Yao Yao

Professor   Supervisor of Doctorate Candidates   Supervisor of Master's Candidates

Honors and Titles : ACM SIGSPATIAL中国新星奖
ICC2019 (Tokyo) GIS Session会场主席
司马云“我心中的GIS名师”

Gender : Male

Alma Mater : Sun Yat-sen University

Education Level : Postgraduate (Doctoral)

Degree : Doctoral Degree in Science

Status : Employed

School/Department : School of Geography and Information Engineering

Date of Employment : 2018-03-05

Discipline : Geospatial Information Engineering

Business Address : Room 521, No. 68 Jinchen St.

Contact Information : yaoy@cug.edu.cn

Email :


Research Projects

耦合多源空间大数据的中国城市贫困精细分布研究

Hits :

Note : 中央高校基本科研业务费专项资金杰出人才培育基金

Project Number : CUG190606

Date of Project Initiation : 2019-01-01

Date of Project Completion : 2020-12-01

Next One : Participate in the National Natural Science Foundation of China (Grant No. 41601420)

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Personal Profile

Dr. Yao Yao is a professor and doctoral supervisor. He is a researcher and visiting scholar at the Center for Spatial Information Science, University of Tokyo, Japan, and a recipient of the Japan Society for the Promotion of Science (JSPS) Excellence Young Researcher (EYR) qualification. He is also a science and technology talent supported by the "Morning Light Plan" project in Hubei Province. He serves as a senior member and committee member of the Big Data Committee of the China Urban Science Research Association, and a visiting scholar in the Data Technology and Product Department of Alibaba Group. He also holds part-time positions as a senior technical consultant at the State Grid Corporation of China.


Since 2016, he has been dedicated to research in the fields of spatio-temporal big data technology and computable urban science (micro-scale urban models). He was honored with the 2020 ACM SIGSPATIAL China Rising Star Award (1-2 Chinese selected worldwide each year), Clarivate Highly Cited Researcher (2023), Top 2% Scientist Worldwide by Stanford University (2022, 2023), and Global Frontiers of Science Young Scientist 2022.


Dr. Yao has published over 100 high-level papers in the field of multi-source spatio-temporal big data mining and urban computing, which have been cited over 4,500 times in total. This includes 9 ESI highly cited/hotspot papers, with an H-index of 31. He has led and participated in numerous national key R&D projects, natural science foundation projects, and projects funded by large corporations, holding more than 20 related patents and software copyrights. In 2022, he was the most cited scholar in the field of Geographic Information Systems in the past five years in the top-tier journal IJGIS, with 3 of his papers being in the top 10 most cited papers in the past 5 years. He also serves as a guest editor for the top-tier urban climate journal, Urban Climate, and an editor for the Journal of Spatio-temporal Information. His research can be downloaded from the "Lights of City" website: https://www.urbancomp.net/.


Dr. Yao has become a reviewer for 50 authoritative international SCI/SSCI journals in the fields of geographic information, remote sensing, computer science, and data science, including Nature Human Behaviour, International Journal of Geographical Information Science (IJGIS), Annuals of AAG, Transactions In GIS (TGIS), Computers Environment and Urban Systems (CEUS), Landscape and Urban Planning, and Cities. As a senior member of the Urban Science Research Association of the Ministry of Housing and Urban-Rural Development, Dr. Yao has collaborated, researched, and exchanged with teams including Wuhan University, Sun Yat-sen University, Shenzhen University, Stanford University, University of Tokyo, Alibaba DAMO Academy, and Google Tensorflow on location-based services, big data technology, and fine urban simulation and application.


Students with backgrounds in 3S (GNSS/RS/GIS), computer science, and data science are welcome to join the High Performance Spatial Intelligent Computing Laboratory (HPSCIL@CUG) and Dr. Yao Yao's graduate student team!


 


Research website:

https://www.researchgate.net/profile/Yao_Yao42/

https://www.urbancomp.net/  


Publications (* is the corresponding author): 

 

[1] Wang, R., Lu, Y.*, Wu, X., Liu, Y., & Yao, Y.*, 2020. Relationship between eye-level greenness and cycling frequency around metro stations in Shenzhen, China: A big data approach. Sustainable Cities and Society, 102201. (SCI)

[2] Zhang, J., Li, X.*, Yao, Y.*, Hong, Y., He, J., Jiang, Z., & Sun, J. 2020. The Traj2Vec model to quantify residents’ spatial trajectories and estimate the proportions of urban land-use types. International Journal of Geographical Information Science, 1-19. (SCI/SSCI)

[3] Yao, Y.*, Qian, C., Hong, Y. etc. 2020. Delineating mixed urban “Jobs-Housing” patterns at a fine scale by using high spatial-resolution remote-sensing imagery. Complexity. DOI: 10.1155/2020/8018629. (SCI)

