23.4.2 DEM, DSM, DTM, Generation in Urban Areas

Chapter Contents (Back)
Digital Elevation Map. Urban, DEM.

Gabet, L., Giraudon, G., Renouard, L.,
Automatic-Generation of High-Resolution Urban Zone Digital Elevation Models,
PandRS(52), No. 1, February 1997, pp. 33-47. 9703

Davis, C.H.[Curt H.], Wang, X.Y.[Xiang-Yun],
High-Resolution DEMs for Urban Applications from NAPP Photography,
PhEngRS(67), No. 5, May 2001, pp. 585-592. 0106
1:40,000-scale NAPP aerial photography, in conjunction with precision ground control, can be used to generate DEMs with horizontal resolutions of 1 to 3 meters and vertical accuracies of 1.8 to 2.5 meters.
See also Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information. BibRef

Shan, J.[Jie], Sampath, A.[Aparajithan],
Urban DEM Generation from Raw Lidar Data: A Labeling Algorithm and its Performance,
PhEngRS(71), No. 2, February 2005, pp. 217.
WWW Link. An efficient one-dimensional, bi-directional labeling approach for generating bald ground DEM from raw lidar data in complex urban areas. 0509

See also Building Boundary Tracing and Regularization from Airborne Lidar Point Clouds. BibRef

Perissin, D., Rocca, F.,
High-Accuracy Urban DEM Using Permanent Scatterers,
GeoRS(44), No. 11, November 2006, pp. 3338-3347.

Perissin, D., Ferretti, A.[Alessandro],
Urban-Target Recognition by Means of Repeated Spaceborne SAR Images,
GeoRS(45), No. 12, December 2007, pp. 4043-4058.

Chehata, N., Jung, F., Stamon, G.,
A graph cut optimization guided by 3D-features for surface height recovery,
PandRS(64), No. 2, March 2009, pp. 193-203.
Elsevier DOI 0903
Stereoscopic; Urban; High resolution satellite images; Surface modeling; Graph cut optimization BibRef

Susaki, J.,
Adaptive Slope Filtering of Airborne LiDAR Data in Urban Areas for Digital Terrain Model (DTM) Generation,
RS(4), No. 6, June 2012, pp. 1804-1819.
DOI Link 1208

See also Segmentation of Shadowed Buildings in Dense Urban Areas from Aerial Photographs. BibRef

Susaki, J.[Junichi],
Knowledge-Based Modeling of Buildings in Dense Urban Areas by Combining Airborne LiDAR Data and Aerial Images,
RS(5), No. 11, 2013, pp. 5944-5968.
DOI Link 1312

Chen, Z.Y.[Zi-Yue], Devereux, B.[Bernard], Gao, B.B.[Bing-Bo], Amable, G.[Gabriel],
Upward-fusion urban DTM generating method using airborne Lidar data,
PandRS(72), No. 1, August 2012, pp. 121-130.
Elsevier DOI 1209
Airborne Lidar; Upward-fusion; GIS; Generation; DTM; Urban BibRef

Rossi, C.[Cristian], Gernhardt, S.[Stefan],
Urban DEM generation, analysis and enhancements using TanDEM-X,
PandRS(85), No. 1, 2013, pp. 120-131.
Elsevier DOI 1310
TanDEM-X BibRef

Palm, S., Oriot, H.M., Cantalloube, H.M.,
Radargrammetric DEM Extraction Over Urban Area Using Circular SAR Imagery,
GeoRS(50), No. 11, November 2012, pp. 4720-4725.

Palm, S., Pohl, N., Stilla, U.,
Challenges and Potentials Using Multi Aspect Coverage of Urban Scenes by Airborne SAR on Circular Trajectories,
DOI Link 1504

Shabou, A., Baselice, F., Ferraioli, G.,
Urban Digital Elevation Model Reconstruction Using Very High Resolution Multichannel InSAR Data,
GeoRS(50), No. 11, November 2012, pp. 4748-4758.

Geiss, C., Wurm, M., Breunig, M., Felbier, A., Taubenbock, H.,
Normalization of TanDEM-X DSM Data in Urban Environments With Morphological Filters,
GeoRS(53), No. 8, August 2015, pp. 4348-4362.
geomorphology BibRef

Budillon, A.[Alessandra], Johnsy, A.C.[Angel Caroline], Schirinzi, G.[Gilda],
Extension of a Fast GLRT Algorithm to 5D SAR Tomography of Urban Areas,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708

Budillon, A.[Alessandra], Johnsy, A.C.[Angel Caroline], Schirinzi, G.[Gilda],
Urban Tomographic Imaging Using Polarimetric SAR Data,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902

Panagiotakis, E.[Emmanouil], Chrysoulakis, N.[Nektarios], Charalampopoulou, V.[Vasiliki], Poursanidis, D.[Dimitris],
Validation of Pleiades Tri-Stereo DSM in Urban Areas,
IJGI(7), No. 3, 2018, pp. xx-yy.
DOI Link 1804

