24.3.15 Large Scale Models, City Scale Models, City Models

Chapter Contents (Back)
City Models. How to represent them:
See also GIS Implementation, City Models, Urban Models, City Data.
See also Cultural Heritage Sites, Modeling, Analysis, Large Scale Models.
See also GIS: Cadastral Data Storage and Use.
See also CityGML. Smart City related models:
See also Smart City Tools, Models.

Murai, S.,
Generation of 3D City Models in Japan: An Overview,
Ascona01(59-64). Modeling from 3D images. 0201
BibRef

Haala, N., and Hahn, M.,
Data Fusion for the Detection and Reconstruction of Buildings,
Ascona95(211-220). Combine range (DTM, etc.) with stereo and image data to get a good model for the building. BibRef 9500

Haala, N.[Norbert], Böhm, J.[Jan], Kada, M.[Martin],
Processing of 3D Building Models for Location Aware Applications,
PCV02(A: 138). 0305
BibRef

Haala, N.[Norbert], Böhm, J.[Jan],
A multi-sensor system for positioning in urban environments,
PandRS(58), No. 1, June 2003, pp. 31-42.
Elsevier DOI 0307
BibRef

Haala, N.[Norbert], Anders, K.H.[Karl-Heinrich],
Acquisition of 3D Urban Models by Analysis of Aerial Images, Digital Surface Models, and Existing 2D Building Information,
SPIE(3072), April 1997, pp. 212-222. BibRef 9704

Haala, N.[Norbert], Brenner, C.[Claus],
Interpretation of Urban Surface Models Using 2d Building Information,
CVIU(72), No. 2, November 1998, pp. 204-214.
DOI Link BibRef 9811
Earlier: Ascona97(213-222). BibRef

Haala, N.[Norbert], Brenner, C.[Claus],
Virtual City Models from Laser Altimeter and 2D Map Data,
PhEngRS(65), No. 7, July 1999, pp. 787. Use 2D ground plans and a laser digital surface model to derive 3D building geometry BibRef 9907

Haala, N.[Norbert], Brenner, C.[Claus],
Extraction of buildings and trees in urban environments,
PandRS(54), No. 2-3, July 1999, pp. 130-137. In the laser scanner issue. Using range data. BibRef 9907

Haala, N.[Norbert], Kada, M.[Martin],
An update on automatic 3D building reconstruction,
PandRS(65), No. 6, November 2010, pp. 570-580.
Elsevier DOI 1101
Reconstruction; Three-dimensional; Building; Urban; Automation BibRef

Brenner, C., Haala, N., Fritsch, D.[Diter],
Towards Fully Automated 3D City Model Generation,
Ascona01(47-57). Integrate 2-D surface models (maps) with 3D digital surface models. Generate surfaces in 3D data, force to polygonal shapes. 0201
BibRef

Brenner, C.,
Constraints for Modelling Complex Objects,
CMRT05(xx-yy).
PDF File. 0508
BibRef

Böhm, J., Haala, N.,
Efficient integration of aerial and terrestrial laser data for virtual city modeling using lasermaps,
Laser05(xx-yy).
PDF File. 0509
BibRef

Grejner-Brzezinska, D.A.[Dorota A.], Li, R.[Ron], Haala, N.[Norbert], Toth, C.K.[Charles K.],
From Mobile Mapping to Telegeoinformatics: Paradigm Shift in Geospatial Data Acquisition, Processing, and Management,
PhEngRS(70), No. 2, February 2004, pp. 197-210.
WWW Link. The mobile mapping systems paradigm has shifted from the post-mission to near-real-time systems due to the technological advances in positioning and imaging sensors, combined with the explosion in wireless mobile communication systems. 0403
BibRef

Kada, M.[Martin], McKinley, L.,
3D Building Reconstruction from Lidar Based on a Cell Decomposition Approach,
CMRT09(47-52).
PDF File. 0909
BibRef

Haala, N.[Norbert], Becker, S.[Susanne], Kada, M.[Martin],
Cell Decomposition for the Generation of Building Models at Multiple Scales,
PCV06(xx-yy).
PDF File. 0609

See also Grammar Supported Facade Reconstruction from Mobile Lidar Mapping. BibRef

Portales, C.[Cristina], Lerma, J.L.[Jose Luis], Navarro, S.[Santiago],
Augmented reality and photogrammetry: A synergy to visualize physical and virtual city environments,
PandRS(65), No. 1, January 2010, pp. 134-142.
Elsevier DOI 1001
Augmented reality; Model; Multisensor; Tracking; Navigation; Real time BibRef

Lerma, J.L., Navarro, S., Cabrelles, M., Portalès, C.,
Implementation of an Architectonic GIS on a Brickwork Farmhouse,
ISPRS08(B5: 1013 ff).
PDF File. 0807
BibRef

Poullis, C.[Charalambos], You, S.[Suya],
Photorealistic Large-Scale Urban City Model Reconstruction,
VCG(15), No. 4, July-August 2009, pp. 654-669.
IEEE DOI 0905
BibRef
Earlier:
Automatic Creation of Massive Virtual Cities,
VR09(199-202).
IEEE DOI 0905
Interactive reconstruction of buildings with linear and nonlinear surfaces, and a rendering engine to take advantage of the models. BibRef

Poullis, C.[Charalambos],
Large-Scale Urban Reconstruction with Tensor Clustering and Global Boundary Refinement,
PAMI(42), No. 5, May 2020, pp. 1132-1145.
IEEE DOI 2004
Laser radar, Buildings, Data mining, Solid modeling, Measurement, Tensor clustering, boundary refinement BibRef

Poullis, C.[Charalambos], You, S.[Suya],
3D Reconstruction of Urban Areas,
3DIMPVT11(33-40).
IEEE DOI 1109
BibRef
Earlier:
Automatic reconstruction of cities from remote sensor data,
CVPR09(2775-2782).
IEEE DOI 0906

See also Vision-Based System For Automatic Detection and Extraction Of Road Networks, A. BibRef

Poullis, C., You, S., and Neumann, U.,
Rapid Creation of Large-Scale Photorealistic Virtual Environments,
VR08(153-160).
IEEE DOI 0905
BibRef

Wang, L.[Lu], You, S.[Suya], Neumann, U.[Ulrich],
Large-Scale Urban Modeling by Combining Ground Level Panoramic and Aerial Imagery,
3DPVT06(806-813).
IEEE DOI 0606
BibRef

Hu, J.H.[Jin-Hui], You, S.[Suya], Neumann, U.[Ulrich],
Integrating LiDAR, Aerial Image and Ground Images for Complete Urban Building Modeling,
3DPVT06(184-191).
IEEE DOI 0606
BibRef

Zhou, Q.Y.[Qian-Yi], Neumann, U.[Ulrich],
2.5D building modeling by discovering global regularities,
CVPR12(326-333).
IEEE DOI 1208
BibRef
Earlier:
2.5D building modeling with topology control,
CVPR11(2489-2496).
IEEE DOI 1106
BibRef
Earlier:
2.5D Dual Contouring: A Robust Approach to Creating Building Models from Aerial LiDAR Point Clouds,
ECCV10(III: 115-128).
Springer DOI 0109
BibRef

Agarwal, S.[Sameer], Furukawa, Y.[Yasutaka], Snavely, N.[Noah], Curless, B.[Brian], Seitz, S.M.[Steven M.], Szeliski, R.S.[Richard S.],
Reconstructing Rome,
Computer(43), No. 6, June 2010, pp. 40-47.
IEEE DOI 1007
BibRef

