中国地质大学(武汉)导师教师师资介绍简介-姚尧

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本站小编 Free考研考试/2021-07-31

招生专业：
081603 地图制图学与地理信息工程（学硕，需考数一）
资源与环境（专硕）

团队介绍：
“城市之光”：http://www.urbancomp.net/ourteam/

欢迎3S（GNSS/RS/GIS）、计算机科学、统计学和数据科学等专业背景的同学们，加入高性能空间智能计算实验室（HPSCIL@CUG，PI：关庆锋教授）的研究生团队！

学术成果 (*表示通讯作者，详细参考“城市之光”官网)

这里不更新了，对相关成果感兴趣的请访问我们官网：www.urbancomp.net
微信公众号：iGEODATA

[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检索)
[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检索)
[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/**. (SCI检索)
[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检索)
[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/**.2020.**. (SCI/SSCI检索，# 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.**. (SCI检索)
[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检索)
[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检索)
[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/**.2019.**. (SCI/SSCI检索)
[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检索)
[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检索)
[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检索)
[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检索)
[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检索)
[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检索)
[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/**.2019.**. (SCI/SSCI检索)
[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检索，# 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检索)
[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检索)
[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/**.2019.**. (SCI/SSCI检索)
[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.**. (SCI检索)
[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检索)
[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/**.2018.**. (SCI检索)
[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检索)
[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检索)
[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检索)
[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/**.2018.**. (SCI检索)
[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检索)
[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检索)
[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检索)
[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检索)
[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检索)
[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检索)
[34] 关庆锋, 任书良, 姚尧*, 等.耦合手机信令数据和房价数据的城市不同经济水平人群行为活动模式研究[J].地球信息科学学报,2020,22(1):100-112.
[35]姚尧, 张亚涛*, 关庆锋, 麦可, 张金宝. 使用时序出租车轨迹识别多层次城市功能结构[J]. 武汉大学学报·信息科学版, 2019, 44(6): 875-884. (EI检索)
[36] 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.
[37] 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.
[38] 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.
[39] 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.
[40] 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.
...

专利成果
[1] 姚尧, 刘晔, 关庆锋, 王葭泐. 2020. 一种用于街道品质评估的人机对抗评分模型. 2.8.
[2] 刘一飞, 姚尧. 2019. 一种具备验证机制的请求队列方法及系统. 6.X.
[3] 姚尧, 刘一飞. 2019. 一种用于失踪人群时空定位服务的数据分析方法. 6.6.
[4] 刘小平, 梁迅, 黎夏, 陈逸敏, 姚尧, 许晓聪 & 李丹. 2017. 一种未来土地利用情景动态模拟模型. CN.
[5] 姚尧, 邹同元, 吴俊, 王玮哲 & 王文亮. 2014. 一种面向水质定量遥感应用的遥感影像融合方法. CNA.
[6] 刘翔, 姚尧, 王玮哲 & 邹同元. 2013. 一种用于遥感图像的IO双缓存交互多核处理方法. CNA.
[7] 王玮哲, 姚尧, 邹同元, 宋晨曦 & 李光丽. 2013. 一种面向区域覆盖的影像自动镶嵌方法. CNA.
...

项目经历

[1] 2020/07-2023/06 主持国家重点研发计划子课题《区域生态环境在线智能感知系统》；
[2] 2020/04-2021/12 主持国家电网重点项目《基于配用电大数据的供电服务质效提升模型》；
[3] 2020/04-2020/12 主持XX项目《多源遥感图像融合目标XXXX系统》；
[4] 2019/07-2020/07 入选湖北省湖北省青年科技晨光计划项目，日本交流；
[5] 主持“宝贝在哪”寻亲服务发布（http://www.baobeizaina.cn），公益服务项目；
[6] 主持中央高校基本科研业务费专项资金杰出人才培育基金（CUG190606），耦合多源空间大数据的中国城市贫困精细分布研究；
[7] 江西省遥感地理与用电信息相融合的农村用地性质识别与负荷预测；
[8] 主持国家科研基金项目青年科学基金（**），融合多源空间数据的建筑物尺度城市混合功能识别与评价；
[9] 主持武汉大学测绘遥感信息工程国家重点实验室开放基金项目（18S01），耦合夜间灯光数据和阿里大数据的微观尺度的城市经济模式分析；
[10] 国家科研基金重点项目（20**293), 地理过程建模的多尺度空间协同与精细化模拟：以城市群增长为例；
[11] 国家科技重大专项，城市群经济区空间开发规划管理和辅助决策；
[12] 武汉市科研项目应用基础研究计划（），基于多源时空大数据的市政管线智能管控关键技术研究；
[13] 国家自然科学基金青年基金项目（**），基于地块对象的城市空间结构演化精细模拟；
[14] 阿里巴巴集团线下新零售业务选址、销售额预测等科研项目负责人；
[15] 委内瑞拉遥感卫星1号（VRSS-1）地面典型应用系统（TAS）技术总体负责人；
[16] 联合国环境署（UNEP）非洲水资源调查项目遥感高级应用分系统负责人；
[17] 国家“十二五”计划GF系列卫星减灾应用系统需求分析技术总体负责人；
[18] 国家深空探测计划嫦娥三号（CE-3）探月卫星遥感数据质量评价分系统负责人。
...

