[1] A study of urban mixed-use development in theory and practice: The case of Shanghai. Shanghai:Tongji University(2008).
[2] Extracting urban functional regions from points of interest and human activities on location-based social networks[J]. Transactions in GIS, 21, 446-467(2017).
[3] Quantification of land use diversity in the context of mixed land use[J]. Procedia-Social and Behavioral Sciences, 104, 563-572(2013).
[4] Variables communalities and dependence to factors of street system, density, and mixed land use in sustainable site design[J]. Sustainable Cities and Society, 3, 46-53(2012).
[5] 龚咏喜, 李贵才, 林姚宇. 土地利用对城市居民出行碳排放的影响研究[J]. 城市发展研究, 2013,20(9):112-118. [ Gong YX, Li GC, et al. Impact of land use on urban household travel carbon emissions[J]. Urban Development Studies, 2013,20(9):112-118. ] [ Gong Y X, Li G C, et al. Impact of land use on urban household travel carbon emissions[J]. Urban Development Studies, 2013,20(9):112-118. ]
[6] 包宇. 城市土地混合利用测度研究——以深圳市为例[J]. 湖北农业科学, 2016,55(22):5794-5797. [ BaoY. Measure of mixed urban land use: Case of Shenzhen city[J]. Hubei Agricultural Sciences, 2016,55(22):5794-5797. ] [ BaoY. Measure of mixed urban land use: Case of Shenzhen city[J]. Hubei Agricultural Sciences, 2016,55(22):5794-5797. ]
[7] Travel demand and the 3Ds: density, diversity, and design[J]. Transportation Research Part D: Transport and Environment, 2, 199-219(1997).
[8] 李苗裔, 马妍, 孙小明, 等. 基于多源数据时空熵的城市功能混合度识别评价[J]. 城市规划, 2018,42(2):97-103. [ Li MY, MaY, Sun XM. Application of spatial and temporal entropy based on multi-source data for measuring the mix degree of urban functions[J]. City Planning Review, 2018,42(2):97-103. ] [ Li M Y, Ma Y, Sun X M. Application of spatial and temporal entropy based on multi-source data for measuring the mix degree of urban functions[J]. City Planning Review, 2018,42(2):97-103. ]
[9] Entropy and Diversity[J]. Oikos, 113, 363-375(2010).
[10] Analysis of the influence of land use structure and urban vitality. Shenzhen: Shenzhen University(2016).
[11] 许思扬, 陈振光. 混合功能发展概念解读与分类探讨[J]. 规划师, 2012,28(7):105-109. [ Xu SY, Chen ZG. Interpretation and classification of mixed function development concept[J]. Planners, 2012,28(7):105-109. ] [ Xu S Y, Chen Z G. Interpretation and classification of mixed function development concept[J]. Planners, 2012,28(7):105-109. ]
[12] et alMeasurements of POI-based mixed use and their relationships with neighbourhood vibrancy[J]. International Journal of Geographical Information Systems, 31, 1-18(2016).
[13] 康朝贵, 刘瑜, 邬伦. 城市手机用户移动轨迹时空熵特征分析[J]. 武汉大学学报·信息科学版, 2017,42(1):63-69. [ Kang CG, LiuY, WuL. An analysis of entropy of human mobility from mobile phone data[J]. Geomatics and Information Science of Wuhan University, 2017,42(1):63-69. ] [ Kang C G, Liu Y, Wu L. An analysis of entropy of human mobility from mobile phone data[J]. Geomatics and Information Science of Wuhan University, 2017,42(1):63-69. ]
[14] 康雨豪, 王玥瑶, 夏竹君. 利用POI数据的武汉城市功能区划分与识别[J]. 测绘地理信息, 2018,43(1):81-85. [ Kang YH, WangYY, Xia ZZ. Identification and classification of wuhan urban districts based on POI[J]. Journal of Geomatics, 2018,43(1):81-85. ] [ Kang Y H, Wang YY, Xia Z Z. Identification and classification of wuhan urban districts based on POI[J]. Journal of Geomatics, 2018,43(1):81-85. ]
[15] Extracting hierarchical landmarks from urban POI data[J]. Journal of Remote Sensing, 15, 973-988(2011).
[16] et alQuantitative identification and visualization of urban functional area based on POI data[J]. Journal of Geomatics, 41, 68-73(2016).