Agarwal, S.[Sameer], Furukawa, Y.[Yasutaka], Snavely, N.[Noah], Simon, I.[Ian], Curless, B.[Brian], Seitz, S.M.[Steven M.], Szeliski, R.S.[Richard S.],
Building Rome in a Day,
CACM(54), No. 10, October 2011, pp. 105-112.
DOI Link 1110
BibRef
Earlier: A1, A3, A4, A6, A7, Only:
Building Rome in a day,
ICCV09(72-79).
IEEE DOI Award, Helmholtz Prize. 0909
We present a system that can reconstruct 3D geometry from large, unorganized collections of photographs. Our experimental results demonstrate that it is possible to reconstruct city-scale image collections with more than a hundred thousand images. BibRef

Lafarge, F.[Florent], Mallet, C.[Clément],
Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation,
IJCV(99), No. 1, August 2012, pp. 69-85.
WWW Link. 1202
BibRef
Earlier:
Building large urban environments from unstructured point data,
ICCV11(1068-1075).
IEEE DOI 1201
City models from unstructed point data. Building, trees and complex surfaces. BibRef

Mallet, C., Soergel, U., Bretar, F.,
Analysis of Full-Waveform LIDAR Data for an Accurate Classification of Urban Areas,
ISPRS08(B3a: 85 ff).
PDF File. 0807
BibRef

Guo, L.[Li], Chehata, N.[Nesrine], Mallet, C.[Clement], Boukir, S.[Samia],
Relevance of airborne lidar and multispectral image data for urban scene classification using Random Forests,
PandRS(66), No. 1, January 2011, pp. 56-66.
Elsevier DOI 1101
BibRef
Earlier: A1, A2, A4, Only:
A two-pass random forests classification of airborne lidar and image data on urban scenes,
ICIP10(1369-1372).
IEEE DOI 1009
Lidar; Multispectral image; Urban; Random forests; Variable importance BibRef

Zhao, J.Q.[Jun-Qiao], Zhu, Q.[Qing], Du, Z.Q.[Zhi-Qiang], Feng, T.T.[Tian-Tian], Zhang, Y.T.[Ye-Ting],
Mathematical morphology-based generalization of complex 3D building models incorporating semantic relationships,
PandRS(68), No. 1, March 2012, pp. 95-111.
Elsevier DOI 1204
Generalization; Complex 3D building; Mathematical morphology; Levels of Detail; Semantic relationships BibRef

Zhu, Q.[Qing], Zhao, J.Q.[Jun-Qiao], Du, Z.Q.[Zhi-Qiang], Zhang, Y.T.[Ye-Ting], Xu, W.P.[Wei-Ping], Xie, X.[Xiao], Ding, Y.L.[Yu-Lin], Wang, F.[Fei], Wang, T.S.[Ting-Song],
Towards Semantic 3D City Modeling and Visual Explorations,
GeoInfo10(xx-yy).
PDF File. 1011
BibRef

Jedrzejas, T.[Thomas], Przybilla, H.J.[Heinz-Jürgen],
Generating Historical Urban 3D-Scenarios for Use in Google Earth Representing the Medieval City of Duisburg,
PFG(2009), No. 3, 2009, pp. 199-207.
WWW Link. 1211
BibRef

Semmo, A.[Amir], Hildebrandt, D.[Dieter], Trapp, M.[Matthias], Döllner, J.[Jürgen],
Concepts for Cartography-Oriented Visualization of Virtual 3D City Models,
PFG(2012), No. 4, 2012, pp. 455-465.
WWW Link. 1211
BibRef

Römer, C.[Christoph], Plümer, L.[Lutz],
Identifying Architectural Style in 3D City Models with Support Vector Machines,
PFG(2010), No. 5, 2010, pp. 371-384.
WWW Link. 1211
BibRef

Byelozyorov, S.[Sergiy], Jochem, R.[Rainer], Pegoraro, V.[Vincent], Slusallek, P.[Philipp],
From real cities to virtual worlds using an open modular architecture,
VC(29), No. 2, February 2013, pp. 141-153.
WWW Link. 1302
BibRef

Huang, X., Liu, H., Zhang, L.,
Spatiotemporal Detection and Analysis of Urban Villages in Mega City Regions of China Using High-Resolution Remotely Sensed Imagery,
GeoRS(53), No. 7, July 2015, pp. 3639-3657.
IEEE DOI 1503
Buildings BibRef

Ohori, K.A.[Ken Arroyo], Ledoux, H.[Hugo], Biljecki, F.[Filip], Stoter, J.[Jantien],
Modeling a 3D City Model and Its Levels of Detail as a True 4D Model,
IJGI(4), No. 3, 2015, pp. 1055.
DOI Link 1507
BibRef

Snavely, N.[Noah],
Technical Perspective: Paris Beyond Frommer's,
CACM(58), No. 12, December 2015, pp. 102.
DOI Link 1601
BibRef

Doersch, C.[Carl], Singh, S.[Saurabh], Gupta, A.[Abhinav], Sivic, J.[Josef], Efros, A.A.[Alexei A.],
What Makes Paris Look Like Paris?,
CACM(58), No. 12, December 2015, pp. 103-110.
DOI Link 1601
BibRef

Sargent, I.[Isabel], Holland, D.[David], Harding, J.[Jenny],
The Building Blocks of User-Focused 3D City Models,
IJGI(4), No. 4, 2015, pp. 2890.
DOI Link 1601
BibRef

Biljecki, F.[Filip], Stoter, J.[Jantien], Ledoux, H.[Hugo], Zlatanova, S.[Sisi], Çöltekin, A.[Arzu],
Applications of 3D City Models: State of the Art Review,
IJGI(4), No. 4, 2015, pp. 2842.
DOI Link 1601
BibRef

Sakurada, K.[Ken], Okatani, T.[Takayuki], Kitani, K.M.[Kris M.],
Hybrid macro-micro visual analysis for city-scale state estimation,
CVIU(146), No. 1, 2016, pp. 86-98.
Elsevier DOI 1604
City-scale BibRef

Hartmann, A.[André], Meinel, G.[Gotthard], Hecht, R.[Robert], Behnisch, M.[Martin],
A Workflow for Automatic Quantification of Structure and Dynamic of the German Building Stock Using Official Spatial Data,
IJGI(5), No. 8, 2016, pp. 142.
DOI Link 1609
BibRef

Larnaout, D.[Dorra], Gay-Bellile, V.[Vincent], Bourgeois, S.[Steve], Dhome, M.[Michel],
Fast and automatic city-scale environment modelling using hard and/or weak constrained bundle adjustments,
MVA(27), No. 5, August 2016, pp. 943-962.
Springer DOI 1609
BibRef

Liang, J.M.[Jian-Ming], Gong, J.H.[Jian-Hua], Liu, J.[Jin], Zou, Y.L.[Yu-Ling], Zhang, J.M.[Jin-Ming], Sun, J.[Jun], Chen, S.S.[Shui-Sen],
Generating Orthorectified Multi-Perspective 2.5D Maps to Facilitate Web GIS-Based Visualization and Exploitation of Massive 3D City Models,
IJGI(5), No. 11, 2016, pp. 212.
DOI Link 1612
BibRef

Tutzauer, P.[Patrick], Becker, S.[Susanne], Fritsch, D.[Dieter], Niese, T.[Till], Deussen, O.[Oliver],
A Study of the Human Comprehension of Building Categories Based on Different 3D Building Representations,
PFG(2016), No. 5-6, 2016, pp. 319-333.
DOI Link 1703
BibRef
Earlier: A1, A2, A4, A5, A3:
Understanding Human Perception Of Building Categories In Virtual 3d Cities - A User Study,
ISPRS16(B2: 683-687).
DOI Link 1610
BibRef

