Dr. Hao Li

E-Mail:	hao_bgd.li@tum.de
Telefon:	(+49) 89 289 555 54
Raum:	103
Anschrift:	Technische Universität München Dr. Hao Li Lise-Meitner-Str. 9 85521 Ottobrunn

Full publications and CV

Publications at the Professorship

Liu, Z., Fang, C., Li, H., Wu, J., Zhou, L., & Werner, M. (2024). Efficiency and equality of the multimodal travel between public transit and bike-sharing accounting for multiscale. Sustainable Cities and Society, 101, 105096. https://doi.org/https://doi.org/10.1016/j.scs.2023.105096 [PDF] [Online] [BibTeX]
```
@article{2023_bikeEfficiency_Zhihang,
  title = {Efficiency and equality of the multimodal travel between public transit and bike-sharing accounting for multiscale},
  journal = {Sustainable Cities and Society},
  volume = {101},
  pages = {105096},
  year = {2024},
  issn = {2210-6707},
  doi = {https://doi.org/10.1016/j.scs.2023.105096},
  url = {https://www.sciencedirect.com/science/article/pii/S2210670723007060},
  author = {Liu, Zhihang and Fang, Chenyu and Li, Hao and Wu, Jinlin and Zhou, Lin and Werner, Martin}
}
```

Luo, X., Walther, P., Mansour, W., Teuscher, B., Zollner, J. M., Li, H., & Werner, M. (2023). Exploring GeoAI Methods for Supraglacial Lake Mapping on Greenland Ice Sheet. The 31st ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’23), November 13–16, 2023, Hamburg, Germany. https://doi.org/10.1145/3589132.3629971 [PDF] [Online] [BibTeX]

@inproceedings{2023_giscup_Luo,
  author = {Luo, Xuanshu and Walther, Paul and Mansour, Wejdene and Teuscher, Balthasar and Zollner, Johann Maximilian and Li, Hao and Werner, Martin},
  title = {Exploring GeoAI Methods for Supraglacial Lake Mapping on Greenland Ice Sheet},
  year = {2023},
  isbn = {979-8-4007-0168-9/23/11},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3589132.3629971},
  doi = {10.1145/3589132.3629971},
  booktitle = {The 31st ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL '23), November 13--16, 2023, Hamburg, Germany},
  numpages = {4},
  keywords = {supraglacial lakes, image segmentation, satellite imagery, computer vision, mask R-CNN, segment anything model},
  location = {Hamburg, Germany},
  series = {SIGSPATIAL '23}
}

Hong, D., Zhang, B., Li, H., Li, Y., Yao, J., Li, C., Werner, M., Chanussot, J., Zipf, A., & Zhu, X. X. (2023). Cross-city matters: A multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks. Remote Sensing of Environment, 299, 113856. https://doi.org/https://doi.org/10.1016/j.rse.2023.113856 [Online] [BibTeX]

@article{2023_crosscity,
  title = {Cross-city matters: A multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks},
  journal = {Remote Sensing of Environment},
  volume = {299},
  pages = {113856},
  year = {2023},
  issn = {0034-4257},
  doi = {https://doi.org/10.1016/j.rse.2023.113856},
  url = {https://www.sciencedirect.com/science/article/pii/S0034425723004078},
  author = {Hong, Danfeng and Zhang, Bing and Li, Hao and Li, Yuxuan and Yao, Jing and Li, Chenyu and Werner, Martin and Chanussot, Jocelyn and Zipf, Alexander and Zhu, Xiao Xiang}
}

Li, H., Wang, J., Zollner, J. M., Mai, G., Lao, N., & Werner., M. (2023). Rethink Geographical Generalizability with Unsupervised Self-Attention Model Ensemble: A Case Study of OpenStreetMap Missing Building Detection in Africa. Proceedings of the 31st International Conference on Advances in Geographic Information Systems. https://doi.org/10.1145/3589132.3625598 [PDF] [Online] [BibTeX]

@inproceedings{2023_GWME_Hao,
  author = {Li, Hao and Wang, Jiapan and Zollner, Johann Maximilian and Mai, Gengchen and Lao, Ni and Werner., Martin},
  title = {Rethink Geographical Generalizability with Unsupervised Self-Attention Model Ensemble: A Case Study of OpenStreetMap Missing Building Detection in Africa},
  year = {2023},
  isbn = {979-8-4007-0168-9/23/11},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3589132.3625598},
  doi = {10.1145/3589132.3625598},
  booktitle = {Proceedings of the 31st International Conference on Advances in Geographic Information Systems},
  numpages = {9},
  keywords = {GeoAI, OpenStreetMap, Vision Transformer, Model Ensemble, Humanitarian Mapping, Self-Attention},
  location = {Hamburg, Germany},
  series = {SIGSPATIAL '23}
}

