24.4 Terrain Extraction, DEM, DTM, DSM

Chapter Contents (Back)
Terrain. DTM. Digital Terrain Map. DEM. DSM. Digital Elevation Map. Many other related papers in
See also Three-Dimensional Descriptions -- General.
See also Triangulated Surface Models, Mesh Models, Mesh Descriptions, 3-D Meshes.
See also Stereo and Surface Models.
See also Bathymetric Mapping, Analysis, Underwater Terrain. UAV sourced:
See also DEM, DSM, DTM, Generation Using UAV.
See also DEM, DSM, DTM, Generation Using Radar, SAR, IFSAR, INSAR, InSAR.
See also DEM, DSM, DTM, Generation Using LiDAR, LIDAR, Laser Data.
See also DEM, DSM, DTM, Generation in Urban Areas.
See also Landform Analysis, Landform Description.
See also Terrain Analysis of Mars, Craters, Minerals.
See also SAR, Radar Altimetry.

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GeoInfo(7), No. 1, March 2003, pp. 33-53.
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Toutin, T.,
Elevation modelling from satellite visible and infrared (VIR) data,
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Toutin, T.[Thierry],
DEM from stereo Landsat 7 ETM+ data over high relief areas,
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See also Block Bundle Adjustment of Landsat 7 ETM+ Images over Mountainous Areas. BibRef

Toutin, T.[Thierry],
Three-dimensional topographic mapping with ASTER stereo data in rugged topography,
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IEEE Top Reference. 0301
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Toutin, T.[Thierry],
Spatiotriangulation With Multisensor HR Stereo-Images,
GeoRS(44), No. 2, February 2006, pp. 456-462.
IEEE DOI 0602

See also Impact of terrain slope and aspect on radargrammetric DEM accuracy. BibRef

Toutin, T.[Thierry],
Generation of DSMs from SPOT-5 in-track HRS and across-track HRG stereo data using spatiotriangulation and autocalibration,
PandRS(60), No. 3, May 2006, pp. 170-181.
Elsevier DOI 0610
Mapping; DEM/DTM; SPOT5; Stereoscopic; Block-bundle; Calibration; Accuracy; Performance BibRef

Toutin, T.[Thierry],
Comparison of 3D Physical and Empirical Models for Generating DSMs from Stereo HR Images,
PhEngRS(72), No. 5, May 2006, pp. 597-604.
WWW Link. 0610
A comparison of 3D physical and empirical models for stereo-processing and the generation of digital surface models from different stereo, high-resolution sensors: Ikonos and QuickBird. BibRef

Zhu, X.K.[Xiao-Kun], Toutin, T.,
Object-Oriented Interpretation and Classification with Airborne LiDAR 3D Data,
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Schenk, T.,
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Lee, I.Y.[Imp-Yeong], Schenk, T.[Toni],
Perceptual Organization of 3D Surface Points,
PCV02(A: 193). 0305
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Tang, L., Braun, J., Debitsch, R.,
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PandRS(52), No. 3, June 1997, pp. 122-131.
Elsevier DOI 9708
Award, ISPRS. BibRef

Krupnik, A., Schenk, T.,
Experiments with Matching in the Object Space for Aerotriangulation,
PandRS(52), No. 4, August 1997, pp. 160-168. 9709
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McIntosh, K.[Kerry], Krupnik, A.[Amnon],
Integration of laser-derived DSMs and matched image edges for generating an accurate surface model,
PandRS(56), No. 3, April 2002, pp. 167-176.
HTML Version. 0205
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Morgado, A., Dowman, I.J.,
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Hsueh, W.J., Antonsson, E.K.,
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Springer DOI 9709
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Sum, J., Leung, C.S., Chan, L.W., Xu, L.,
Yet Another Algorithm Which Can Generate Topography Map,
TNN(8), No. 5, September 1997, pp. 1204-1207. 9709
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Cignoni, P., Puppo, E., Scopigno, R.,
Representation and Visualization of Terrain Surfaces at Variable Resolution,
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Du, C.J.,
An Interpolation Method for Grid-Based Terrain Modeling,
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Hung, Y.P., Chen, C.S., Hung, K.C., Chen, Y.S., Fuh, C.S.,
Multipass Hierarchical Stereo Matching for Generation of Digital Terrain Models from Aerial Images,
MVA(10), No. 5-6, April 1998, pp. 280-291.
Springer DOI 9805
BibRef

de Berg, M.[Mark], Dobrindt, K.T.G.[Katrin T.G.],
On Levels of Detail in Terrains,
GMIP(60), No. 1, January 1998, pp. 1-12. BibRef 9801

Bribiesca, E.[Ernesto],
Digital Elevation Model Data Analysis Using the Contact Surface Area,
GMIP(60), No. 2, March 1998, pp. 166-172.
See also easy measure of compactness for 2D and 3D shapes, An.
See also Measuring 3-D Shape Similarity Using Progressive Transformations. BibRef 9803

