Zhu Mao (毛竹)

About Me

Postdoctoral Researcher in the Forest Technology Group, Department of Forest Sciences, University of Helsinki. My research focuses on forest precision harvesting, deep learning and artificial intelligence in forestry, photogrammetry and remote sensing, 3D modeling.

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Education

Publications

Estimation of carbon sequestration capacity of urban green infrastructure by fusing multi-source remote sensing data Chang, J., Shao, Z., Wang, J., Mao, Z., Cheng, T., Xu, X., & Zhuang, Q. (2025) - International Journal of Applied Earth Observation and Geoinformation. 141, 104643. DOI: 10.1016/j.jag.2025.104643

Paper

Super-resolution supporting individual tree detection and canopy stratification using half-meter aerial data Mao, Z., Abdi O., Uusitalo J., Laamanena V., & Kivinen V. (2025) - ISPRS Journal of Photogrammetry and Remote Sensing. DOI: 10.1016/j.isprsjprs.2025.04.005

Paper Github

Automating the consolidation of GNSS logging tracks and machine pass counting in boreal forests Cao, S., Abdi, O., Koivukoski, K., Mao, Z., & Uusitalo, J. (2025) - Smart Agricultural Technology. DOI: 10.1016/j.atech.2025.101038

Paper

Glass façade segmentation and repair for aerial photogrammetric 3D building models with multiple constraints Mao, Z., Gong, Y., Zhang, F., & Tang, J. (2023) - International Journal of Applied Earth Observation and Geoinformation. 118, 103242. DOI: 10.1016/j.jag.2023.103242

Paper

Oblique photogrammetry supporting procedural tree modeling in urban areas Wang, X., Xiang, H., Niu, W., Mao, Z., Huang, X., & Zhang, F. (2023) - ISPRS Journal of Photogrammetry and Remote Sensing. DOI: 10.1016/j.isprsjprs.2023.05.008

Paper Github

Improved instance segmentation for slender urban road facility extraction using oblique aerial images Mao, Z., Huang, X., Niu, W., Wang, X., Hou, Z., & Zhang, F. (2023) - International Journal of Applied Earth Observation and Geoinformation. DOI: 10.1016/j.jag.2023.103362

Paper

A dataset and ensemble model for glass façade segmentation in oblique aerial images Mao, Z., Huang, X., Gong, Y., Xiang, H., & Zhang, F. (2022) - IEEE Geoscience and Remote Sensing Letters. 19, 1-5. DOI: 10.1109/LGRS.2022.3187760

Paper Github

Deep neural networks for road sign detection and embedded modeling using oblique aerial images Mao, Z., Zhang, F., Huang, X., Jia, X., Gong, Y., & Zou, Q. (2021) - Remote Sensing. 13(5), 879. DOI: 10.3390/rs13050879

Paper Github

Research Projects

• GeoAI explained soil mapping of Finland (2025.5 – Now).
• Forest precision harvesting (2024.1 – 2025.6).
• Assembly-based 3D traffic facility detection and modeling (2022.9 – 2023.6).
• Yungang Grottoes restoration (2022.4 – 2022.8): Virtual restoration of Buddha statues.
• Vehicle detection and removal (2021.1 – 2021.4): Dynamic vehicle removal from 3D urban models.

Teaching

• Guest Lecturer in
• FOR-263: Operations Research in Forest Resource Management, Computer Vision in Forestry, University of Helsinki (2024, 2026)
• FOR-280: Precision Harvesting, University of Helsinki (2025)
• FOR-018: Introduction to MSc Programme in Forest Sciences, University of Helsinki (2025)

Presentations

• Deep-learning-based individual tree detection for tomorrow's precision harvesting operations — Formec 2025, Joensuu.
• Mapping tree-level structural diversity for precision harvesting operations: A comparison of open-source and drone datasets — Forest Science Day 2025, Helsinki.