Werner, M., Li, H., Zollner, J. M., Teuscher, B., & Deuser., F. (2023). Bavaria Buildings - A Novel Dataset for Building Footprint Extraction, Instance Segmentation, and Data Quality Estimation (Data and Resources Paper). Proceedings of the 31st International Conference on Advances in Geographic Information Systems (ACM SIGSPATAIL GIS’23). https://doi.org/10.1145/3589132.3625658 [PDF] [Online] [BibTeX]
```
@inproceedings{2023_BBD_Martin,
  author = {Werner, Martin and Li, Hao and Zollner, Johann Maximilian and Teuscher, Balthasar and Deuser., Fabian},
  title = {Bavaria Buildings - A Novel Dataset for Building Footprint Extraction, Instance Segmentation, and Data Quality Estimation (Data and Resources Paper)},
  year = {2023},
  url = {https://doi.org/10.1145/3589132.3625658},
  doi = {10.1145/3589132.3625658},
  booktitle = {Proceedings of the 31st International Conference on Advances in Geographic Information Systems (ACM SIGSPATAIL GIS'23)}
}
```
Liu, Z., Wu, J., Li, H., & Werner, M. (2023). Spatio-temporal Analysis of Urban Economic Resilience during Covid-19 with Multilayer Complex Networks. The ISPRS Geospatial Week 2023, GeoHB Workshop. [PDF] [BibTeX]
```
@article{2023_multilayer_Zhihang,
  author = {Liu, Zhihang and Wu, Jinlin and Li, Hao and Werner, Martin},
  title = {Spatio-temporal Analysis of Urban Economic Resilience during Covid-19 with Multilayer Complex Networks},
  journal = {the ISPRS Geospatial Week 2023, GeoHB workshop},
  year = {2023}
}
```

Li, H., Yuan, Z., Dax, G., Kong, G., Fan, H., Zipf, A., & Werner, M. (2023). Semi-Supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation. In R. Beecham, J. A. Long, D. Smith, Q. Zhao, & S. Wise (Eds.), 12th International Conference on Geographic Information Science (GIScience 2023) (Vol. 277, pp. 7:1–7:15). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.GIScience.2023.7 [PDF] [Online] [BibTeX]

@inproceedings{2023_semisupervised_Hao,
  author = {Li, Hao and Yuan, Zhendong and Dax, Gabriel and Kong, Gefei and Fan, Hongchao and Zipf, Alexander and Werner, Martin},
  title = {{Semi-Supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation}},
  booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)},
  pages = {7:1--7:15},
  series = {Leibniz International Proceedings in Informatics (LIPIcs)},
  isbn = {978-3-95977-288-4},
  issn = {1868-8969},
  year = {2023},
  volume = {277},
  editor = {Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address = {Dagstuhl, Germany},
  url = {https://drops.dagstuhl.de/opus/volltexte/2023/18902},
  urn = {urn:nbn:de:0030-drops-189028},
  doi = {10.4230/LIPIcs.GIScience.2023.7},
  annote = {Keywords: OpenStreetMap, Street-view Images, VGI, GeoAI, 3D city model, Facade parsing}
}

Teuscher, B., Geißendörfer, O., Luo, X., Li, H., Anders, K., Holst, C., & Werner, M. (2024). Efficient In-Memory Point Cloud Query Processing. In T. H. Kolbe, A. Donaubauer, & C. Beil (Eds.), Recent Advances in 3D Geoinformation Science (pp. 267–286). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43699-4_16 [PDF] [Online] [BibTeX]

@incollection{2023_pointcloudqueries_Teuscher,
  title = {Efficient In-Memory Point Cloud Query Processing},
  isbn = {978-3-031-43698-7 978-3-031-43699-4},
  url = {https://link.springer.com/10.1007/978-3-031-43699-4_16},
  pages = {267--286},
  booktitle = {Recent Advances in 3D Geoinformation Science},
  publisher = {Springer Nature Switzerland},
  author = {Teuscher, Balthasar and Geißendörfer, Oliver and Luo, Xuanshu and Li, Hao and Anders, Katharina and Holst, Christoph and Werner, Martin},
  editor = {Kolbe, Thomas H. and Donaubauer, Andreas and Beil, Christof},
  urldate = {2024-02-27},
  year = {2024},
  doi = {10.1007/978-3-031-43699-4_16},
  note = {Series Title: Lecture Notes in Geoinformation and Cartography}
}