Rumpler, M.[Markus], Tscharf, A.[Alexander], Mostegel, C.[Christian], Daftry, S.[Shreyansh], Hoppe, C.[Christof], Prettenthaler, R.[Rudolf], Fraundorfer, F.[Friedrich], Mayer, G.[Gerhard], Bischof, H.[Horst],
Evaluations on multi-scale camera networks for precise and geo-accurate reconstructions from aerial and terrestrial images with user guidance,
CVIU(157), No. 1, 2017, pp. 255-273.
Elsevier DOI 1704
Photogrammetric computer vision BibRef

Tateno, K.[Keisuke], Tombari, F.[Federico], Navab, N.[Nassir],
Large scale and long standing simultaneous reconstruction and segmentation,
CVIU(157), No. 1, 2017, pp. 138-150.
Elsevier DOI 1704
Dense SLAM BibRef

Schöps, T.[Thomas], Sattler, T.[Torsten], Häne, C.[Christian], Pollefeys, M.[Marc],
Large-scale outdoor 3D reconstruction on a mobile device,
CVIU(157), No. 1, 2017, pp. 151-166.
Elsevier DOI 1704
Dense 3D reconstruction BibRef

Zhu, J.[Jie], Sun, Y.Z.[Yi-Zhong],
Building an Urban Spatial Structure from Urban Land Use Data: An Example Using Automated Recognition of the City Centre,
IJGI(6), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Virtanen, J.P.[Juho-Pekka], Kukko, A.[Antero], Kaartinen, H.[Harri], Jaakkola, A.[Anttoni], Turppa, T.[Tuomas], Hyyppä, H.[Hannu], Hyyppä, J.[Juha],
Nationwide Point Cloud: The Future Topographic Core Data,
IJGI(6), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Zhu, L.L.[Ling-Li], Kukko, A.[Antero], Virtanen, J.P.[Juho-Pekka], Hyyppä, J.[Juha], Kaartinen, H.[Harri], Hyyppä, H.[Hannu], Turppa, T.[Tuomas],
Multisource Point Clouds, Point Simplification and Surface Reconstruction,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Babahajiani, P.[Pouria], Fan, L.X.[Li-Xin], Kämäräinen, J.K.[Joni-Kristian], Gabbouj, M.[Moncef],
Urban 3D segmentation and modelling from street view images and LiDAR point clouds,
MVA(28), No. 7, October 2017, pp. 679-694.
Springer DOI 1710
BibRef

Potje, G.[Guilherme], Resende, G.[Gabriel], Campos, M.[Mario], Nascimento, E.R.[Erickson R.],
Towards an efficient 3D model estimation methodology for aerial and ground images,
MVA(28), No. 8, November 2017, pp. 937-952.
Springer DOI 1710
BibRef

Gao, X.[Xiang], Hu, L.H.[Li-Hua], Cui, H.N.[Hai-Nan], Shen, S.H.[Shu-Han], Hu, Z.Y.[Zhan-Yi],
Accurate and efficient ground-to-aerial model alignment,
PR(76), No. 1, 2018, pp. 288-302.
Elsevier DOI 1801
3D reconstruction of a large-scale architectural scene. Image based modeling. Use ground model. BibRef

Zhou, Y., Shen, S.H.[Shu-Han], Gao, X.[Xiang], Hu, L.H.[Li-Hua],
Accurate mesh-based alignment for ground and aerial multi-view stereo models,
ICIP17(2627-2631)
IEEE DOI 1803
Cameras, Computational modeling, Feature extraction, Image reconstruction, Reliability, Skeleton, Skeleton Facet Set BibRef

Liang, L.[Lei], Li, X.[Xinwu], Ferro-Famil, L.[Laurent], Guo, H.D.[Hua-Dong], Zhang, L.[Lu], Wu, W.J.[Wen-Jin],
Urban Area Tomography Using a Sparse Representation Based Two-Dimensional Spectral Analysis Technique,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Julin, A.[Arttu], Jaalama, K.[Kaisa], Virtanen, J.P.[Juho-Pekka], Pouke, M.[Matti], Ylipulli, J.[Johanna], Vaaja, M.[Matti], Hyyppä, J.[Juha], Hyyppä, H.[Hannu],
Characterizing 3D City Modeling Projects: Towards a Harmonized Interoperable System,
IJGI(7), No. 2, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Zhang, L.Q.[Li-Qiang], Zhang, L.[Liang],
Deep Learning-Based Classification and Reconstruction of Residential Scenes From Large-Scale Point Clouds,
GeoRS(56), No. 4, April 2018, pp. 1887-1897.
IEEE DOI 1804
Buildings, Feature extraction, Image reconstruction, Semantics, Shape, Solid modeling, Classification, reconstruction BibRef

Zhang, L.Q.[Li-Qiang], Li, Z.Q.[Zhu-Qiang], Li, A.J.[An-Jian], Liu, F.Y.[Fang-Yu],
Large-scale urban point cloud labeling and reconstruction,
PandRS(138), 2018, pp. 86-100.
Elsevier DOI 1804
ReLu-NN, Point cloud parsing, Building reconstruction BibRef

He, X.J.[Xian-Jin], Zhang, X.C.[Xin-Chang], Yang, J.[Jie],
Progressive Amalgamation of Building Clusters for Map Generalization Based on Scaling Subgroups,
IJGI(7), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Wolberg, G.[George], Zokai, S.[Siavash],
PhotoSketch: a photocentric urban 3D modeling system,
VC(34), No. 5, May 2018, pp. 605-616.
WWW Link. 1804
BibRef

Neuville, R.[Romain], Pouliot, J.[Jacynthe], Poux, F.[Florent], de Rudder, L.[Laurent], Billen, R.[Roland],
A Formalized 3D Geovisualization Illustrated to Selectivity Purpose of Virtual 3D City Model,
IJGI(7), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Huang, X., Hu, T., Li, J., Wang, Q., Benediktsson, J.A.,
Mapping Urban Areas in China Using Multisource Data With a Novel Ensemble SVM Method,
GeoRS(56), No. 8, August 2018, pp. 4258-4273.
IEEE DOI 1808
environmental monitoring (geophysics), geophysical image processing, remote sensing, urban mapping BibRef

Silva de Araujo, A.[Agnes], Pereira de Queiroz, A.[Alfredo],
Spatial Characterization and Mapping of Gated Communities,
IJGI(7), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Buyukdemircioglu, M.[Mehmet], Kocaman, S.[Sultan], Isikdag, U.[Umit],
Semi-Automatic 3D City Model Generation from Large-Format Aerial Images,
IJGI(7), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Agius, T.[Tyler], Sabri, S.[Soheil], Kalantari, M.[Mohsen],
Three-Dimensional Rule-Based City Modelling to Support Urban Redevelopment Process,
IJGI(7), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Conte, P.[Paolo], Girelli, V.A.[Valentina A.], Mandanici, E.[Emanuele],
Structure from Motion for aerial thermal imagery at city scale: Pre-processing, camera calibration, accuracy assessment,
PandRS(146), 2018, pp. 320-333.
Elsevier DOI 1812
Aerial thermography, Geometric calibration, Structure from Motion, Orthomosaicking, 00-01, 99-00 BibRef

Murshed, S.M.[Syed Monjur], Picard, S.[Solène], Koch, A.[Andreas],
Modelling, Validation and Quantification of Climate and Other Sensitivities of Building Energy Model on 3D City Models,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Joo, K.[Kyungdon], Oh, T.H.[Tae-Hyun], Kim, J.[Junsik], Kweon, I.S.[In So],
Robust and Globally Optimal Manhattan Frame Estimation in Near Real Time,
PAMI(41), No. 3, March 2019, pp. 682-696.
IEEE DOI 1902
BibRef
Earlier:
Globally Optimal Manhattan Frame Estimation in Real-Time,
CVPR16(1763-1771)
IEEE DOI 1612
Estimation, Robustness, Real-time systems, Complexity theory, Stability analysis, Gravity, vanishing point estimation. Using surface normals. BibRef