Rufino, G., Moccia, A., Esposito, S.,
DEM Generation by Means of ERS Tandem Data,
GeoRS(36), No. 6, November 1998, pp. 1905.
IEEE Top Reference. BibRef 9811

Pfeifer, N.[Norbert],
A subdivision algorithm for smooth 3D terrain models,
PandRS(59), No. 3, May 2005, pp. 115-127.
Elsevier DOI 0509
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Briese, C.[Christian], Pfeifer, N.[Norbert], Dorninger, P.[Peter],
Applications of the Robust Interpolation for DTM Determination,
PCV02(A: 55). 0305
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Hsia, J.S.[Jung-Sheng], Newton, I.[Ian],
A Method for the Automated Production of Digital Terrain Models Using a Combination of Feature Points, Grid Points, and Filling Back Points,
PhEngRS(65), No. 6, June 1999, pp. 713. BibRef 9906

Hodgson, M.E.[Michael E.], Gaile, G.L.[Gary L.],
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Lohani, B., Mason, D.C.,
Construction of a Digital Elevation Model of the Holderness Coast using the waterline method and Airborne Thematic Mapper data,
JRS(20), No. 3, February 1999, pp. 593 BibRef 9902

Bartels, M.[Marc], Wei, H.[Hong], Mason, D.C.[David C.],
DTM Generation from LIDAR Data using Skewness Balancing,
ICPR06(I: 566-569).
IEEE DOI 0609
BibRef

Sansosti, E., Lanari, R., Fornaro, G., Franceschetti, G., Tesauro, M., Puglisi, G., Coltelli, M.,
Digital elevation model generation using ascending and descending ERS-1/ERS-2 tandem data,
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McArthur, D.E.[Donald E.], Fuentes, R.W.[Robert W.], Devaragan, V.[Venkat],
Generation of Hierarchical Multiresolution Terrain Databases Using Wavelet Filtering,
PhEngRS(66), No. 3, March 2000, pp. 287. 0003
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Endreny, T.A., Wood, E.F.[Eric F.], Hsu, A.,
Correction of Errors in SPOT-Derived DEM's Using GTOPO30 Data,
GeoRS(38), No. 3, May 2000, pp. 1234-1241.
IEEE Top Reference. 0006
BibRef

Doucette, P.[Peter], Beard, K.[Kate],
Exploring the Capability of Some GIS Surface Interpolators for DEM Gap Fill,
PhEngRS(66), No. 7, July 2000, pp. 881. The evaluation tends to favor the use of the splining function when interpolating for the kind of gaps and sample configurations considered. 0008
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de Floriani, L.[Leila], Magillo, P.[Paola], Puppo, E.[Enrico],
VARIANT: A System for Terrain Modeling at Variable Resolution,
GeoInfo(4), No. 3, October 2000, pp. 287-315.
DOI Link 0011

See also Horizon Computation on a Hierarchical Triangulated Terrain Model. BibRef

Anderson, J.M.M., Al Qatshan, A.S.,
Matched filtering-based estimation of ground elevation using laser altimetry,
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IEEE Top Reference. 0111
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Sim, D.G.[Dong-Gyu], Park, R.H.[Rae-Hong],
Localization based on DEM matching using multiple aerial image pairs,
IP(11), No. 1, January 2002, pp. 52-55.
IEEE DOI 0202
BibRef

Gonçalves, G., Julien, P., Riazanoff, S., Cervelle, B.,
Preserving cartographic quality in DTM interpolation from contour lines,
PandRS(56), No. 3, April 2002, pp. 210-220.
HTML Version. 0205
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Almansa, A., Cao, F., Gousseau, Y., Rouge, B.,
Interpolation of digital elevation models using AMLE and related methods,
GeoRS(40), No. 2, February 2002, pp. 314-325.
IEEE Top Reference. 0205
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Whitaker, R.T., Juarez-Valdes, E.L.,
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IEEE DOI 0207
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Whitaker, R.T.,
A Level-Set Approach to 3D Reconstruction from Range Data,
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See also Level-Set Approach to Image Blending, A. BibRef

Whitaker, R.T.,
Maximum Likelihood Surface Estimation,
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PDF File. 0209
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Reconstructing Terrain Maps from Dense Range Data,
ICIP01(II: 165-168).
IEEE DOI 0108
BibRef

Altmaier, A.[Angela], Kany, C.[Christoph],
Digital surface model generation from CORONA satellite images,
PandRS(56), No. 4, July 2002, pp. 221-235.
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Lee, H.Y.[Hae-Yeoun], Kim, T.J.[Tae-Jung], Park, W.[Wonkyu], Lee, H.K.[Heung Kyu],
Extraction of digital elevation models from satellite stereo images through stereo matching based on epipolarity and scene geometry,
IVC(21), No. 9, September 2003, pp. 789-796.
Elsevier DOI 0308
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Rahmes, M.D.[Mark Donald], Karp, J.P.[John Philip],
Automated method for making a topographical model and related system,
US_Patent6,654,690, Nov 25, 2003
WWW Link. Process randomly spaced data to generate gridded data. BibRef 0311