Xiong, Z., Stober, D., Krstić, M., Korup, O., Arango, M. I., Li, H., & Werner, M. (2023). Integrating AI Hardware in Academic Teaching: Experiences and Scope from Brandenburg and Bavaria. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. [BibTeX]
```
@article{2022_IGCE_AcademicTeaching_BBKI_Xiong,
  title = {Integrating AI Hardware in Academic Teaching: Experiences and Scope from Brandenburg and Bavaria},
  project = {bbki},
  author = {Xiong, Zhouyi and Stober, Dirk and Krstić, Miloš and Korup, Oliver and Arango, Maria Isabel and Li, Hao and Werner, Martin},
  journal = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
  year = {2023}
}
```
Knoblauch, S., Li, H., Lautenbach, S., Elshiaty, Y., Rocha, A. A. de A., Resch, B., Arifi, D., Jänisch, T., Morales, I., & Zipf, A. (2023). Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti. International Journal of Applied Earth Observation and Geoinformation, 119, 103304. https://doi.org/10.1016/j.jag.2023.103304 [PDF] [Online] [BibTeX]
```
@article{2022_Geoepi_watertank_Hao,
  title = {Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti},
  author = {Knoblauch, Steffen and Li, Hao and Lautenbach, Sven and Elshiaty, Yara and Rocha, Ant{\^o}nio A de A and Resch, Bernd and Arifi, Dorian and J{\"a}nisch, Thomas and Morales, Ivonne and Zipf, Alexander},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  url = {https://doi.org/10.1016/j.jag.2023.103304},
  volume = {119},
  pages = {103304},
  year = {2023},
  publisher = {Elsevier}
}
```
Dax, G., Nagarajan, S., Li, H., & Werner, M. (2022). Compression Supports Spatial Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS). https://doi.org/10.1109/JSTARS.2022.3226563 [Online] [BibTeX]
```
@article{2022_CompInDL_Dax,
  title = {Compression Supports Spatial Deep Learning},
  journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS)},
  author = {Dax, Gabriel and Nagarajan, Srilakshmi and Li, Hao and Werner, Martin},
  url = {https://doi.org/10.1109/JSTARS.2022.3226563},
  year = {2022},
  project = {mlab}
}
```
Grinberger, A. Y., Liu, P., Li, H., Juhasz, L., & Minghini, M. (2022). OpenStreetMap, beyond just Data: The Academic Track at State of the Map 2022. Zenodo. https://doi.org/10.5281/zenodo.7004424 [Online] [BibTeX]
```
@proceedings{grinberger_a_yair_2022_7004424,
  author = {Grinberger, A Yair and Liu, Pengyuan and Li, Hao and Juhasz, Levente and Minghini, Marco},
  title = {{OpenStreetMap, beyond just Data: The Academic
                     Track at State of the Map 2022}},
  year = {2022},
  publisher = {Zenodo},
  month = aug,
  doi = {10.5281/zenodo.7004424},
  url = {https://doi.org/10.5281/zenodo.7004424}
}
```

Werner, M., & Li, H. (2022). AtlasHDF: An Efficient Big Data Framework for GeoAI. 1–7. https://doi.org/10.1145/3557917.3567615 [PDF] [Online] [BibTeX]

@inproceedings{2022_atlashdf_Werner,
  author = {Werner, Martin and Li, Hao},
  title = {AtlasHDF: An Efficient Big Data Framework for GeoAI},
  year = {2022},
  isbn = {9781450395311},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3557917.3567615},
  doi = {10.1145/3557917.3567615},
  pages = {1–7},
  numpages = {7},
  keywords = {GeoAI, OpenStreetMap, big data, hierarchical data format, immediate mapping},
  location = {Seattle, Washington},
  series = {BigSpatial '22}
}

Hu, X., Zhou, Z., Li, H., Hu, Y., Gu, F., Kersten, J., Fan, H., & Klan, F. (2023). Location Reference Recognition from Texts: A Survey and Comparison. ACM Comput. Surv. https://doi.org/10.1145/3625819 [Online] [BibTeX]

@article{hu2022location,
  author = {Hu, Xuke and Zhou, Zhiyong and Li, Hao and Hu, Yingjie and Gu, Fuqiang and Kersten, Jens and Fan, Hongchao and Klan, Friederike},
  title = {Location Reference Recognition from Texts: A Survey and Comparison},
  year = {2023},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  issn = {0360-0300},
  url = {https://doi.org/10.1145/3625819},
  doi = {10.1145/3625819},
  note = {Just Accepted},
  journal = {ACM Comput. Surv.},
  month = oct,
  keywords = {machine learning, geoparsing, comparative review, location reference recognition}
}