Hou, Y.L.[Yao-Lin], Peng, J.W.[Jian-Wei], Hu, Z.H.[Zhi-Hua], Tao, P.J.[Peng-Jie], Shan, J.[Jie],
Planarity constrained multi-view depth map reconstruction for urban scenes,
PandRS(139), 2018, pp. 133-145.
Elsevier DOI 1804
Planarity constraint, Multi-view depth map, Optimization, Segmentation, PatchMatch BibRef

Hu, Z.H.[Zhi-Hua], Hou, Y.L.[Yao-Lin], Tao, P.J.[Peng-Jie], Shan, J.[Jie],
IMGTR: Image-triangle based multi-view 3D reconstruction for urban scenes,
PandRS(181), 2021, pp. 191-204.
Elsevier DOI 2110
Triangulation, Multi-view reconstruction, Depth map, Urban scenes, Continuity constraints BibRef

Wu, B.[Bo], Xie, L.F.[Lin-Fu], Hu, H.[Han], Zhu, Q.[Qing], Yau, E.[Eric],
Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas,
PandRS(139), 2018, pp. 119-132.
Elsevier DOI 1804
Aerial oblique imagery, Terrestrial imagery, Photogrammetry, 3D modeling BibRef

Shirowzhan, S.[Sara], Sepasgozar, S.M.E.[Samad M. E.],
Spatial Analysis Using Temporal Point Clouds in Advanced GIS: Methods for Ground Elevation Extraction in Slant Areas and Building Classifications,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link 1903

Rambour, C.[Clément], Denis, L.[Loïc], Tupin, F.[Florence], Oriot, H.[Hélène], Huang, Y.[Yue], Ferro-Famil, L.[Laurent],
Urban surface reconstruction in SAR tomography by graph-cuts,
CVIU(188), 2019, pp. 102791.
Elsevier DOI 1910
Tomographic SAR inversion, Dense urban areas, Graph cut, 3-D reconstruction, Surface segmentation BibRef

Luo, H., Li, Z., Dong, Z., Liu, P., Wang, C., Song, J.,
A New Baseline Linear Combination Algorithm for Generating Urban Digital Elevation Models With Multitemporal InSAR Observations,
GeoRS(58), No. 2, February 2020, pp. 1120-1133.
Strain, Synthetic aperture radar, Deformable models, Surface topography, Atmospheric modeling, multitemporal synthetic aperture radar interferometry (MTInSAR) BibRef

Liebel, L.[Lukas], Bittner, K.[Ksenia], Körner, M.[Marco],
A generalized multi-task learning approach to stereo DSM filtering in urban areas,
PandRS(166), 2020, pp. 213-227.
Elsevier DOI 2007
Multi-task learning, Stereo DSM filtering, Roof type segmentation, 3D city models, Deep learning BibRef

Lajczak, A.[Adam], Zarychta, R.[Roksana], Walek, G.[Grzegorz],
Quantitative Assessment of Changes in Topography of Town Caused by Human Impact, Krakow City Centre, Southern Poland,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106

Fan, L.[Lei], Cai, Y.Z.[Yuan-Zhi],
An Efficient Filtering Approach for Removing Outdoor Point Cloud Data of Manhattan-World Buildings,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110

Häufel, G., Böge, M., Bulatov, D.,
DTM Correction In Areas of Steep Slopes,
DOI Link 2012

Jamali, A., Castro, F.A.,
Topological 3D Elevation Data Interpolation of ASTER GDEM Based on Continuous Deformation,
DOI Link 1901

Schachtschneider, J., Schlichting, A., Brenner, C.,
Assessing Temporal Behavior in Lidar Point Clouds of Urban Environments,
DOI Link 1805

Rothermel, M.[Mathias], Haala, N.[Norbert], Wenzel, K.[Konrad], Bulatov, D.[Dimitri],
Fast and Robust Generation of Semantic Urban Terrain Models from UAV Video Streams,
Buildings BibRef

Rossi, C., Fritz, T., Eineder, M., Erten, E., Zhu, X.X., Gernhardt, S.,
Towards an Urban DEM Generation With Satellite SAR Interferometry,
DOI Link 1209

Aktaruzzaman, M.D., Schmitt, T.[Theo],
LiDAR-data: automatic object detection for urban flooding models.,
PDF File. 1006
Detailed Digital Surface Model (DSM) Generation and Automatic Object Detection to Facilitate Modelling of Urban Flooding,
PDF File. 0906

Elaksher, A.F.[Ahmed F.],
A framework for generating high quality digital elevation models in urban areas,

Jalobeanu, A., Fitzenz, D.D.,
Robust Disparity Maps with Uncertainties for 3D Surface Reconstruction or Ground Motion Inference,
PDF File. 0711
Include uncertainity estimation in computation. BibRef

Champion, N.[Nicolas], Boldo, D.[Didier],
A Robust Algorithm for Estimating Digital Terrain Models from Digital Surface Models in Dense Urban Areas,
PDF File. 0609

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
DEM, DSM, DTM, Generation Using Radar, SAR, IFSAR, INSAR, InSAR .

Last update:Jan 30, 2024 at 20:33:16