Peng Luo

Postdoc, SCL

Peng Luo earned his Ph.D. from the Technical University of Munich and was a former visiting researcher at the University of Oxford. He received his master's degree in GIScience from Peking University in 2020. Peng's research interests focus on using geographic domain knowledge for urban analysis, particularly considering the unique characteristics of geographic data, such as sparsity and bias. His research experience includes spatial prediction, human mobility analysis, and visual AI.

Selected publications

Leading author (* corresponding author/ project lead)

  1. Luo, P., Song, Y., Zhu, D., Cheng J. and Meng L. A Generalized Spatial Heterogeneity Model for Interpolation.2022. International Journal of Geographical Information Science, 37(3), 634-659 (Top 10 read at 2023)
  2. Luo, P., Song, Y., Huang, X., Ma, H., Liu, J., Yao, Y. and Meng, L., 2022. Identifying determinants of spatio-temporal disparities in soil moisture of the Northern Hemisphere using a geographically optimal zones-based heterogeneity model. ISPRS Journal of Photogrammetry and Remote Sensing, 185, pp.111-128 
  3. Luo, P., Song, Y. and Wu, P., 2021. Spatial disparities in trade-offs: economic and environmental impacts of road infrastructure on continental level. GIScience and Remote Sensing, 58(5), pp.756-775. 
  4. Li, Y.#, Luo, P.#(co-first), Song, Y., Zhang, L., Qu, Y and Hou, Z., 2023. A locally explained heterogeneity model for examining wetland disparity. International Journal of Digital Earth, 13(2), p.4533-4552.
  5.  Yang#, L., Luo, P. #(co-first), et al. 2024. A spatio-temporal unmixing with heterogeneity model for the identification of remotely sensed MODIS aerosols: Exemplified by the case of Africa. International Journal of Applied Earth Observation and Geoinformation
  6. Luo, P., Zhang, X., Cheng, J. and Sun, Q., 2019. Modeling population density using a new index derived from multi-sensor image data. Remote Sensing, 11(22), p.2620.
  7. Yao, Y., … Guan, Q. , Luo, P.*, 2024. Automated External Defibrillator (AED) location selection considering myocardial infarction risk and medical resources. Transactions in GIS.
  8. Yao, Y., Dong, A., Liu, Z., Jiang, Y., Guo, Z., Cheng, J., Guan, Q. and Luo, P.*., 2023. Extracting the pickpocketing information implied in the built environment by treating it as the anomalies. Cities, 143, p.104575. 
  9. Yao Y., Lei S., Guo., Li Y., Ren S., Liu Z., Guan Q.,Luo, P.*. Fast urban logistics optimization based on hybrid sparrow search algorithm. International Journal of Geographical Information Science.1-29 
  10. Yao, Y., Yan, X., Luo, P.*, Liang, Y.*, Ren, S., Hu, Y., Han, J. and Guan, Q., 2022. Classifying land-use patterns by integrating time-series electricity data and high-spatial resolution remote sensing imagery. International Journal of Applied Earth Observation and Geoinformation, 106, p.102664.
  11. Yao, Y., Guo, Z., Dou, C., Jia, M., Hong, Y., Guan, Q.* and Luo, P.*, 2023. Predicting mobile users' next location using the semantically enriched geo-embedding model and the multilayer attention mechanism. Computers, Environment and Urban Systems, 104, p.102009. 
  12. Yao, Y., Feng, C., Xie, J., Yan, X., Guan, Q., Han, J., Zhang, J., Ren, S., Liang, Y., Luo, P*. A site selection framework for urban power substation at micro-scale using spatial optimization strategy and geospatial big data. Transactions in GIS. (Cover paper)

Other publications

  1. Yan, X., Jiang, Z., Luo, P., Wu, H., Dong, A., Mao, F., Wang, Z., Liu, H. and Yao, Y., 2024. A multimodal data fusion model for accurate and interpretable urban land use mapping with uncertainty analysis. International Journal of Applied Earth Observation and Geoinformation, 129, p.103805.
  2. Chen, C., Feng, Y., Wei, M., Liu, Z., Luo, P., Wang, S. and Meng, L., 2024. A hyper-knowledge graph system for research on AI ethics cases. Heliyon.
  3. Wei, M., Feng, Y., Chen, C., Luo, P., Zuo, C., Meng, L. Unveiling Public Perception of AI Ethics: An Exploration on Wikipedia Data. EPJ Data Science.
  4. Dong, A., Zhang, Y., Guo, Z., Luo, P., Yao, Y., He, J., Zhu, Q., Jiang, Y., Xiong, K. and Guan, Q., 2024. Predicting the locations of missing persons in China by using NGO data and deep learning techniques. International Journal of Digital Earth, 17(1), p.2304076.
  5. Zhang Z, Song Y, Luo, P.. GeoComplexity explains spatial errors. International Journal of Geographical Information Science (Most read at 2023)
  6. Zhang, Z., Song, Y., Luo, P. et al. Spatial disparities of factors affecting air pollutant emissions in industrial regions on continental level. International journal of applied earth observation and geoinformation.117 (2023): 103221. 
  7. Cheng, T., Zhao, Y., Song, Y., Ma, L., Zhang, Z., Luo, P., Gao, P., Zhang, M. and Zhao, C., 2023. Towards resilience effectiveness: Assessing its patterns and determinants to identify optimal geographic zones. Journal of Cleaner Production, 429, p.139596.
  8. Cheng, J., Zhang, X., Chen, X., Ren, M., Huang, J. and Luo, P., 2022. Early Detection of Suspicious Behaviors for Safe Residence from Movement Trajectory Data. ISPRS International Journal of Geo-Information , 11(9), p.478.
  9. Cheng, J., Zhang, X., Luo, P., Huang, J., Huang J. An unsupervised approach for semantic place annotation of trajectories based on the prior probability. Information Sciences, 607, 1311-1327 
  10. Yang, W., Zhang, X. and Luo, P., 2021. Transferability of convolutional neural network models for identifying damaged buildings due to earthquake. Remote Sensing, 13(3), p.504.
  11. Cheng, J., Zhang, X., Sun, M., Luo, P. and Yang, W., 2020. Random forest model for the estimation of fractional vegetation coverage based on a UAV-ground co-sampling strategy. Acta Scientiarum Naturalium Universitatis Pekinensis. 56(1), pp.143-154
Headshot of Peng Luo

Contact

pengluo@mit.edu

Labs

Senseable City Lab

Current Projects

Favelas 4D