[4] Wang, R., Yang, B., Liu, P., Zhang, J., Liu, Y., Yao, Y.*, & Lu, Y. 2020. The longitudinal relationship between exposure to air pollution and depression in older adults. International Journal of Geriatric Psychiatry. DOI: 10.1002/gps.5277. (SCI/SSCI)

[5] Zhai, Y.#, Yao Y.#, Guan Q.*, Liang X., Li X., Pan Y., Yue H., Yuan Z., & Zhou J., 2020. Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata. International Journal of Geographical Information Science, DOI: 10.1080/13658816.2020.1711915. (SCI/SSCI,# 共同第一作者)

[6] Yao, Y.*, Wu, D., Hong, Y., Chen, D., Liang, Z., Guan, Q., Liang, X., Dai, L. 2020. Analyzing the Effects of Rainfall on Urban Traffic-Congestion Bottlenecks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS.2020.2966591. (SCI)

[7] Chen, D., Zhang, Y., Yao, Y.*, Hong, Y., Guan, Q., Tu, W. 2019. Exploring the spatial differentiation of urbanization on two sides of the Hu Huanyong Line -- based on nighttime light data and cellular automata. Applied Geography. 112(2019): 102081. (SSCI) 

[8] Wang, R., Liu, Y., Lu, Y., Zhang, J., Liu, P., Yao, Y.*, Grekousis, G.*. 2019. Perceptions of built environment and health outcomes for older Chinese in Beijing: A big data approach with street view images and deep learning technique. Computers, Environment and Urban Systems. DOI: 10.1016/j.compenvurbsys.2019.101386. (SSCI)

[9] Yao, Y., Liang, Z., ..., Guan, Q.*. 2019. A human-machine adversarial scoring framework for urban perception assessment using street-view images. International Journal of Geographical Information Science. DOI: 10.1080/13658816.2019.1643024. (SCI/SSCI)

[10] Wang, R., Liu, Y.*, ..., Yao, Y.*. 2019. The linkage between the perception of neighbourhood and physical activity in Guangzhou, China: using street view imagery with deep learning techniques. International Journal of Health Geographics. DOI: 10.1186/s12942-019-0182-z. (SCI/SSCI)

[11] Wang, R., Yuan, Y., ..., Yao, Y.*. 2019. Using street view data and machine learning to assess how perception of neighborhood safety influences urban residents’ mental health. Health & Place. DOI: 10.1016/j.healthplace.2019.102186. (SCI/SSCI)

[12] Zhang, Y., Li, Q., Tu, W.*, Mai, K., Yao, Y., Chen, Y. 2019. Functional urban land use recognition integrating multi-source geospatial data and cross-correlations. Computers, Environment and Urban System. DOI: 10.1016/j.compenvurbsys.2019.101374. (SSCI)

[13] Wang, R., Helbich, M., Yao, Y., Zhang, J., Liu, P., Yuan, Y.*, & Liu, Y.*. 2019. Urban greenery and mental wellbeing in adults: Cross-sectional mediation analyses on multiple pathways across different greenery measures, Environmental Research. DOI: 10.1016/j.envres.2019.108535. (SCI/SSCI)

[14] Yao, Y., Liu, P., Hong, Y., Liang, Z., Wang, R., Guan, Q.*, & Chen, J. 2019. Fine-scale Intra- and intercity commercial store site recommendations using knowledge transfer. Transactions in GIS. DOI: 10.1111/TGIS.12553. (SSCI)

[15] Wang, R., Lu, Y., Zhang, J., Liu, P., Yao, Y.*, Liu, Y. 2019. The relationship between visual enclosure for neighbourhood street walkability and elders’ mental health in China: Using street view images. Journal of Transport & Health. DOI: 10.1016/j.jth.2019.02.009. (SCI)

[16] Hong, Y. & Yao, Y.* 2019. Hierarchical community detection and functional area identification with OSM roads and complex graph theory. International Journal of Geographical Information Science. DOI: 10.1080/13658816.2019.1584806. (SCI/SSCI)

[17] Marco, H.#, Yao, Y.#, Liu, Y., Zhang, J., Liu, P. & Wang, R.*. 2019. Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China. Enviroment International.DOI: 10.1016/j.envint.2019.02.013. (SCI,# 共同第一作者)

[18] Wang, R., Liu, Y., Xue, D.*, Yao, Y., Liu, P., & Helbich, M. 2019. Cross-sectional associations between long-term exposure to particulate matter and depression in China: The mediating effects of sunlight, physical activity, and neighborly reciprocity. Journal of Affective Disorders. DOI: 10.1016/j.jad.2019.02.007. (SCI)

[19] Wang, R., Chen, H.*, Liu, Y., Lu, Y., Yao, Y. 2019. Neighborhood social reciprocity and mental health among older adults in China: the mediating effects of physical activity, social interaction, and volunteering. BMC Public Health. DOI: 10.1186/s12889-019-7385-x. (SCI)