Joo, K.[Kyungdon], Oh, T.H.[Tae-Hyun], Kweon, I.S.[In So], Bazin, J.C.[Jean-Charles],
Globally Optimal Inlier Set Maximization for Atlanta World Understanding,
PAMI(42), No. 10, October 2020, pp. 2656-2669.
IEEE DOI 2009
BibRef
Earlier:
Globally Optimal Inlier Set Maximization for Atlanta Frame Estimation,
CVPR18(5726-5734)
IEEE DOI 1812
Estimation, Gravity, Cameras, Lasers, Optimization, Layout, Atlanta frame, RGB-D image, branch-and-bound, scene understanding. Buildings. BibRef

Wang, W.[Wei], Gao, W.[Wei],
Efficient multi-plane extraction from massive 3D points for modeling large-scale urban scenes,
VC(35), No. 5, May 2019, pp. 625-638.
WWW Link. 1906
BibRef

Cai, W.[Wei], Wen, X.D.[Xiao-Dong], Tu, Q.[Qiu], Guo, X.J.[Xiu-Juan],
Research on image processing of intelligent building environment based on pattern recognition technology,
JVCIR(61), 2019, pp. 141-148.
Elsevier DOI 1906
Intelligent building, Image processing, Satellite imagery, Building contours, Edge detection BibRef

Antón, D.[Daniel], Pineda, P.[Paloma], Medjdoub, B.[Benachir], Iranzo, A.[Alfredo],
As-Built 3D Heritage City Modelling to Support Numerical Structural Analysis: Application to the Assessment of an Archaeological Remain,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Strek, Z.[Zanna], Noga, K.[Karol],
Method of Delimiting the Spatial Structure of Villages for the Purposes of Land Consolidation and Exchange,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Xia, N.[Nan], Cheng, L.[Liang], Li, M.C.[Man-Chun],
Mapping Urban Areas Using a Combination of Remote Sensing and Geolocation Data,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Feng, Y.[Yu], Thiemann, F.[Frank], Sester, M.[Monika],
Learning Cartographic Building Generalization with Deep Convolutional Neural Networks,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Liu, S.[Sheng'en], Yi, H.[Hui], Chen, X.N.[Xiang-Ning], Wang, D.C.[De-Cheng], Jin, W.[Wei],
Multifaceted Geometric Assessment towards Simplified Urban Surfaces Built by 3D Reconstruction,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Guzzetti, F., Anyabolu, K.L.N., d'Ambrosio, L., Marchetti, G.,
Built Environment: Modelling The Urban Space,
GEORES19(595-600).
DOI Link 1912
BibRef

Li, S.Y.[Si-Yi], Li, W.J.[Wen-Jing], Lin, Z.Y.[Zhi-Yong], Yi, S.J.[Sheng-Jie],
Method for 3D City Building Continuous Transformation Based on an Improved LOD Topological Data Structure,
IJGI(8), No. 11, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Lu, C.Y.[Chen-Yu], Pang, M.[Min], Zhang, Y.[Yang], Li, H.J.[Heng-Ji], Lu, C.P.[Cheng-Peng], Tang, X.L.[Xiang-Long], Cheng, W.[Wei],
Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Lee, J.W.[Ji-Won], Min, K.H.[Ki-Hong], Lee, Y.H.[Young-Hee], Lee, G.[GyuWon],
X-Net-Based Radar Data Assimilation Study over the Seoul Metropolitan Area,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Gibril, M.B.A.[Mohamed Barakat A.], Kalantar, B.[Bahareh], Al-Ruzouq, R.[Rami], Ueda, N.[Naonori], Saeidi, V.[Vahideh], Shanableh, A.[Abdallah], Mansor, S.[Shattri], Shafri, H.Z.M.[Helmi Z. M.],
Mapping Heterogeneous Urban Landscapes from the Fusion of Digital Surface Model and Unmanned Aerial Vehicle-Based Images Using Adaptive Multiscale Image Segmentation and Classification,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Kim, S.[Suzi], Kim, D.[Dodam], Choi, S.[Sunghee],
CityCraft: 3D virtual city creation from a single image,
VC(36), No. 5, May 2020, pp. 911-924.
WWW Link. 2005
BibRef

Huang, R.[Rong], Xu, Y.S.[Yu-Sheng], Hong, D.F.[Dan-Feng], Yao, W.[Wei], Ghamisi, P.[Pedram], Stilla, U.[Uwe],
Deep point embedding for urban classification using ALS point clouds: A new perspective from local to global,
PandRS(163), 2020, pp. 62-81.
Elsevier DOI 2005
Semantic labeling, ALS point cloud, Deep learning, Feature embedding, Manifold learning, Graph optimization BibRef

Wagner, F.H.[Fabien H.], Dalagnol, R.[Ricardo], Tarabalka, Y.[Yuliya], Segantine, T.Y.F.[Tassiana Y. F.], Thomé, R.[Rogério], Hirye, M.C.M.[Mayumi C. M.],
U-Net-Id, an Instance Segmentation Model for Building Extraction from Satellite Images: Case Study in the Joanópolis City, Brazil,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Zhu, J.W.[Jing-Wei], Gehrung, J.[Joachim], Huang, R.[Rong], Borgmann, B.[Björn], Sun, Z.H.[Zheng-Hao], Hoegner, L.[Ludwig], Hebel, M.[Marcus], Xu, Y.S.[Yu-Sheng], Stilla, U.[Uwe],
TUM-MLS-2016: An Annotated Mobile LiDAR Dataset of the TUM City Campus for Semantic Point Cloud Interpretation in Urban Areas,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Yang, N.[Naisen], Tang, H.[Hong],
GeoBoost: An Incremental Deep Learning Approach toward Global Mapping of Buildings from VHR Remote Sensing Images,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Zhang, X.Y.[Xue-Yan],
Village-Level Homestead and Building Floor Area Estimates Based on UAV Imagery and U-Net Algorithm,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Esch, T.[Thomas], Zeidler, J.[Julian], Palacios-Lopez, D.[Daniela], Marconcini, M.[Mattia], Roth, A.[Achim], Mönks, M.[Milena], Leutner, B.[Benjamin], Brzoska, E.[Elisabeth], Metz-Marconcini, A.[Annekatrin], Bachofer, F.[Felix], Loekken, S.[Sveinung], Dech, S.[Stefan],
Towards a Large-Scale 3D Modeling of the Built Environment: Joint Analysis of TanDEM-X, Sentinel-2 and Open Street Map Data,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Jovanovic, D.[Dušan], Milovanov, S.[Stevan], Ruskovski, I.[Igor], Govedarica, M.[Miro], Sladic, D.[Dubravka], Radulovic, A.[Aleksandra], Pajic, V.[Vladimir],
Building Virtual 3D City Model for Smart Cities Applications: A Case Study on Campus Area of the University of Novi Sad,
IJGI(9), No. 8, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Xue, F.[Fan], Lu, W.S.[Wei-Sheng], Chen, Z.[Zhe], Webster, C.J.[Christopher J.],
From LiDAR point cloud towards digital twin city: Clustering city objects based on Gestalt principles,
PandRS(167), 2020, pp. 418-431.
Elsevier DOI 2008
LiDAR, Digital Twin City (DTC), Gestalt principles, Hierarchical clustering, Symmetry, Cross-section BibRef

