[1] TU W, HU Z W, LI L F, et al.Portraying urban functional zones by coupling remote sensing imagery and human sensing data[J].Remote Sensing, 2018, 10(1):141. [2] BAO H Q, MING D P, GUO Y, et al.DFCNN-based semantic recognition of urban functional zones by integrating remote sensing data and POI data[J].Remote Sensing, 2020, 12(7):1088. [3] ZHANG X Y, DU S H, WANG Q.Hierarchical semantic cognition for urban functional zones with VHR satellite images and POI data[J].ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 132:170-184. [4] MATSUOKA R H, KAPLAN R.People needs in the urban landscape:analysis of landscape and urban planning contributions[J].Landscape and Urban Planning, 2008, 84(1):7-19. [5] MONTANGES A P, MOSER G, TAUBENBÖCK H, et al.Classification of urban structural types with multisource data and structured models[C]//Proceedings of JURSE'15.Washington D.C., USA:IEEE Press, 2015:1-4. [6] HEIDEN U, HELDENS W, ROESSNER S, et al.Urban structure type characterization using hyperspectral remote sensing and height information[J].Landscape and Urban Planning, 2012, 105(4):361-375. [7] FAN J, TAO A J, REN Q.On the historical background, scientific intentions, goal orientation, and policy framework of major function-oriented zone planning in China[J].Journal of Resources and Ecology, 2010, 1(4):289-299. [8] 陈占龙, 周路林, 禹文豪, 等.顾及兴趣点潜在上下文关系的城市功能区识别[J].测绘学报, 2020, 49(7):907-920. CHEN Z L, ZHOU L L, YU W H, et al.Identification of the urban functional regions considering the potential context of interest points[J].Acta Geodaetica et Cartographica Sinica, 2020, 49(7):907-920.(in Chinese) [9] CAO R, TU W, YANG C X, et al.Deep learning-based remote and social sensing data fusion for urban region function recognition[J].ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 163:82-97. [10] XIA J M, DING Y, TAN L.Urban remote sensing scene recognition based on lightweight convolution neural network[J].IEEE Access, 2021, 9:26377-26387. [11] DU S J, DU S H, LIU B, et al.Large-scale urban functional zone mapping by integrating remote sensing images and open social data[J].GIScience & Remote Sensing, 2020, 57(3):411-430. [12] JIANG Z, EVANS M, OLIVER D, et al.Identifying K primary corridors from urban bicycle GPS trajectories on a road network[J].Information Systems, 2016, 57:142-159. [13] ZHANG F S, JIN B H, WANG Z Y, et al.On geocasting over urban bus-based networks by mining trajectories[J].IEEE Transactions on Intelligent Transportation Systems, 2016, 17(6):1734-1747. [14] QIAN Z, LIU X T, TAO F, et al.Identification of urban functional areas by coupling satellite images and taxi GPS trajectories[J].Remote Sensing, 2020, 12(15):2449. [15] YUAN J, ZHENG Y, XIE X.Discovering regions of different functions in a city using human mobility and POIs[C]//Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York, USA:ACM Press, 2012:186-194. [16] GONZÁLEZ M C, HIDALGO C A, BARABÁSI A L.Understanding individual human mobility patterns[J].Nature, 2008, 453(7196):779-782. [17] PEI T, SOBOLEVSKY S, RATTI C, et al.A new insight into land use classification based on aggregated mobile phone data[J].International Journal of Geographical Information Science, 2014, 28(9):1988-2007. [18] 江贵林, 胡访宇, 石立兴.基于呼叫详细记录数据的城市功能区识别[J].计算机应用, 2016, 36(7):2046-2050. JIANG G L, HU F Y, SHI L X.Urban functional area identification based on call detail record data[J].Journal of Computer Applications, 2016, 36(7):2046-2050.(in Chinese) [19] TU W, CAO J Z, YUE Y, et al.Coupling mobile phone and social media data:a new approach to understanding urban functions and diurnal patterns[J].International Journal of Geographical Information Science, 2017, 31(12):2331-2358. [20] JIA Y X, GE Y, LING F, et al.Urban land use mapping by combining remote sensing imagery and mobile phone positioning data[J].Remote Sensing, 2018, 10(3):446. [21] BIRANT D, KUT A.ST-DBSCAN:an algorithm for clustering spatial-temporal data[J].Data & Knowledge Engineering, 2007, 60(1):208-221. [22] LEO B.Random forests[J].Machine Learning, 2001, 45(1):5-32. [23] PRAAGMAN J.Classification and regression trees:Leo BREIMAN, Jerome H.FRIEDMAN, Richard A.OLSHEN and Charles J.STONE The Wadsworth Statistics/Probability Series, Wadsworth, Belmont, 1984, x +358 pages[J].European Journal of Operational Research, 1985, 19(1):144. [24] ELOMAA T, MANNILA H, TOIVONEN H.Machine Learning[C]//Proceedings of the 13th European Conference on Machine Learning.Berlin, Heidelberg:Springer, 2002:1-5. [25] KIBRIYA A M, FRANK E, PFAHRINGER B, et al.Multinomial Naive Bayes for text categorization revisited[M]//WEBB G I, YU X.AI 2004:advances in artificial intelligence.Berlin, Germany:Springer, 2004:488-499. [26] ZHANG M L, ZHOU Z H.ML-KNN:a lazy learning approach to multi-label learning[J].Pattern Recognition, 2007, 40(7):2038-2048. [27] HOSMER D W, LEMESHOW S, STURDIVANT R X.Applied logistic regression[M].[S.l.]:Wiley, 2013. [28] MASON L, BAXTER J, BARTLETT P, et al.Boosting algorithms as gradient descent in function space[EB/OL].[2021-05-10].https://www.researchgate.net/profile/Marcus-Frean/publication/2750572_Boosting_Algorithms_as_Gradient_Descent_in_Function_Space/links/09e4150617c0848d46000000/Boosting-Algorithms-as-Gradient-Desc ent-in-Function-Space.pdf?origin=publication_detail. |