出版著作

  • 期刊论文
  • 会议论文
  • 专著
  • 项目
  • 学术报告
  1. Yue J, Long Y, Wang S, et al. Optimization of Shared Electric Scooter Deployment Stations Based on Distance Tolerance[J]. ISPRS International Journal of Geo-Information, 2024, 13(5): 147.
  2. Zhong Y, Wang S, Liang H, et al. ReCovNet: Reinforcement learning with covering information for solving maximal coverage billboards location problem[J]. International Journal of Applied Earth Observation and Geoinformation, 2024, 128: 103710.
  3. Wang S, Li X, Lin L, et al. A Single Data Extraction Algorithm for Oblique Photographic Data Based on the U-Net[J]. Remote Sensing, 2024, 16(6): 979.
  4. Wang S, Qi H, Li T, et al. Can normalized difference vegetation index and climate data be used to estimate soil carbon, nitrogen, phosphorus and their ratios in Xizang's grasslands?[J]. Frontiers in Earth Science, 2024, 11: 1340020.
  5. Liang H, Wang S*, Li H, et al. Sponet: solve spatial optimization problem using deep reinforcement learning for urban spatial decision analysis[J]. International Journal of Digital Earth, 2024, 17(1): 2299211.
  6. Chen X, Wang S*, Li H, et al. An attention model with multiple decoders for solving p-Center problems[J]. International Journal of Applied Earth Observation and Geoinformation, 2023, 125: 103526.
  7. Yu Q, Wei W, Pan Z, J He, S Wang*, D Hong. GPF-Net: Graph-Polarized Fusion Network for Hyperspectral Image Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023.
  8. Nie S, Cai G, He J, S Wang*, et al. Economic costs and environmental benefits of deploying CCUS supply chains at scale: Insights from the source–sink matching LCA–MILP approach[J]. Fuel, 2023, 344: 128047.
  9. Wang S, Fu G. Modelling soil moisture using climate data and normalized difference vegetation index based on nine algorithms in alpine grasslands[J]. Frontiers in Environmental Science, 2023, 11: 1130448.
  10. Wang S, Liang H, Zhong Y, et al. DeepMCLP: Solving the MCLP with deep reinforcement learning for urban facility location analytics[J]. 2023.
  11. Ren, J., Yang, J*., Zhang, Y., Xiao, X., Xia, J. C., Li, X., & Wang, S*. (2022). Exploring thermal comfort of urban buildings based on local climate zones. Journal of Cleaner Production, 340, 130744.
  12. Liang, H., Wang, S*., Li, H., Ye, H., & Zhong, Y. (2022). A Trade-Off Algorithm for Solving p-Center Problems with a Graph Convolutional Network. ISPRS International Journal of Geo-Information, 11(5), 270.
  13. Song, S., Wang, S*., Ye, H., & Guan, Y. (2022). Exploratory analysis on the spatial distribution and influencing factors of Beitang landscape in the Shangzhuang Basin. Land, 11(3), 418.
  14. Chen, X., Wang, S*., Li, H., Lyu, F., Liang, H., Zhang, X., & Zhong, Y. (2022). Ndist2vec: Node with Landmark and New Distance to Vector Method for Predicting Shortest Path Distance along Road Networks. ISPRS International Journal of Geo-Information, 11(10), 514.
  15. Huang, K., Wang, C., Wang, S*., Liu, R., Chen, G., & Li, X. (2021). An efficient, platform-independent map rendering framework for mobile augmented reality. ISPRS International Journal of Geo-Information, 10(9), 593.
  16. Sun, Y., Wang, S*., Zhang, X., Chan, T. O., & Wu, W*. (2021). Estimating local-scale domestic electricity energy consumption using demographic, nighttime light imagery and Twitter data. Energy, 226, 120351.
  17. Feng, X., Wang, S*., Murray, A. T., Cao, Y., & Gao, S. (2021). Multi-objective trajectory optimization in planning for sequential activities across space and through time. Environment and Planning B: Urban Analytics and City Science, 48(4), 945-963.
  18. Sun, Y., Wang, S*., & Wang, Y. (2020). Estimating local-scale urban heat island intensity using nighttime light satellite imageries. Sustainable Cities and Society, 57, 102125.
  19. Li, W*., Wang, S*., Zhang, X., Jia, Q., & Tian, Y. (2020). Understanding intra-urban human mobility through an exploratory spatiotemporal analysis of bike-sharing trajectories. International Journal of Geographical Information Science, 34(12), 2451-2474.
  20. Church, R. L., & Wang, S. (2020). Solving the p-median problem on regular and lattice networks. Computers & Operations Research, 123, 105057.
  21. Zhou, L., Wang, S*., & Xu, Z. (2020). A multi-factor spatial optimization approach for emergency medical facilities in Beijing. ISPRS International Journal of Geo-Information, 9(6), 361.
  22. Wang, S*., Zhong, Y., & Wang, E. (2019). An integrated GIS platform architecture for spatiotemporal big data. Future Generation Computer Systems, 94, 160-172.
  23. Wang, S., Gao, S*., Feng, X., Murray, A. T., & Zeng, Y. (2018). A context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks. International Journal of Geographical Information Science, 32(7), 1368-1390.
  1. Wang S, Zhang Z, Su C, et al. Spatial Optimization Site Selection of Beijing Cainiao Station Based on Multi-Source Geospatial Data[C]//Proceedings of the 1st ACM SIGSPATIAL International Workshop on Geocomputational Analysis of Socio-Economic Data. 2023: 20-23.
  2. Wang S, Su C, Zhou J, et al. Analysis of the Distribution Characteristics and Influencing Factors of Advertising Billboards in Wuhan[C]//Proceedings of the 7th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising. 2023: 6-14.
  3. Wang S, Wang R, Su C, et al. Optimization of shared bicycle location in Wuhan city based on multi-source geospatial big data[C]//Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications. 2023: 43-46.
  4. Wang S, Zhou J, Liang H, et al. A New Approach for Solving Location Routing Problems with Deep Reinforcement Learning of Emergency Medical Facility[C]//Proceedings of the 8th ACM SIGSPATIAL International Workshop on Security Response using GIS. 2023: 50-53.
  5. Shaohua Wang*, Haojian Liang, Yang Zhong, Xueyan Zhang, Cheng Su. DeepMCLP:Solving the MCLP with Deep Reinforcement Learning for Urban Facility Location Analytics. The Fourth Spatial Data Science Symposium (SDSS 2023).http://sdss2023.spatial-data-science.net/.
  6. Haojian Liang, Shaohua Wang*. A New Approach Based on Graph Neural Network for Solving p-center Problems. The 1st International Workshop on Methods, Models, and Resources for Geospatial Knowledge Graphs and GeoAI, GIScience 2021, Poznań, Poland. https://ling-cai.github.io/GIScience-GeoKG/

