Personal Profile

Yao Yao，Ph.D., Professor, mainly engaged in geographic information system (GIS) and geographic information science (GIScience) research. 

  Dr. Yao Yao is a professor and doctoral supervisor, a visiting scholar of the Spatial Information Science Research Center of the University of Tokyo, Japan, and a supporting scientific and technological talent of the "Morning Glory Plan" of Hubei Province. He is a senior member of the Big Data Committee of China Urban Science Research Association and a visiting scholar of Alibaba Group Data Department (Dharma Institute). He works part-time at the China Aerospace Qian Xuesen Institute of Space Technology and the State Grid Corporation as a senior technical advisor. Since 2016, he has been dedicated to research in the field of spatio-temporal big data technology and computable urban science (micro-scale urban information model), and has been awarded the 2020 ACM SIGSPATIAL China Rising Star Award (1-2 Chinese selected globally each year), Top 2% Global Scientist 2022 at Stanford University, and Young Scientist 2022 Global Frontier Science and Technology. He has published more than 100 high-level papers in the research area of multi-source spatio-temporal big data mining and urban computing, with a total of more than 3300 citations, including 9 ESI highly cited/hot papers with H-index=28. He has presided over and participated in many national key R&D, natural science fund projects and giant enterprise funded projects, and has more than 20 relevant patents and software copyrights. 2022 IJGIS, the top journal in the field of GIS, has the highest cited scholars (non-review papers) in the past five years, and three of them are the top 10 most cited papers of IJGIS in the past five years. The research can be downloaded from the City Light website: https://www.urbancomp.net/.

    Dr. Yao Yao has been working in the Fifth Research Institute of China Aerospace Science and Technology Group since 2011, and is responsible for the design and development of data analysis and processing systems for several national key projects. He has participated in several key national projects, including the UNEP African Water Resources Survey Project, the National Deep Space Exploration Program Chang'e-3 (CE-3) Lunar Satellite Remote Sensing Data Quality Evaluation Subsystem and the National 12th Five-Year Plan GF Series Satellite Disaster Mitigation Application System Requirements Analysis as the technical leader.

    Dr. Yao Yao has been published in Nature Human Behaviour, International Journal of Geographical Information Science (IJGIS), Annuals of AAG, Transactions In GIS (TGIS), Computers Environment and Urban Systems (CEGS), and the International Journal of Geographical Information Science (IJGIS), Computers Environment and Urban Systems (CEUS), Sustainable Cities and Society (SCS), and Cities, etc. He is a reviewer for 50 prestigious international SCI/SSCI journals in geographic information, remote sensing, computer science and data science. As a senior member of the Urban Science Research Society of the Ministry of Housing and Construction, Dr. Yao Yao has worked with teams including Wuhan University, Sun Yat-sen University, Shenzhen University, Stanford University (USA), University of Tokyo (Japan), Dharma Institute of Alibaba Corporation and Google Tensorflow (USA) on geolocation-based services, big data technologies and fine-grained urban simulation and applications. Conduct cooperation, research and exchange.

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

Research website：

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

https://www.urbancomp.net/  

Publications (* is the corresponding author): 

• I will not update publication list here. 

• Plese visit our website at http://www.urbancomp.net 

[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)

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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