Chen, W.[Wei], Zhou, Y.Y.[Yu-Yu], Wu, Q.S.[Qiu-Sheng], Chen, G.[Gang], Huang, X.[Xin], Yu, B.[Bailang],
Urban Building Type Mapping Using Geospatial Data: A Case Study of Beijing, China,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Zheng, X.W.[Xian-Wei], Huan, L.X.[Lin-Xi], Xia, G.S.[Gui-Song], Gong, J.Y.[Jian-Ya],
Parsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss,
PandRS(170), 2020, pp. 15-28.
Elsevier DOI 2011
Semantic segmentation, Convolutional neural network (ConvNet), Edge-aware loss BibRef

Wurm, M.[Michael], Droin, A.[Ariane], Stark, T.[Thomas], Geiß, C.[Christian], Sulzer, W.[Wolfgang], Taubenböck, H.[Hannes],
Deep Learning-Based Generation of Building Stock Data from Remote Sensing for Urban Heat Demand Modeling,
IJGI(10), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Li, M.L.[Ming-Lei], Nan, L.L.[Liang-Liang],
Feature-preserving 3D mesh simplification for urban buildings,
PandRS(173), 2021, pp. 135-150.
Elsevier DOI 2102
Urban modelling, Mesh simplification, Mesh filtering, Edge collapse BibRef

Neupane, B.[Bipul], Horanont, T.[Teerayut], Aryal, J.[Jagannath],
Deep Learning-Based Semantic Segmentation of Urban Features in Satellite Images: A Review and Meta-Analysis,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Yan, F.H.[Fei-Hu], Xia, E.[Enyong], Li, Z.X.[Zhao-Xin], Zhou, Z.[Zhong],
Sampling-Based Path Planning for High-Quality Aerial 3D Reconstruction of Urban Scenes,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Chen, D.Y.[De-Yue], Peng, L.[Ling], Li, W.C.[Wei-Chao], Wang, Y.D.[Yin-Da],
Building Extraction and Number Statistics in WUI Areas Based on UNet Structure and Ensemble Learning,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Cai, Y.Z.[Yuan-Zhi], Huang, H.[Hong], Wang, K.Y.[Kai-Yang], Zhang, C.[Cheng], Fan, L.[Lei], Guo, F.Y.[Fang-Yu],
Selecting Optimal Combination of Data Channels for Semantic Segmentation in City Information Modelling (CIM),
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Shao, Y.[Yang], Cooner, A.J.[Austin J.], Walsh, S.J.[Stephen J.],
Assessing Deep Convolutional Neural Networks and Assisted Machine Perception for Urban Mapping,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Ding, C.[Cheng], Weng, L.G.[Li-Guo], Xia, M.[Min], Lin, H.F.[Hai-Feng],
Non-Local Feature Search Network for Building and Road Segmentation of Remote Sensing Image,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Salleh, S.[Syahiirah], Ujang, U.[Uznir], Azri, S.[Suhaibah],
Virtual 3D Campus for Universiti Teknologi Malaysia (UTM),
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Zhao, B.[Bufan], Hua, X.H.[Xiang-Hong], Yu, K.[Kegen], He, X.X.[Xiao-Xing], Xue, W.X.[Wei-Xing], Li, Q.Q.[Qi-Qi], Qi, H.W.[Han-Wen], Zou, L.[Lujie], Li, C.[Cheng],
An Inverse Node Graph-Based Method for the Urban Scene Segmentation of 3D Point Clouds,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Wang, L.[Libo], Li, R.[Rui], Wang, D.Z.[Dong-Zhi], Duan, C.X.[Chen-Xi], Wang, T.[Teng], Meng, X.L.[Xiao-Liang],
Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Han, J.L.[Jia-Li], Zhu, L.J.[Ling-Jie], Gao, X.[Xiang], Hu, Z.Y.[Zhan-Yi], Zhou, L.Y.[Li-Yang], Liu, H.M.[Hong-Min], Shen, S.H.[Shu-Han],
Urban Scene LOD Vectorized Modeling From Photogrammetry Meshes,
IP(30), 2021, pp. 7458-7471.
IEEE DOI 2109
Solid modeling, Buildings, Semantics, Image segmentation, Computational modeling, Shape, segment based modeling BibRef

Zhu, L.J.[Ling-Jie], Shen, S.H.[Shu-Han], Gao, X.[Xiang], Hu, Z.Y.[Zhan-Yi],
Large Scale Urban Scene Modeling from MVS Meshes,
ECCV18(XI: 640-655).
Springer DOI 1810
BibRef

Yang, C.[Chong], Zhang, F.[Fan], Gao, Y.L.[Yun-Long], Mao, Z.[Zhu], Li, L.[Liang], Huang, X.F.[Xian-Feng],
Moving Car Recognition and Removal for 3D Urban Modelling Using Oblique Images,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Luo, H.[Heng], He, B.[Biao], Guo, R.Z.[Ren-Zhong], Wang, W.X.[Wei-Xi], Kuai, X.[Xi], Xia, B.[Bilu], Wan, Y.[Yuan], Ma, D.[Ding], Xie, L.F.[Lin-Fu],
Urban Building Extraction and Modeling Using GF-7 DLC and MUX Images,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Abdollahi, A.[Abolfazl], Pradhan, B.[Biswajeet], Shukla, N.[Nagesh], Chakraborty, S.[Subrata], Alamri, A.[Abdullah],
Multi-Object Segmentation in Complex Urban Scenes from High-Resolution Remote Sensing Data,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Pepe, M.[Massimiliano], Costantino, D.[Domenica], Alfio, V.S.[Vincenzo Saverio], Vozza, G.[Gabriele], Cartellino, E.[Elena],
A Novel Method Based on Deep Learning, GIS and Geomatics Software for Building a 3D City Model from VHR Satellite Stereo Imagery,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Lin, G.Y.[Gui-Ye], Giordano, A.[Andrea], Sang, K.[Kun], Stendardo, L.[Luigi], Yang, X.C.[Xiao-Chun],
Application of Territorial Laser Scanning in 3D Modeling of Traditional Village: A Case Study of Fenghuang Village in China,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhao, L.[Ling], Luo, L.[Li], Li, B.[Bo], Xu, L.Y.[Li-Yan], Zhu, J.W.[Jia-Wei], He, S.[Silu], Li, H.F.[Hai-Feng],
Analysis of the Uniqueness and Similarity of City Landscapes Based on Deep Style Learning,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Yan, L.[Li], Li, Y.[Yao], Xie, H.[Hong],
Urban Building Mesh Polygonization Based on 1-Ring Patch and Topology Optimization,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhao, L.[Li], Liu, Y.M.[Yong-Mei], Men, C.G.[Chao-Guang], Men, Y.[Yubo],
Double Propagation Stereo Matching for Urban 3-D Reconstruction From Satellite Imagery,
GeoRS(60), 2022, pp. 1-17.
IEEE DOI 2112
Satellites, Solid modeling, Image edge detection, Image segmentation, Optimization, urban scenes BibRef