[1] 王少华著. 地理空间优化理论、方法和应用（Foundations、Methodologies and Applications of Geospatial Optimization）

  1. 中国科学院引才计划
  2. 中国科学院引才择优工程
  3. 北京市朝阳区协同创新项目（共同负责人）， 2022.07-2023.06 “地理空间智能模型与GIS平台高效嵌入关键技术研发与应用”（E2DZ050100）课题经费175万元
  4. 创新团队项目（共同负责人），2023.07-2023.12，“遥感大数据创新团队”，课题经费100万元
  5. 可持续发展大数据国际研究中心（共同负责人），2022.03-2023.12，“地球大数据支撑城市可持续发展目标研究 ”，课题经费30万元
  6. 海南省自然科学基金面上项目（负责人）, 2023.01-2024.12 耦合遥感大数据和空间智能的槟榔黄化病预测预报方法研究(323MS110), 课题经费7万元
  7. 北京市传感器重点实验室开放课题（负责人），2022.07-2023.06 “面向复杂情景的声传感器的特征分析及配置优化”（E2U1050600），课题经费3万元
  8. 国家测绘局测绘公益项目（负责人） 2015.01-2016.12 “地理空间数据内容模型与存储格式标准化研究”课题-GIS数据格式检查软件 （No.201512015）课题经费28.2万元
  9. 北京市优秀人才资助项目（负责人） 2015.01-2016.12 “面向大数据的商业地理信息系统关键技术研究” （No.201500002685XG242） 课题经费30万元
  10. 全国博士后管委会资助项目（负责人） 2015.01-2016.12 “空间优化优化研究” （No.20150081）课题经费30万元
  11. 中国营养学术开放课题（负责人） 2016.01-2016.12 “中国儿童营养地图” （No.20160095）课题经费5万元
  12. 北京市科委科技创新战略研究及专家咨询专项研究课题 2015.03-2015.12 “京津冀空间信息产业一体化发展专题调研”（Z151100003115007），研究报告分析与撰写（第二参与人），经费5万元
  13. 北京市科委新技术培育项目 2015.01-2016.04 面向海量地理信息数据存储和并行空间分析的高性能GIS系统研制，负责系统设计（第二参与人）经费600万
  14. 企事业委托项目，2023.08-2.23.12，“遥感大数据综合分析与可视化平台开发” ，课题经费100万元
  1. 王少华. 基于地理学认知的遥感智能计算. 中国科学院空天信息创新研究院遥感与数字地球重点实验室2023年年会报告. 2024-01-05
  2. Shaohua Wang. Learn to Solve the Spatial Optimization Decision with Deep Reinforcement Learning in SDGs. The 1st Youth Innovation Forum on Digital Earth. 2023-08-23—2023-08-24.
  3. 王少华.耦合大数据和人工智能的遥感智能计算进展. 第22届中国遥感大会国土资源遥感论坛. 2023-08-22.
  4. 王少华. 耦合时空大数据和人工智能的空间优化研究进展. ACM中国图灵大会（ACM TURC 2023）时空智能专题研讨会. 2023-07-30.
  5. 王少华. 耦合大数据和人工智能的高智能空间计算研究进展. 第三届空间信息技术应用大会社会遥感地理计算分论坛. 2023-07-14.
  6. Haojian Liang; Shaohua Wang*. A New Approach Based on Graph Neural Network for Solving p-center Problems, The 1st International Workshop on Methods, Models, and Resources for Geospatial Knowledge Graphs and GeoAI, Poznań, 2021-09-27—2021-09-30.
  7. Shaohua Wang. The New Generation Geoinformation System & Science, 2021年美国地理学家协会年会, 美国西雅图, 2021-04-07至2021-04-11.
  8. Shaohua Wang; Ershun Zhong; Hao Lu; Weiying Yun; Wenwen Cai. A Big Spatiotemporal Analytics Engine for Air Traffic Movement data, Analysis of Movement Data (AMD’18) workshop, GIScience, Melbourne, Australia, 2018-8-28—2018-8-30.
  9. Shaohua Wang. Spatiotemporal Study: Big Geospatial Data Challenges and Best Practices, 2018年美国地理学家协会年会, 美国新奥尔良, 2018-4-10至2018-4-14.
  10. Shaohua Wang. Comparative analysis for p-median problems, Leadership Workshop on Location Analytics in Business, University of California Santa Barbara, 2018-1-31—2018-2-2.