Chen Xiao
Fung Tze Kwan

Chen Xiao

Academic Qualifications

M.Sc in Surveying and Mapping Engineering, Southwest Jiaotong University

Research areas

LiDAR, Forest remote sensing, spatial analysis

Research interests

Chen’ research focuses on vegetation remote sensing of forest carbon and biodiversity. He is interested in using full waveform LiDAR data to map and monitor the structure and function changes of terrestrial ecosystems.


Chen’s research is centered at remote sensing, with a focus on the use of LiDAR for mapping and monitoring object. He was responsible for many LiDAR related engineering projects during his master years in China. He is familiar with LiDAR technology and has a lot of LiDAR data processing experience. He now is interested in vegetation remote sensing of forest carbon and biodiversity, with using LiDAR remote sensing technology for a baseline assessment of terrestrial ecosystem structure and function. He now joins the Centre for Nature-based Climate Solutions in hopes that his research will helps advance the capacity of using spatiotemporal data in monitoring forest structure dynamics to discover and demonstrate ecological and biodiversity hypothesis.

Selected publications

  1. Chen, X., Liu, G., Chen, Z., Li, Y., Luo, C., Luo, B., & Zhang, X. (2022). Automatic detection system with 3D scanning and robot technology for detecting surface dimension of the track slabs. Automation in Construction, 142, 104525.
  2. Fu, R., Chen, R., Wang, C., Chen, X., Gu, H., Wang, C., ... & Yin, G. (2022). Generating High-Resolution and Long-Term SPEI Dataset over Southwest China through Downscaling EEAD Product by Machine Learning. Remote Sensing, 14(7), 1662.
  3. Chen, X., Chen, Z., Liu, G., Chen, K., Wang, L., Xiang, W., & Zhang, R. (2021). Railway Overhead Contact System Point Cloud Classification. Sensors, 21(15), 4961.
  4. Chen, X., (2021). Research on Classification and Extraction of Railway Cross-Section Contour and Catenary Based on Vehicle LiDAR Laser Point Cloud Data[D]. Southwest Jiaotong University, DOI:10.27414/d.cnki.gxnju.2020.001622.
  5. Chen, X., Qin, F., Xia, C., Bao, J., Huang, Y., & Zhang, X. (2019). An Innovative Detection Method of High-Speed Railway Track Slab Supporting Block Plane Based on Point Cloud Data from 3D Scanning Technology. Applied Sciences, 9(16), 3345.

Feature and publications in popular media

  1. Kwan, J. (2019). Protecting endangered wildlife in Singapore. The Straits Times, Singapore. 7 Sep 2019, Science.
  2. Wildlife Reserves Singapore (2019). Twin interests deliver double. In Wildlife Matters: 10 Years of Conservation in Singapore. Epigram, pp. 30-35.
  3. The Straits Times. (2017). The shy creatures of wild Singapore. The Straits Times, Singapore. 6 Mar 2017, Home.
  4. Khew, C. (2015). Civets on Ubin get GPS collars. The Straits Times, Singapore. 23 Jan 2015, Home, pB19.

 Conference and presentations

  1. “Classification and Extraction of Railway Overhead Contact System Based on LiDAR Point Cloud”, 2020, The Sixth China LiDAR Conference