Namouchi, S.[Slim], Farah, I.R.[Imed Riadh],
Graph-Based Classification and Urban Modeling of Laser Scanning and Imagery: Toward 3D Smart Web Services,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Luo, B.H.[Bin-Han], Yang, J.[Jian], Song, S.[Shalei], Shi, S.[Shuo], Gong, W.[Wei], Wang, A.[Ao], Du, L.[Lin],
Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Sánchez-Vaquerizo, J.A.[Javier Argota],
Getting Real: The Challenge of Building and Validating a Large-Scale Digital Twin of Barcelona's Traffic with Empirical Data,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Tumurbaatar, Z.[Zorigt], Miura, H.[Hiroyuki], Tsamba, T.[Tsoggerel],
Development of Building Inventory Data in Ulaanbaatar, Mongolia for Seismic Loss Estimation,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Alsadik, B.[Bashar], Khalaf, Y.H.[Yousif Hussein],
Potential Use of Drone Ultra-High-Definition Videos for Detailed 3D City Modeling,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Lee, A.[Ahyun], Lee, K.W.[Kang-Woo], Kim, K.H.[Kyong-Ho], Shin, S.W.[Sung-Woong],
A Geospatial Platform to Manage Large-Scale Individual Mobility for an Urban Digital Twin Platform,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Hu, Q.Y.[Qing-Yong], Yang, B.[Bo], Khalid, S.[Sheikh], Xiao, W.[Wen], Trigoni, N.[Niki], Markham, A.[Andrew],
SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Clouds,
IJCV(130), No. 2, February 2022, pp. 316-343.
Springer DOI 2202

WWW Link. Dataset, Urban. Urban scale point cloud BibRef

Maduako, I.[Iyke], Yi, Z.[Zhuangfang], Zurutuza, N.[Naroa], Arora, S.[Shilpa], Fabian, C.[Christopher], Kim, D.H.[Do-Hyung],
Automated School Location Mapping at Scale from Satellite Imagery Based on Deep Learning,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
Large scale, specific structures, which are highly varied. BibRef

Kulawiak, M.[Marek],
A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Li, J.[Jihao], Weinmann, M.[Martin], Sun, X.[Xian], Diao, W.H.[Wen-Hui], Feng, Y.C.[Ying-Chao], Hinz, S.[Stefan], Fu, K.[Kun],
VD-LAB: A view-decoupled network with local-global aggregation bridge for airborne laser scanning point cloud classification,
PandRS(186), 2022, pp. 19-33.
Elsevier DOI 2203
Applications. Water, Powerlines. ALS Point Cloud, Classification, Deep Learning, Decoupled High-level Feature, Local-global Information Aggregation BibRef

Stouffs, R.[Rudi],
Virtual 3D City Models,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Berenguel-Baeta, B.[Bruno], Bermudez-Cameo, J.[Jesus], Guerrero, J.J.[Jose J.],
Atlanta scaled layouts from non-central panoramas,
PR(129), 2022, pp. 108740.
Elsevier DOI 2206
Omnidirectional vision, 3D vision, Non-central cameras, Layout recovery, Scene understanding BibRef

Li, M.T.[Meng-Tian], Xie, Y.[Yuan], Ma, L.Z.[Li-Zhuang],
Paying attention for adjacent areas: Learning discriminative features for large-scale 3D scene segmentation,
PR(129), 2022, pp. 108722.
Elsevier DOI 2206
Large-scale 3D point clouds, Attention, Long-tailed distribution, Segmentation BibRef

Zhang, H.C.[Huang-Chuang], Shi, R.P.[Ruo-Ping], Li, G.[Ge],
RETRACTED: Geometric Construction of Video Stereo Grid Space,
RS(16), No. 13, 2024, pp. 2297.
DOI Link 2407
BibRef

Scalas, A.[Andreas], Cabiddu, D.[Daniela], Mortara, M.[Michela], Spagnuolo, M.[Michela],
Potential of the Geometric Layer in Urban Digital Twins,
IJGI(11), No. 6, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Gao, F.J.[Feng-Jiao], Yan, Y.M.[Yi-Ming], Lin, H.[Hemin], Shi, R.Y.[Rui-Yao],
PIIE-DSA-Net for 3D Semantic Segmentation of Urban Indoor and Outdoor Datasets,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Yu, M.[Mulin], Lafarge, F.[Florent], Oesau, S.[Sven], Hilaire, B.[Bruno],
Repairing geometric errors in 3D urban models with kinetic data structures,
PandRS(192), 2022, pp. 315-326.
Elsevier DOI 2209
Mesh repairing, Semantic reconstruction, Kinetic data structure, BIM, CityGML, IFC BibRef

Tanduo, B.[Beatrice], Martino, A.[Andrea], Balletti, C.[Caterina], Guerra, F.[Francesco],
New Tools for Urban Analysis: A SLAM-Based Research in Venice,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Sambaturu, B.[Bhavani], Gupta, A.[Ashutosh], Jawahar, C.V., Arora, C.[Chetan],
ScribbleNet: Efficient interactive annotation of urban city scenes for semantic segmentation,
PR(133), 2023, pp. 109011.
Elsevier DOI 2210
BibRef

Yi, S.[Shi], Liu, X.[Xi], Li, J.J.[Jun-Jie], Chen, L.[Ling],
UAVformer: A Composite Transformer Network for Urban Scene Segmentation of UAV Images,
PR(133), 2023, pp. 109019.
Elsevier DOI 2210
Urban scenes segmentation, UAV image, Composite backbone, Aggregation windows multi-head self-attention transformer block, V-shaped decoder BibRef

Tang, Q.[Quan], Liu, F.G.[Fa-Gui], Zhang, T.[Tong], Jiang, J.[Jun], Zhang, Y.[Yu], Zhu, B.[Boyuan], Tang, X.[Xuhao],
Compensating for Local Ambiguity With Encoder-Decoder in Urban Scene Segmentation,
ITS(23), No. 10, October 2022, pp. 19224-19235.
IEEE DOI 2210
Image segmentation, Semantics, Logic gates, Transformers, Computational modeling, Convolutional neural networks, autonomous driving BibRef

Zhou, J.[Jie], Liu, Y.[Yaohui], Nie, G.[Gaozhong], Cheng, H.[Hao], Yang, X.Y.[Xin-Yue], Chen, X.X.[Xiao-Xian], Gross, L.[Lutz],
Building Extraction and Floor Area Estimation at the Village Level in Rural China Via a Comprehensive Method Integrating UAV Photogrammetry and the Novel EDSANet,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Watson, C.S.[C. Scott], Elliott, J.R.[John R.], Amey, R.M.J.[Ruth M. J.], Abdrakhmatov, K.E.[Kanatbek E.],
Analyzing Satellite-Derived 3D Building Inventories and Quantifying Urban Growth towards Active Faults: A Case Study of Bishkek, Kyrgyzstan,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Fan, Q.D.[Qin-Dong], Mei, X.J.[Xue-Jian], Zhang, C.M.[Chen-Ming], Yang, X.Y.[Xiao-Yu],
Research on Gridding of Urban Spatial Form Based on Fractal Theory,
IJGI(11), No. 12, 2022, pp. xx-yy.
DOI Link 2301
BibRef

Ma, X.T.[Xiao-Tong], Man, Q.X.[Qi-Xia], Yang, X.M.[Xin-Ming], Dong, P.L.[Pin-Liang], Yang, Z.L.[Ze-Long], Wu, J.R.[Jing-Ru], Liu, C.H.[Chun-Hui],
Urban Feature Extraction within a Complex Urban Area with an Improved 3D-CNN Using Airborne Hyperspectral Data,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Chen, J.[Jie], Dai, X.Y.[Xin-Yi], Guo, Y.[Ya], Zhu, J.[Jingru], Mei, X.M.[Xiao-Ming], Deng, M.[Min], Sun, G.[Geng],
Urban Built Environment Assessment Based on Scene Understanding of High-Resolution Remote Sensing Imagery,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Dong, Y.[Yang], Song, J.X.[Jia-Xuan], Fan, D.Z.[Da-Zhao], Ji, S.[Song], Lei, R.[Rong],
Joint Deep Learning and Information Propagation for Fast 3D City Modeling,
IJGI(12), No. 4, 2023, pp. 150.
DOI Link 2305
BibRef

