Picture of Yu Feng

Dr.-Ing. Yu Feng

Postal address

Arcisstr. 21
80333 München


  • Image Analysis for Mapping (winter semester - Cartography M.Sc.)
  • Seminar Cartography (winter semester - Geodesy and Geoinformation M.Sc.)

Research Interest

  • Volunteered Geographic Information (VGI) - social media for disaster monitoring
  • Cartographic Generalization with deep learning methods
  • Mobile Laser Scanning (MLS) - terrain and building modelling

Project fundings

NFDI4Earth Educational Pilots
  • An open-access and interactive coding platform to facilitate e-learning in Geospatial Data Analysis (Coding4Geo), DFG funded NFDI4Earth. (PI, 2022-2023)
ISPRS scientific initiatives
  • BeBaOI: Benchmark and Baseline Methods for Determining Overlapping Images, International Society for Photogrammetry and Remote Sensing (ISPRS), (2nd PI, 2023-2024).
TUM Global Incentive Fund
  • Knowledge discovery and visual analysis for urban mobility data in Munich and Helsinki, TUM lobal & Alumni Office, (2nd PI, 2023-2024).

Selected publications

Full publication list please refer to Google scholar.
  1. Yu Feng*, Xiao Huang & Monika Sester. Extraction and analysis of natural disaster-related VGI from social media: review, opportunities and challenges. International Journal of Geographical Information Science, 2022.
  2. Yu Feng*, Qing Xiao, Claus Brenner, Aaron Peche, Juntao Yang, Udo Feuerhake & Monika Sester. Deter mination of building flood risk maps from lidar mobile mapping data. Computers, Environment and Urban Systems, 2022.
  3. Yu Feng*, Claus Brenner & Monika Sester. Flood severity mapping from volunteered geographic information by interpreting water level from images containing people: A case study of Hurricane Harvey. ISPRS Journal of Photogrammetry and Remote Sensing, 2020. (featured article of issue Nov. 2020).
  4. Yu Feng*, Frank Thiemann & Monika Sester. Learning cartographic building generalization with deep convolutional neural networks. ISPRS International Journal of Geo-Information, 2019.
  5. Yu Feng* & Monika Sester. Extraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos. ISPRS International Journal of Geo-Information, 2018.



  • Hou, Qianbao; Xia, Rui; Zhang, Jiahuan; Feng, Yu; Zhan, Zongqian; Wang, Xin: Learning visual overlapping image pairs for SfM via CNN fine-tuning with photogrammetric geometry information. International Journal of Applied Earth Observation and Geoinformation 116, 2023, 103162 mehr… BibTeX Volltext ( DOI )
  • Zeng, Zhe; Liu, Sai; Cheng, Hao; Liu, Hailong; Li, Yang; Feng, Yu; Siebert, Felix: GaVe: A webcam-based gaze vending interface using one-point calibration. Journal of Eye Movement Research 16 (1), 2023 mehr… BibTeX Volltext ( DOI )