Other Publications (Selected)

Li, H., Zech, J., Hong, D., Ghamisi, P., Schultz, M., & Zipf, A. (2022). Leveraging OpenStreetMap and Multimodal Remote Sensing Data with Joint Deep Learning for Wastewater Treatment Plants Detection. International Journal of Applied Earth Observation and Geoinformation, 110, 102804. [BibTeX]
```
@article{li2022leveraging,
  title = {Leveraging OpenStreetMap and Multimodal Remote Sensing Data with Joint Deep Learning for Wastewater Treatment Plants Detection},
  author = {Li, Hao and Zech, Johannes and Hong, Danfeng and Ghamisi, Pedram and Schultz, Michael and Zipf, Alexander},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  volume = {110},
  pages = {102804},
  year = {2022},
  publisher = {Elsevier}
}
```
Li, H., Zech, J., Ludwig, C., Fendrich, S., Shapiro, A., Schultz, M., & Zipf, A. (2021). Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning. International Journal of Applied Earth Observation and Geoinformation, 104, 102571. [BibTeX]
```
@article{li2021automatic,
  title = {Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning},
  author = {Li, Hao and Zech, Johannes and Ludwig, Christina and Fendrich, Sascha and Shapiro, Aurelie and Schultz, Michael and Zipf, Alexander},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  volume = {104},
  pages = {102571},
  year = {2021},
  publisher = {Elsevier}
}
```
Li, H., Yuan, Z., Novack, T., Huang, W., & Zipf, A. (2022). Understanding spatiotemporal trip purposes of urban micro-mobility from the lens of dockless e-scooter sharing. Computers, Environment and Urban Systems, 96, 101848. [BibTeX]
```
@article{li2022understanding,
  title = {Understanding spatiotemporal trip purposes of urban micro-mobility from the lens of dockless e-scooter sharing},
  author = {Li, Hao and Yuan, Zhendong and Novack, Tessio and Huang, Wei and Zipf, Alexander},
  journal = {Computers, Environment and Urban Systems},
  volume = {96},
  pages = {101848},
  year = {2022},
  publisher = {Elsevier}
}
```
Li, H., Ghamisi, P., Rasti, B., Wu, Z., Shapiro, A., Schultz, M., & Zipf, A. (2020). A multi-sensor fusion framework based on coupled residual convolutional neural networks. Remote Sensing, 12(12), 2067. [BibTeX]
```
@article{li2020multi,
  title = {A multi-sensor fusion framework based on coupled residual convolutional neural networks},
  author = {Li, Hao and Ghamisi, Pedram and Rasti, Behnood and Wu, Zhaoyan and Shapiro, Aurelie and Schultz, Michael and Zipf, Alexander},
  journal = {Remote Sensing},
  volume = {12},
  number = {12},
  pages = {2067},
  year = {2020},
  publisher = {MDPI}
}
```
Li, H., Ghamisi, P., Soergel, U., & Zhu, X. X. (2018). Hyperspectral and LiDAR fusion using deep three-stream convolutional neural networks. Remote Sensing, 10(10), 1649. [BibTeX]
```
@article{li2018hyperspectral,
  title = {Hyperspectral and LiDAR fusion using deep three-stream convolutional neural networks},
  author = {Li, Hao and Ghamisi, Pedram and Soergel, Uwe and Zhu, Xiao Xiang},
  journal = {Remote Sensing},
  volume = {10},
  number = {10},
  pages = {1649},
  year = {2018},
  publisher = {MDPI}
}
```
Li, H., Herfort, B., Huang, W., Zia, M., & Zipf, A. (2020). Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 41–51. [BibTeX]
```
@article{li2020exploration,
  title = {Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique},
  author = {Li, Hao and Herfort, Benjamin and Huang, Wei and Zia, Mohammed and Zipf, Alexander},
  journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
  volume = {166},
  pages = {41--51},
  year = {2020},
  publisher = {Elsevier}
}
```
Li, H., Herfort, B., Lautenbach, S., Chen, J., & Zipf, A. (2022). Improving OpenStreetMap missing building detection using few-shot transfer learning in sub-Saharan Africa. Transactions in GIS. [BibTeX]
```
@article{li2022improving,
  title = {Improving OpenStreetMap missing building detection using few-shot transfer learning in sub-Saharan Africa},
  author = {Li, Hao and Herfort, Benjamin and Lautenbach, Sven and Chen, Jiaoyan and Zipf, Alexander},
  journal = {Transactions in GIS},
  year = {2022},
  publisher = {Wiley Online Library}
}
```