Guanfangli

[1]  Guan, F., Fang, Z., Wang, L., et al. (2022). Modelling people’s perceived scene complexity of real-world environments using street-view panoramas and open geodata. ISPRS Journal of Photogrammetry and Remote Sensing. 

[2]  Guan, F., Fang, Z., Zhang, X., et al. (2023). Using Street-view Panoramas to Model the Decision-Making Complexity of Road Intersections Based on the Passing Branches during Navigation. Computers, Environment and Urban Systems. 

[3]  Guan, F., Fang, Z., Yu, T., et al. (2020). Detecting visually salient scene areas and deriving their relative spatial relations from continuous street-view panoramas. International Journal of Digital Earth. 

[4]  Wei, X., Guan, F.(Co-First Author), Zhang, X., et al. (2023). Integrating planar and vertical environmental features for modelling land surface temperature based on street view images and land cover data. Building and Environment. 

[5]  Feng, W., Guan, F., Tu, J., et al., (2023). Detection of Changes in Buildings in Remote Sensing Images via Self-Supervised Contrastive Pre-Training and Historical Geographic Information System Vector Maps. Remote Sensing.

[6]  Guan, F., Fang, Z., Huang, H. (2021). Characterization and modeling of the decision-making complexity for navigation road intersections,  Proceedings of the 16th International Conference on Location Based Services, London, UK. (Oral)

[7]  Guan, F., Fang, Z., Huang, H. (2022). A novel framework for modelling people’s perceived scene complexity of navigation environments based on street-level imagery and open geodata. Abstr. Int. Cartogr. Assoc., 5, 104. Vienna, Austria. (Oral)

[8]  Guan, F. (2023). Modeling of the Scene Complexity of Real-World Navigation Environments and Relative Semantics for Egocentric Pedestrian Navigation Systems Using Continuous Street-View Panoramic Imagery. Geomatics and Information Science of Wuhan University, 48(8), 1398. 

[9]  Guan, F., Xu, A. (2019). An improved fast camera calibration method for mobile visual measurement system. Science of Surveying and Mapping, 44(02), 128-135.

[10]  Guan, F., Xu, A. (2018). Tree DBH measurement method based on smartphone and machine vision technology. Journal of Zhejiang A&F University, 35(05), 892-899. 

[11]  Zhang, X., Sun, Y., Guan, F., et al. (2022). Forecasting the crowd: An effective and efficient neural network for citywide crowd information prediction at a fine spatio-temporal scale. Transportation Research Part C Emerging Technologies, 143, 103854.  

[12]  Zhang, X., Liu, X., Chen, K., Guan, F., et al. (2023). Inferring building function : a novel geo-aware neural network supporting building-level function classification. Sustainable Cities and Society.

[13]  Wu, X., Guan, F., Xu, A. (2020). Passive Ranging Based on Planar Homography in a Monocular Vision System. Journal of Information Processing Systems, 16 (1), 155-170.     

[14]  Fang, Z., Yang, F., Guan, F., et al. (2020). A data model for organizing relative semantics as images to support pedestrian navigation computations. Transactions in GIS, 24: 1655– 1680. (SSCI)

[15]  Yang, F., Fang, Z., Guan, F., 2020. What Do We Actually Need During Self-localization in an Augmented Environment?. In: Web and Wireless Geographical Information Systems. W2GIS 2020. Lecture Notes in Computer Science, vol 12473. Springer, Cham. 

[16]  Fang, Z., Wang, L., Yang, F., Guan, F. (2021). Landmark selection preferences of young students under orientation task within street environment. Journal of Location Based Services.