Wu, L.[Letian], Zhang, X.[Xian], Zhu, D.J.[De-Jun], Yang, W.K.[Wan-Kou],
BFANet: Effective segmentation network for low altitude high-resolution urban scene image,
JVCIR(94), 2023, pp. 103847.
Elsevier DOI 2306
Urban scene segmentation, Real-time semantic segmentation, Bi-lateral network, Convolutional neural network BibRef

Lytkin, S.[Sergey], Badenko, V.[Vladimir], Fedotov, A.[Alexander], Vinogradov, K.[Konstantin], Chervak, A.[Anton], Milanov, Y.[Yevgeny], Zotov, D.[Dmitry],
Saint Petersburg 3D: Creating a Large-Scale Hybrid Mobile LiDAR Point Cloud Dataset for Geospatial Applications,
RS(15), No. 11, 2023, pp. 2735.
DOI Link 2306
BibRef

Gutierrez, I.[Ivan], Weibull, W.[Wiktor], Watson, L.[Lisa], Olsen, T.M.[Thomas Meldahl], Escalona, A.[Alejandro],
Holistic 3D Model of an Urban Area in Norway: An Integration of Geophysical, Geotechnical, Remote Sensing, and Geological Methods,
RS(15), No. 11, 2023, pp. 2872.
DOI Link 2306
BibRef

Vaienti, B.[Beatrice], Petitpierre, R.[Rémi], di Lenardo, I.[Isabella], Kaplan, F.[Frédéric],
Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction,
RS(15), No. 13, 2023, pp. 3352.
DOI Link 2307
BibRef

Rantanen, T.[Toni], Julin, A.[Arttu], Virtanen, J.P.[Juho-Pekka], Hyyppä, H.[Hannu], Vaaja, M.T.[Matti T.],
Open Geospatial Data Integration in Game Engine for Urban Digital Twin Applications,
IJGI(12), No. 8, 2023, pp. 310.
DOI Link 2309
BibRef

Hui, Z.Y.[Zhen-Yang], Li, Z.X.[Zhuo-Xuan], Li, D.J.[Da-Jun], Xu, Y.[Yanan], Wang, Y.Q.[Yu-Qian],
Self-Adaptive Filtering for Ultra-Large-Scale Airborne LiDAR Data in Urban Environments Based on Object Primitive Global Energy Minimization,
RS(15), No. 16, 2023, pp. 4013.
DOI Link 2309
BibRef

Zhou, W.[Wujie], Gong, T.T.[Ting-Ting], Lei, J.S.[Jing-Sheng], Yu, L.[Lu],
DBCNet: Dynamic Bilateral Cross-Fusion Network for RGB-T Urban Scene Understanding in Intelligent Vehicles,
SMCS(53), No. 12, December 2023, pp. 7631-7641.
IEEE DOI 2311
BibRef

Zhang, G.Y.[Guang-Yun], Zhang, R.T.[Rong-Ting],
MeshNet-SP: A Semantic Urban 3D Mesh Segmentation Network with Sparse Prior,
RS(15), No. 22, 2023, pp. 5324.
DOI Link 2311
BibRef

Wang, J.X.[Jing-Xue], Li, H.[Huan], Xu, Z.H.[Zheng-Hui], Xie, X.[Xiao],
Semantic Segmentation of Urban Airborne LiDAR Point Clouds Based on Fusion Attention Mechanism and Multi-Scale Features,
RS(15), No. 21, 2023, pp. 5248.
DOI Link 2311
BibRef

Franzini, M.[Marica], Casella, V.M.[Vittorio Marco], Monti, B.[Bruno],
Assessment of Leica CityMapper-2 LiDAR Data within Milan's Digital Twin Project,
RS(15), No. 21, 2023, pp. 5263.
DOI Link 2311
BibRef

Liang, Y.[Yubin], Yang, Y.[Yang], Mu, Y.F.[Yi-Fan], Cui, T.J.[Tie-Jun],
Robust Fusion of Multi-Source Images for Accurate 3D Reconstruction of Complex Urban Scenes,
RS(15), No. 22, 2023, pp. 5302.
DOI Link 2311
BibRef

Gao, X.[Xiang], Tao, D.D.[Dong-Dong], Liu, Y.Q.[Yu-Qian], Xie, Z.X.[Ze-Xiao], Shen, S.H.[Shu-Han],
Vehicle-Borne Multi-Sensor Temporal-Spatial Pose Globalization via Cross-Domain Data Association,
ITS(24), No. 12, December 2023, pp. 13962-13975.
IEEE DOI 2312
BibRef

Li, X.H.[Xin-Hui], Li, M.J.[Ming-Jia], Li, X.P.[Xiao-Peng], Guo, X.J.[Xiao-Jie],
Learning Generalized Knowledge From a Single Domain on Urban-Scene Segmentation,
MultMed(25), 2023, pp. 7635-7646.
IEEE DOI 2312
BibRef

Uciechowska-Grakowicz, A.[Anna], Herrera-Granados, O.[Oscar], Biernat, S.[Stanislaw], Bac-Bronowicz, J.[Joanna],
Usage of Airborne LiDAR Data and High-Resolution Remote Sensing Images in Implementing the Smart City Concept,
RS(15), No. 24, 2023, pp. 5776.
DOI Link 2401
BibRef

Leroux, F.[Frédéric], Germain, M.[Mickaël], Clabaut, É.[Étienne], Bouroubi, Y.[Yacine], St-Pierre, T.[Tony],
Improving Three-Dimensional Building Segmentation on Three-Dimensional City Models through Simulated Data and Contextual Analysis for Building Extraction,
IJGI(13), No. 1, 2024, pp. 20.
DOI Link 2402
BibRef

Han, W.Y.[Wen-Yu], Wen, C.C.[Cong-Cong], Chok, L.[Lazarus], Tan, Y.L.[Yan Liang], Chan, S.L.[Sheung Lung], Zhao, H.[Hang], Feng, C.[Chen],
Autoencoding tree for city generation and applications,
PandRS(208), 2024, pp. 176-189.
Elsevier DOI Code:
WWW Link. 2402
City generation, Real-world city datasets, Tree-structured neural network, Urban planning applications BibRef

Groenen, I.[Inske], Rudinac, S.[Stevan], Worring, M.[Marcel],
PanorAMS: Automatic Annotation for Detecting Objects in Urban Context,
MultMed(26), 2024, pp. 1281-1294.
IEEE DOI 2402
City of Amsterdam and includes over 14 million noisy bounding box annotations of 22 object categories present in 771,299 panoramic images. Annotations, Geospatial analysis, Noise measurement, Urban areas, Protocols, Object detection, Labeling, Object detection, panoramic image datasets BibRef

Luo, H.T.[Hai-Tao], Zhang, J.M.[Jin-Ming], Liu, X.[Xiongfei], Zhang, L.[Lili], Liu, J.Y.[Jun-Yi],
Large-Scale 3D Reconstruction from Multi-View Imagery: A Comprehensive Review,
RS(16), No. 5, 2024, pp. 773.
DOI Link 2403
BibRef

Gao, L.[Lin], Liu, Y.[Yu], Chen, X.[Xi], Liu, Y.X.[Yu-Xiang], Yan, S.[Shen], Zhang, M.[Maojun],
CUS3D: A New Comprehensive Urban-Scale Semantic-Segmentation 3D Benchmark Dataset,
RS(16), No. 6, 2024, pp. 1079.
DOI Link 2403
BibRef

Harshit, Chaurasia, P.[Pallavi], Zlatanova, S.[Sisi], Jain, K.[Kamal],
Low-Cost Data, High-Quality Models: A Semi-Automated Approach to LOD3 Creation,
IJGI(13), No. 4, 2024, pp. 119.
DOI Link 2405
BibRef

