Yao Yao

Associate professor   Supervisor of Master's Candidates

Gender : Male

Alma Mater : Sun Yat-sen University

Education Level : Postgraduate (Doctoral)

Degree : Doctoral Degree in Science

Status : Employed

School/Department : School of Information Engineering

Date of Employment : 2018-03-05

Discipline : software engineering Geographic Information Science

Business Address : Room 406, Engineering Center, China University of Geosciences, No.388 Lumo Road, Hongshan District, Wuhan, Hubei

Contact Information : yaoy@cug.edu.cn

Email :


Education Background

2014.8 -- 2017.12

Sun Yat-sen University       GIS       Doctoral Degree

2009.9 -- 2011.6

School of Geodesy and Geomatics, Wuhan University       Geodesy and Survey Engineering       Master's Degree

2004.9 -- 2008.6

School of Geodesy and Geomatics, Wuhan University       Survey and Mapping Engineering       Bachelor's Degree

Social Affiliations

2018.11 -- Now

住建部中国城市科学研究会城市大数据专委会委员

2019.3 -- Now

国家电网公司高级技术顾问

2018.6 -- Now

阿里巴巴集团达摩院访问学者

Research Focus

Application of artificial intelligence and machine learning in smart cities

Multi-source Geospatial Bgig Data Mining and Fusion

Fine-scale Urban Computing and Urban Land-use Change Simulation

High Spatial Resolution Remote Sensing Image Processing and Understanding

Cluster-based Parallel Computation of Massive Geospatial Data sets

Other Contact Information

  • ZipCode :

  • email :

  • Work Experience

    2018.3 -- Now

    School of Information Engineering, CUG      地理与信息工程学院

    2018.7 -- Now

    Chinese Society for Urban Studies      城市大数据专业委员会      Senior Member

    2018.7 -- Now

    BU of Data Technology and Products, Alibaba      Visiting Scholar

    2017.7 -- 2018.1

    Department of Data Technology, Alibaba Group      Senior Algorithm Engineer

    2011.7 -- 2014.8

    China Academy of Space Technology      Algorithm Engineer

    2008.9 -- 2009.7

    National Undergraduate Voluntary Support Education Group

    Personal Profile

    Yao Yao,Ph.D., associate professor, master's tutor, mainly engaged in geographic information system (GIS) and geographic information science (GIScience) research.  


    Bio and research interests:

    Yao Yao received the Surveying and Mapping engineering degree from Wuhan University (WHU) in 2008, the M.Sc. degree in Geodesy and Survey Engineering from WHU in 2011, and the Ph.D. degree in Cartography and Geography Information System from Sun Yat-sen University (SYSU) in 2017. 

    From 2011 to 2014, he was hired as an algorithm engineer for remote sensing application in China Academy of Space Technology, China Aerospace and Technology Corporation (CASC). Dr. Yao was hired as a senior algorithm engineer for location-based service data mining in Alibaba Group in 2017. 

    Dr. Yao is currently an associate professor in the School of Information Engineering, China University of Geosciences (CUG). At the same time, he worked as a visiting scholar and senior algorithm engineer at Alibaba Group (the China’s biggest online shopping platform) 's data center. He has published more than 30 journal citation report (JCR) papers (inclusing 5+ ESI High Cited Papers) since 2014. 

    Dr. Yao is also a reviewer for many academic journals, including International Journal of Geographical Information Science, International Journal of Remote Sensing, EPJ Data Science, Computers Environment and Urban Systems, Sustainable Cities and Society, Journal of Spatial Science and so on. His main research interests comprise multi-source big data mining, machine learning and fine-scale simulation of urban land-use dynamic changes.



    Researchgate:

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

    http://www.urbancomp.net/


    Publications (* is the corresponding author): 

    [1] 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, # co-first author)

    [2] 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)

    [3] Guan, Q, Ren,S, Yao,Y*, et al. 2020. Revealing the behavioral patterns of different socioeconomic groups in cities with mobile phone data and house price data. Journal of Geo-information Science, 22(1):100-112.

    [4] 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) 

    [2] 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)

    [3] 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)

    [4] 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)

    [5] 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)

    [6] 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. Accepted.

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

    [8] 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)

    [9] 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)

    [10] 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)

    [11] 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, # co-first author)

    [12] 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)

    [13] 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)

    [14] 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)

    [15] 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)

    [16] 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)

    [17] 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)

    [18] 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)

    [19] 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)

    [20] 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)

    [21] 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)

    [22] 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)

    [23] 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)

    [24] 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)

    [25] 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)

    [26] 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)

    [27] 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)

    [28] YAO Yao, ZHANG Yatao, GUAN Qingfeng, MAI Ke, ZHANG Jinbao. Sensing Multi-level Urban Functional Structures by Using Time Series Taxi Trajectory Data. GEOMATICS AND INFORMATION SCIENCE OF WUHAN UNIVERS, 2019, 44(6): 875-884.

    [29] Yao, Y.*, Wu, D., …, & Cai, Y. 2019. Analyzing the effects of rainfall on the urban traffic congestion bottlenecks by using floating car data. IEEE Geoscience and Remote Sensing Society (IGARSS 2019), Yokohama, Japan.

    [30] Yao, Y., Zhou J., Guan Q.* & Zhai Y. 2019. Delineation of Chinese county-scale urban function patterns with the real-time Tencent user density. International Cartographic Association (ICC 2019), Tokyo, Japan.

    [31] Yao, Y., Liang, H., Li, X.*, & Zhang J., 2017. Sensing urban land use patterns by integrating Google Tensorflow and scene classification models. The International Workshop on Image and Data Fusion (IWIDF), ISPRS. Wuhan, China.

    [32] Yao, Y., Hong, Y., Li, X*, & Wu, D. 2017. Estimating effects of the "Communities Opening" policy on alleviating traffic congestion in China's big cities. The Third International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM), ISPRS. Wuhan, China.

    [33] Yao, Y., Liang, Z., Li, X*, Zhang, J. & Chen, G. 2017. Redefining Guangdong Province’s city system by integrating multi- source open spatial data -based on Natural City. International Symposium on Geoenvironmental Informatics (ISGEI), Hongkong, China.

    ...


    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