Personal Profile

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

Bio and research interests:

Dr. Yao have 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, Dr. Yao 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 Geography and Information Engineering, China University of Geosciences (CUG) and visiting associate professor at the University of Tokyo, Japan. 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. Dr. Yao won the ACM SIGSPATIAL CHINA RISING STAR in 2020 (only 2 in China), World’s Top2% Scientists in 2022. He has published more than 100 journal citation report (JCR) papers since 2016, including 9 ESI highly cited papers (h-index = 27). Dr. Yao is also a reviewer for more than 40 academic journals.

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