个人信息 Personal information
博士生导师
,硕士生导师
学历：博士研究生毕业
毕业院校：University of California, Santa Barbara
所在单位：地理与信息工程学院
入职时间：2013-01-01
职务：副院长
电子邮箱：
科学研究
研究领域
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时空大数据：时空大数据分析、挖掘、模拟与可视化
空间计算智能：基于机器学习/人工智能的空间分析与时空模拟，解决复杂地理空间问题
高性能地理空间计算：利用并行计算技术，突破由大数据和复杂算法造成的地理空间计算壁垒
空间感知与计算：利用多源/多元数据，智能感知空间环境，分析和模拟空间环境变化，应用包括城市、土地利用与土地覆盖、地质、环境等
科研项目 查看更多>
著作成果
- 1 Big Data Computing for Geospatial Applications
- 2 High-Performance GeoComputation with the Parallel Raster Processing Library. In: Thill JC., Dragicevic S. (eds) GeoComputational Analysis and Modeling of Regional Systems. Advances in Geographic Information Science
- 3 Opportunities and Challenges for Urban Land-use and Land-cover Change Modeling in High-performance Computing. In: Shi, X. et al. (eds), Modern Accelerator Technologies for Geographic Information Science
专利
论文成果 查看更多>
- 1 Li, Z.*; Tang, W.; Huang, Q.; Shook, E. & Guan, Q. (2020). Introduction to Big Data Computing for Geospatial Applications. ISPRS International Journal of Geo-Information (SCI), 9(8): 487. DOI: 10.3390/ijgi9080487
- 2 Liang, X.; Guan, Q.*; Clarke, K. C.; Chen, G.; Guo, S. & Yao, Y. (2021). Mixed-cell cellular automata: A new approach for simulating the spatio-temporal dynamics of mixed land use structures. Landscape and Urban Planning (SCI/SSCI). DOI: 10.1016/j.landurbplan.2020.103960
- 3 Zhu, Q.; Li, Z.; Zhang, Y. & Guan, Q.* (2020). Building Extraction from High Spatial Resolution Remote Sensing Images via Multiscale-Aware and Segmentation-Prior Conditional Random Fields. Remote Sensing (MDPI, SCI), 2020(12): 3983. DOI: 10.3390/rs12233983
- 4 Liu, S.; Yang, X.; Guan, Q.; Lu, Z. & Lu, J.* (2020). An Ensemble Modeling Framework for Distinguishing Nitrogen, Phosphorous and Potassium Deficiencies in Winter Oilseed Rape (Brassica napus L.) Using Hyperspectral Data. Remote Sensing (MDPI, SCI), 2020(12): 4060. DOI: 10.3390/rs12244060
- 5 Yao, Y; Liu, Y.; Guan, Q.*; Hong, Y.*; Wang, R.; Wang R. & Liang, X. (2021). Spatiotemporal distribution of human trafficking in China and predicting the locations of missing persons. Computers, Environment and Urban Systems (SSCI). DOI: 10.1016/j.compenvurbsys.2020.101567