[17] Identifying urban functional zones using bus smart card data and points of interest in Beijing[J]. City Planning Review, 40, 52-60(2016).
[18] Good city form[M]. Massachusetts: MIT press(1984).
[20] Probabilistic topic models[J]. IEEE Signal Processing Magazine, 27, 55-65(2010).
[21] Latent dirichletallocation[J]. Journal of Machine Learning Research, 3, 993-1022(2003).
[22] Finding scientific topics[J]. Proceedings of the National Academy of Sciences, 101, 5228-5235(2004).
[23] 刘瑜, 詹朝晖, 朱递, 等. 集成多源地理大数据感知城市空间分异格局[J]. 武汉大学学报·信息科学版, 2018,43(3):327-335. [ LiuY, Zhan ZH, ZhuD, et al. Incorporating multi-source big geo-data to sense spatial heterogeneity patterns in an urban space[J]. Geomatics and Information Science of Wuhan University, 2018,43(3):327-335. ] [ Liu Y, Zhan Z H, Zhu D, et al. Incorporating multi-source big geo-data to sense spatial heterogeneity patterns in an urban space[J]. Geomatics and Information Science of Wuhan University, 2018,43(3):327-335. ]
[24] 刘瑜. 社会感知视角下的若干人文地理学基本问题再思考[J]. 地理学报, 2016,71(4):564-575. [ LiuY. Revisiting several basic geographical concepts: A social sensing perspective[J]. Acta Geographica Sinica, 2016,71(4):564-575. ] [ Liu Y. Revisiting several basic geographical concepts: A social sensing perspective[J]. Acta Geographica Sinica, 2016,71(4):564-575. ]
[26] et alA theoretical framework and methodology for urban activity spatial structure in e-society: Empirical evidence for Nanjing city, China[J]. Chinese Geographical Science, 25, 672-683(2015).
[27] Spatial distribution characteristics of residents' emotions based on Sina Weibo big data: A case study of Nanjing[M]. Big Data Support of Urban Planning and Management. Springer, Cham, 43-62(2018).
[28] 秦萧, 甄峰. 大数据与小数据结合:信息时代城市研究方法探讨[J]. 地理科学, 2017,37(3):321-330. [ QinX, ZhenF. Combination between big data and small data: New methods of urban studies in the information era[J]. Scientia Geographica Sinica, 2017,37(3):321-330. ] [ Qin X, Zhen F. Combination between big data and small data: New methods of urban studies in the information era[J]. Scientia Geographica Sinica, 2017,37(3):321-330. ]
[29] 刘瑜, 康朝贵, 王法辉. 大数据驱动的人类移动模式和模型研究[J]. 武汉大学学报·信息科学版, 2014,39(6):660-666. [ LiuY, Kang CG, Wang FH. Towards big data-driven human mobility patterns and models[J]. Geomatics and Information Science of Wuhan University, 2014,39(6):660-666. ] [ Liu Y, Kang C G, Wang F H. Towards big data-driven human mobility patterns and models[J]. Geomatics and Information Science of Wuhan University, 2014,39(6):660-666. ]
[30] 陈瑗瑗, 高勇. 利用社交媒体的位置潜语义特征提取与分析[J]. 地球信息科学学报, 2017,19(11):1405-1414. [ Chen YY, GaoY. Extracting and analyzing latent semantic characteristics of locations using social media data. Journal of Geo-informationScience, 2017,19(11):1405-1414. ] [ Chen Y Y, Gao Y.Extracting and analyzing latent semantic characteristics of locations using social media data. Journal of Geo-information Science, 2017,19(11):1405-1414. ]
[31] . Statistical learning methods, second edition(2019).
[32] 陈泽东, 谯博文, 张晶. 基于居民出行特征的北京城市功能区识别与空间交互研究[J]. 地球信息科学学报, 2018,20(3):291-301. [ Chen ZD, Qiao BW, ZhangJ. Identification and spatial interaction of urban functional regions in Beijing based on the characteristics of residents' traveling[J]. Journal of Geo-information Science, 2018,20(3):291-301. ] [ Chen Z D, Qiao B W, Zhang J. Identification and spatial interaction of urban functional regions in Beijing based on the characteristics of residents' traveling[J]. Journal of Geo-information Science, 2018,20(3):291-301. ]