[20] Yue, H., Guan, Q.*, Pan, Y., Chen, L., Lv, J., & Yao, Y. 2019. Detecting clusters over intercity transportation networks using K-shortest paths and hierarchical clustering: a case study of mainland China. International Journal of Geographical Information Science, DOI: 10.1080/13658816.2019.1566551. (SCI/SSCI)

[21] Yao, Y.*, Chen, D.*, Chen, L., Wang, H. & Guan, Q. 2018. A time series of urban extent in China using DSMP/OLS nighttime light data. PLoS ONE. DOI: 10.1371/journal.pone.0198189. (SCI)

[22] Lv, J., Ma, T., Dong, Z., Yao, Y.* & Yuan, Z. 2018 Temporal and Spatial Analyses of the Landscape Pattern of Wuhan City Based on Remote Sensing Images. ISPRS Int. J. Geo-Inf. 7, 340. (SCI)

[23] He, J., Li, X.*, Yao, Y.*, Hong, Y. & Zhang, J. 2018. Mining transition rules of cellular automata for simulating urban expansion by using the deep learning techniques. International Journal of Geographical Information Science. DOI: 10.1080/13658816.2018.1480783. (SCI)

[24] Liang, X, Liu, X.*, Li, X.*, Chen, Y.*, Tian, H. & Yao, Y. 2018. Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method. Landscape and Urban Planning. 177, 47-63. DOI: j.landurbplan.2018.04.016. (SCI)

[25] Yao, Y*, Hong, Y.*, Wu, D, Zhang, Y. & Guan, Q. 2018. Estimating effects of the "Communities Opening" policy on alleviating traffic congestion in China's big cities by integrating ant colony optimization and complex network analyses. Computers, Environment and Urban System. DOI: 10.1016/j.compenvurbsys.2018.03.005. (SSCI)

[26] Yao, Y.*, Zhang, J.*, Hong, Y., Liang, H., & He, J., 2018. Mapping fine-scale urban housing prices by fusing remote-sensing images and social media data. Transactions in GIS, DOI: 10.1111/tgis.12330. (SCI)

[27] Zhang, D., Liu, X., Wu, X., Yao, Y., Wu, X. & Chen, Y. 2018. Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng, China. GIScience & Remote Sensing, DOI: 10.1080/15481603.2018.1507074. (SCI)

[28] Yao, Y., Liu, X.*, Li, X.*, Liu, P, Hong, Y., Zhang, Y. & Mai, K., 2017. Simulating urban land-use changes at a large scale by integrating dynamic land parcel subdivision and vector-based cellular automata. International Journal of Geographical Information Science, 31(12): 2452-2479. (SCI)

[29] Yao, Y., Li, X.*, Liu, X.*, Liu, P., Liang, Z., Zhang, J. & Mai, K., 2017. Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model. International Journal of Geographical Information Science, 31(4), 825-848. (SCI)

[30] Yao, Y., Liu, X.*, Li, X., Zhang, J., Liang, Z., Mai, K. & Zhang, Y., 2017. Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data. International Journal of Geographical Information Science, 31(6), 1220-1244. (SCI)

[31] Liu, X., He, J., Yao, Y.*, Zhang, J., Liang, H., Wang, H., & Hong, Y., 2017. Classifying urban land use by integrating remote sensing and social media data. International Journal of Geographical Information Science, 31(8): 1675-1696. (SCI)

[32] Chen, Y., Liu, X.*, Li, X., Liu, X., Yao, Y., Hu, G., Xu, X. & Pei, F., 2017. Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k-medoids method. Landscape and Urban Planning, 160, 48-60. (SCI)

[33] He, Y., Ai, B.*, Yao, Y., & Zhong, F., 2015. Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images. International Journal of Applied Earth Observation and Geoinformation, 38, 164-174. (SCI)

...


Project:


  1. Chair the National Natural Science Foundation of China (Grant No. 41801306)

  2. Participate in the National Natural Science Foundation of China (Grant No. 41601420)

  3. Site recommendation of offline-stores for Alibaba Group Visiting Fellow

  4. Typical Application System (TAS) Development -- Affiliated to Venezuelan Remote Sensing Satellite (VRSS-1) Chief Technical Principal

  5. African Water Resources Survey -- Affiliated to United Nations Environment Program (UNEP) Principal of the Advanced Remote Sensing Application Subsystem

  6. Demand Analysis of GF Series Satellite’s Disaster Reduction Application System -- Affiliated to National 12th Five-Year Plan Chief Technical Principal

  7. Chang'e-3 Lunar Probe (CE-3) -- Affiliated to National Deep Space Exploration Plan Principal of the Quality Assessment Subsystem of Satellite Remote Sensing Image