Afzal, M.K.[Muhammad Kamran], Liu, W.Q.[Wei-Quan], Zang, Y.[Yu], Chen, S.T.[Shu-Ting], Afzal, H.M.R.[Hafiz Muhammad Rehan], Adam, J.M.[Jibril Muhammad], Yang, B.[Bai], Li, J.[Jonathan], Wang, C.[Cheng],
GeoSparseNet: A Multi-Source Geometry-Aware CNN for Urban Scene Analysis,
RS(16), No. 11, 2024, pp. 1827.
DOI Link 2406
BibRef

Liu, X.C.[Xin-Cong], Xu, T.F.[Ting-Fa], Wang, Y.[Ying], Yu, Z.N.[Zhi-Nong], Yuan, X.Y.[Xiao-Ying], Qin, H.L.[Hao-Lin], Li, J.A.[Jian-An],
BACTrack: Building Appearance Collection for Aerial Tracking,
CirSysVideo(34), No. 6, June 2024, pp. 5002-5017.
IEEE DOI 2406
Target tracking, Transformers, Feature extraction, Autonomous aerial vehicles, Object tracking, Head, Task analysis, multi-template fusion BibRef

Somanath, S.[Sanjay], Naserentin, V.[Vasilis], Eleftheriou, O.[Orfeas], Sjölie, D.[Daniel], Wästberg, B.S.[Beata Stahre], Logg, A.[Anders],
Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data,
RS(16), No. 11, 2024, pp. 1939.
DOI Link 2406
BibRef

Li, T.Y.[Tian-Yu], Xie, P.[Peng],
A New Method Based on Lattice Boltzmann Method and Unsupervised Clustering for Identification of Urban-Scale Ventilation Corridors,
IJGI(13), No. 6, 2024, pp. 183.
DOI Link 2406
BibRef

Shirinyan, E.[Evgeny], Petrova-Antonova, D.[Dessislava],
Large-Scale Solar Potential Analysis in a 3D CAD Framework as a Use Case of Urban Digital Twins,
RS(16), No. 15, 2024, pp. 2700.
DOI Link 2408
BibRef

Yao, Y.[Yao], Jiang, Y.[Yinghong], Yu, Q.[Qing], Yuan, J.[Jian], Li, J.X.[Jia-Xing], Xu, J.[Jian], Liu, S.Y.[Si-Yuan], Zhang, H.R.[Hao-Ran],
A GIS-Based Framework for Synthesizing City-Scale Long-Term Individual-Level Spatial-Temporal Mobility,
IJGI(13), No. 7, 2024, pp. 261.
DOI Link 2408
BibRef

Wang, Y.F.[Yue-Feng], Jiao, W.[Wei], Fan, H.C.[Hong-Chao], Zhou, G.Q.[Guo-Qing],
A framework for fully automated reconstruction of semantic building model at urban-scale using textured LoD2 data,
PandRS(216), 2024, pp. 90-108.
Elsevier DOI Code:
WWW Link. 2408
Semantic building model, CityGML LoD3, Facade layout graph, Parameter representation, EM-MAP optimization BibRef

Qin, Y.M.[Yi-Ming], Zhao, N.X.[Nan-Xuan], Zhao, N.X.[Nan-Xuan], Yang, J.L.[Jia-Le], Pan, S.Y.[Si-Yuan], Sheng, B.[Bin], Lau, R.W.H.[Rynson W. H.],
UrbanEvolver: Function-Aware Urban Layout Regeneration,
IJCV(132), No. 1, January 2024, pp. 3408-3427.
Springer DOI 2409
BibRef

Liu, P.[Peng], Ge, Y.Q.[Yan-Qi], Duan, L.X.[Li-Xin], Li, W.[Wen], Luo, H.[Haonan], Lv, F.[Fengmao],
Transferring Multi-Modal Domain Knowledge to Uni-Modal Domain for Urban Scene Segmentation,
ITS(25), No. 9, September 2024, pp. 11576-11589.
IEEE DOI 2409
Training, Semantic segmentation, Transformers, Task analysis, Adaptation models, Visualization, Synthetic data, multi-modal learning BibRef

Guo, J.W.[Jian-Wei], Qin, H.[Haobo], Zhou, Y.C.[Yin-Chang], Chen, X.[Xin], Nan, L.L.[Liang-Liang], Huang, H.[Hui],
Fast Building Instance Proxy Reconstruction for Large Urban Scenes,
PAMI(46), No. 11, November 2024, pp. 7267-7282.
IEEE DOI 2410
Buildings, Image reconstruction, Point cloud compression, Solid modeling, Instance segmentation, Surface reconstruction, surface reconstruction BibRef

Schreiber, Q.[Qendrim], Wolpert, N.[Nicola], Schömer, E.[Elmar],
METNet: A mesh exploring approach for segmenting 3D textured urban scenes,
PandRS(218), 2024, pp. 498-509.
Elsevier DOI Code:
WWW Link. 2412
Texture meshes, Semantic segmentation, Urban scene, Large scene understanding, Structured representation, Artificial neural networks BibRef

Jia, X.[Xinqi], Song, X.Y.[Xiao-Yong], Rao, L.[Lei], Fan, G.Y.[Guang-Yu], Cheng, S.L.[Song-Lin], Chen, N.S.[Nian-Sheng],
DEUFormer: High-Precision Semantic Segmentation for Urban Remote Sensing Images,
IET-CV(18), No. 8, 2024, pp. 1209-1222.
DOI Link 2501
convolutional neural nets BibRef

Gao, R.[Rui], Yan, G.H.[Guang-Hui], Wang, Y.Z.[Ying-Zhi], Yan, T.[Tianfeng], Niu, R.[Ruiting], Tang, C.Y.[Chun-Yang],
Construction of a Real-Scene 3D Digital Campus Using a Multi-Source Data Fusion: A Case Study of Lanzhou Jiaotong University,
IJGI(14), No. 1, 2025, pp. 19.
DOI Link 2501
BibRef

Papadopoulos, T.[Theofilos], Evangelidis, K.[Konstantinos], Kaskalis, T.H.[Theodore H.], Evangelidis, G.[Georgios],
The Metaverse Is Geospatial: A System Model Architecture Integrating Spatial Computing, Digital Twins, and Virtual Worlds,
IJGI(14), No. 3, 2025, pp. 126.
DOI Link 2503
BibRef

Zhang, C.C.[Chao-Chen], Chen, J.[Jie], Huang, Z.L.[Zhong-Ling], Zeng, H.C.[Hong-Cheng], Huang, Z.X.[Zhi-Xiang], Li, Y.[Yingsong], Xu, H.[Hui], Pu, X.[Xiangkai], Sun, L.[Long],
SAR Image Target Segmentation Guided by the Scattering Mechanism-Based Visual Foundation Model,
RS(17), No. 7, 2025, pp. 1209.
DOI Link 2504
BibRef

Nguyen, T.A.Q.[Thang-Anh-Quan], Roldão, L.[Luis], Piasco, N.[Nathan], Bennehar, M.[Moussab], Tsishkou, D.[Dzmitry],
RoDUS: Robust Decomposition of Static and Dynamic Elements in Urban Scenes,
ECCV24(LXXII: 112-130).
Springer DOI 2412
BibRef

Chen, Y.[Yun], Wang, J.K.[Jing-Kang], Yang, Z.[Ze], Manivasagam, S.[Sivabalan], Urtasun, R.[Raquel],
G3R: Gradient Guided Generalizable Reconstruction,
ECCV24(VI: 305-323).
Springer DOI 2412
BibRef