曾获荣誉
2017 - Now AAAG/IJGIS/CEUS/IEEE/TGIS/IJRS/EPJD/JSS 等国际权威期刊审稿人
2020 - Now Frontiers in Sustainable Cities 责任编辑
2018 - Now PLOS ONE 责任编辑
2016 - Now ESI高被引论文作者 * 7

2020 国际计算机协会 ACM SIGSPATIAL 中国新星奖
2019 国际制图学大会（ICC2019, Tokyo）GIS Session 主席
2019 指导中国地质大学（武汉）校级优秀毕业论文 * 2
2019中国地质大学信息工程学院优秀教职工
2018第七届高等院校地理信息系统（GIS）论坛优秀论文奖
2018 大学生创新创业训练计划国家级项目校级优秀奖
2018 大学生创新创业训练计划省级项目院级优秀奖
2016中国地理信息科学理论与方法学术年会优秀学生论文奖
2015中山大学“数据玩家—2015大数据信息价值挖掘大赛”一等奖
2012中国航天科技集团有限公司第五研究院骨干员工
2011武汉大学优秀毕业生（硕士）
2011武汉大学优秀硕士毕业论文
2010武汉大学优秀青年志愿者
2009中国共青团中央?中国青年志愿服务一周年证书和志愿者银质奖章
2008 武汉大学优秀毕业生（本科）
...

教育经历Education Background
工作经历Work Experience
2014.82017.12
中山大学地理科学与规划学院
地图学与地理信息系统
博士学位
2009.92011.6
武汉大学测绘学院
大地测量学与测量工程
硕士学位
2004.92008.6
武汉大学测绘学院
测绘工程
学士学位
2018.3至今
中国地质大学（武汉）
地理与信息工程学院
2018.7至今
中国城市科学研究会城市大数据专业委员会
城市大数据专业委员会
高级会员/委员
2018.7至今
阿里巴巴集团达摩院
访问****
2017.72018.1
阿里巴巴集团数据技术与产品部
算法专家
2011.72014.8
中国空间技术研究院
算法工程师
2008.92009.7
中国青年志愿者协会扶贫接力计划第十届研究生支教团

研究方向Research Focus
社会兼职Social Affiliations
人工智能和机器学习在智慧城市的应用
多源空间大数据挖掘和融合
城市空间变量及其动态变化的精细模拟
高分辨率遥感影像处理和图像理解
海量空间数据集群并行运算
2018.11至今
住建部中国城市科学研究会城市大数据专委会委员
2019.3至今
国家电网公司高级技术顾问
2018.6至今
阿里巴巴集团达摩院访问****

基本信息Personal Information 副教授硕士生导师
曾获荣誉 : 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”
性别 : 男
毕业院校 : 中山大学
学历 : 研究生(博士)毕业
学位 : 理学博士学位
在职信息 : 在职
所在单位 : 地理与信息工程学院
入职时间 : 2018年03月05日
学科 : 地理空间信息工程
办公地点 : 中国地质大学（武汉）未来城校区地理与信息工程学院521
联系方式 : yaoy@cug.edu.cn
Email :

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论文成果当前位置: 中文主页 >> 科学研究 >> 论文成果
[1]2.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检索)
[2]1.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检索)
[3]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/**.2019.**. (SCI/SSCI)
[4]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)
[5]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)
[6]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/**.2019.**. (SCI/SSCI)
[7]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.**. (SCI)
[8]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. 10.1080/**.2018.**. (SCI)
[9]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)
[10]Yao, Y*, Hong, Y.*, Li, X.* & Wu D. 2018. Estimating effects of the "Communities Opening" policy on alleviating traffic congestion in China's big cities. Computers, Environment and Urban System. DOI: 10.1016/j.compenvurbsys.2018.03.005. (SSCI).2018
[11]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检索).2018
[12]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检索).2018
[13]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检索).2018
[14]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检索).2018
[15]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, 1-22. (SCI检索).2018
[16]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检索).2018
[17]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检索).2018
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