employment
Education
| 2006-2010 | Huazhong Agriculture University, Bachelor of Science, GIS |
| 2011-2017 | Beijing Normal University, Doctor of Science, Global Environment Change |
Academic Employment
| 2010-2011 | Beijing Normal University, Research Assistant |
| 2017-2019 | Tsinghua University, Postdoc Researcher |
| 2017-2019 | Director, Department of Information Science, National Engineering Laboratory for Traffic Safety and Emergency Response, CTTIC |
| 2019-2021 | University of Pennsylvania, Visiting Researcher, CM2 Project Research Fellow |
| 2021-2024 | Hiroshima University, Assistant Professor |
Fields of Research Interests
Climate change adaptation, Land Use policy and Carbon neutral, Satellite remote sensing, GIS, Machine Learning
Academic Publications
[Peer-reviewed papers]
- Kang, J.,* Zhang, B., Dang, A. A Novel Geospatial Machine Learning Approach to Quantify Non-Linear Effects of Land Use/Land Cover Change (LULCC) on Carbon Dynamics. International Journal of Applied Earth Observation and Geoinformation, 2024,128, 103712 (SCI, IF:7.5) https://doi.org/10.1016/j.jag.2024.103712
- Kang, J.,* Zhang, B., Zhang, J., and Dang, A. “Quantifying the Effects of Different Containment Policies on Urban NO2 Decline: Evidence from Remote Sensing Integrated with Ground-Station Data”. Remote Sensing, 2023, 15(4), 1068. (SCI, IF:5) https://doi.org/10.3390/rs15041068
- Kang, J.,* Kong, H., Lin, Z., and Dang, A. “Mapping the Dynamics of Electric Vehicle Charging Demand Within Beijing’s Spatial Structure”. Sustainable Cities and Society, 2022, 76, 103507. (SCI, IF: 11.8) https://doi.org/10.1016/j.scs.2021.103507
- Kang, J.,* Kan, C., and Lin, Z. “Are Electric Vehicles Reshaping the City? An Investigation of the Clustering of Electric Vehicle Owners’ Dwellings and Their Interaction with Urban Spaces”. ISPRS International Journal of Geo-Information, 2021, 10(5), 320. (SCI, IF:3.4) https://doi.org/10.3390/ijgi10050320
- Kang, J.,* Cheng, X., Hui, F., and Ci T. “An Accurate and Automated Method for Identifying and Mapping Exposed Rock Outcrop in Antarctica Using Landsat 8 Images”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 1(11), 57-67. (SCI, IF: 5.5, Front Cover) https://doi.org/10.1109/JSTARS.2017.2755502
- Kang, J.,* Dang, A., Zhang, B., Wang, Y., Su, H., Su, F., Ci, T., and Wang, F. “An Improved Convolutional Neural Network for Monocular Depth Estimation”. In Green, Smart and Connected Transportation Systems, 2020, Springer, 1229-1237. https://doi.org/10.1007/978-981-15-0644-4_94
- Kang, J.,* Ci, T., Dang, A., et.al. “An Automatic Method for Water Extraction from High Spatial Resolution GF-1 Imagery Based on a Deep Learning Algorithm”. In International Conference on Computer Intelligent Systems and Network Remote Control, 2019, 555-562 https://doi.org/10.12783/dtcse%2Fcisnrc2019%2F33358
- Kang, J.,* Cheng, X., Liu, Y., Hui, F., Ouyang, L., Li, Tian. “Shadow Detection Method of Landsat8 Satellite Imagery in Antarctic Region”. Journal of Beijing Normal University, 2017 https://doi.org/10.16360/j.cnki.jbnuns.2017.02.013
- Zhang, B., Kang, J.* “Quantitative Attribution Framework for Urban Air Pollutant: Insights of the Policies’ Impacts on NO2 Emissions from Megacities in China and Japan”. Sustainable Cities and Society. 2023, 104965. (SCI, IF: 11.8) https://doi.org/10.1016/j.scs.2023.104965
- Zhang, J., Feng, T., Kang, J.,* et al. “What Should Be Computed for Supporting Post-Pandemic Recovery Policymaking? A Life-Oriented Perspective”. Computational Urban Science, 2021, 1(1), 1-16. https://doi.org/10.1007/s43762-021-00025-8
- Ma, Q., Gong, Z., Kang, J.,* and Dang, A. “Measuring Functional Urban Shrinkage with Multi-Source Geospatial Big Data: A Case Study of The Beijing-Tianjin-Hebei Megaregion”. Remote Sensing, 2020, 12(16), 2513. (SCI, IF:5.5) https://doi.org/10.3390/rs12162513
- Hui F, Kang, J. *, Liu Y., Cheng, X., Gong, P., Wang, F., Li, Z., Ye, Y., and Guo, Z. “AntarcticaLC2000: The New Antarctic Land Cover Database for The Year 2000”. Science China Earth Sciences, 2017, 60(4), 686-696. (SCI, IF:5.492) https://doi.org/10.1007/s11430-016-0029-2
[Books]
- Kang, J.,* Zhang, M and Tanaka T. “Accessible Remote Sensing: Interdisciplinary Approach and Applications”, 2024, CRC Press | Taylor & Francis (Textbook).
- Hui F, Cheng X., Liu Y., Kang, J., * Li X. High-Resolution Remote Sensing Mapping of Antarctica, 2022, China Ocean Press.
Other Interests
Tea ceremony, Hiking, Zen
Affiliated Academic Organizations
IEEE Geosciences and Remote Sensing
American Geophysical Union (AGU)
European Geosciences Union (EGU)
American Association of Geographers (AAG)
Japan Society of Civil and Environmental Planning
Awards
2018 First Prize of China High-Resolution Remote Sensing Application Solution Competition
2014 CSC National Scholarship, National Oceanography Centre UK and Beijing Normal University
2008 Second Prize of National Undergraduate Mathematical Modeling Contest, China