Ham, T.E.[Todd E.], Andrews, A.[Aaron], Bleeze, B.[Brian],
System and method for identifying tie point collections used in imagery,
US_Patent6,707,464, Mar 16, 2004
WWW Link. BibRef 0403

Gousie, M.B.[Michael B.], Franklin, W.R.[William Randolph],
Augmenting Grid-Based Contours to Improve Thin-Plate DEM Generation,
PhEngRS(71), No. 1, January 2005, pp. 69-81. Gradient paths and intermediate contours improve thin plate DEM approximations from grid-based contour data.
WWW Link. 0509
BibRef

Bonin, O.[Olivier], Rousseaux, F.[Frederic],
Digital Terrain Model Computation from Contour Lines: How to Derive Quality Information from Artifact Analysis,
GeoInfo(9), No. 3, September 2005, pp. 253-268.
Springer DOI 0509
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Maire, C., Datcu, M.,
Earth observation image and DEM information aggregation for realistic 3-D visualization of natural landscapes,
GeoRS(43), No. 11, November 2005, pp. 2676-2683.
IEEE DOI 0512
BibRef

Zhang, L.[Li], Gruen, A.[Armin],
Multi-image matching for DSM generation from IKONOS imagery,
PandRS(60), No. 3, May 2006, pp. 195-211.
Elsevier DOI 0610
High-resolution satellite imagery; IKONOS; Image matching; DSM generation BibRef

Bouillon, A.[Aurélie], Bernard, M.[Marc], Gigord, P.[Patrick], Orsoni, A.[Alain], Rudowski, V.[Véronique], Baudoin, A.[Alain],
SPOT 5 HRS geometric performances: Using block adjustment as a key issue to improve quality of DEM generation,
PandRS(60), No. 3, May 2006, pp. 134-146.
Elsevier DOI 0610
SPOT; HRS; stereoscopic; geometric; performance; calibration; monitoring; block; adjustment; DEM; accuracy BibRef

Kornus, W., Alamús, R., Ruiz, A., Talaya, J.,
DEM generation from SPOT-5 3-fold along track stereoscopic imagery using autocalibration,
PandRS(60), No. 3, May 2006, pp. 147-159.
Elsevier DOI 0610
SPOT; Bundle adjustment; Autocalibration; DEM; Accuracy BibRef

Zebedin, L.[Lukas], Klaus, A.[Andreas], Gruber-Geymayer, B.[Barbara], Karner, K.[Konrad],
Towards 3D map generation from digital aerial images,
PandRS(60), No. 6, September 2006, pp. 413-427.
Elsevier DOI 0610
Aerial triangulation; Dense image matching; Information fusion; True ortho image BibRef

Olson, C.F.[Clark F.], Abi-Rached, H.[Habib],
Wide-baseline stereo vision for terrain mapping,
MVA(21), No. 5, August 2010, pp. 713-725.
WWW Link. 1011
BibRef

Lenk, U.[Ulrich], Heipke, C.[Christian],
The Radial Topology Algorithm: A New Approach for Deriving 2.5D GIS Data Models,
GeoInfo(10), No. 4, December 2006, pp. 447-468.
Springer DOI 0703
BibRef

Chen, Q.[Qi], Gong, P.[Peng], Baldocchi, D.[Dennis], Xie, G.X.[Geng-Xin],
Filtering Airborne Laser Scanning Data with Morphological Methods,
PhEngRS(73), No. 2, February 2007, pp. 175-186.
WWW Link. 0704
A new method for filtering laser scanning data based on morphological methods without slope restrictions, and a method to fill in missing data voids. BibRef

Tsutsui, K., Rokugawa, S., Nakagawa, H., Miyazaki, S., Cheng, C.T., Shiraishi, T., Yang, S.D.,
Detection and Volume Estimation of Large-Scale Landslides Based on Elevation-Change Analysis Using DEMs Extracted From High-Resolution Satellite Stereo Imagery,
GeoRS(45), No. 6, June 2007, pp. 1681-1696.
IEEE DOI 0706
BibRef

Liao, M., Wang, T., Lu, L., Zhou, W., Li, D.,
Reconstruction of DEMs From ERS-1/2 Tandem Data in Mountainous Area Facilitated by SRTM Data,
GeoRS(45), No. 7, July 2007, pp. 2325-2335.
IEEE DOI 0707
BibRef

Poon, J.[Joanne], Fraser, C.S.[Clive S.], Zhang, C.S.[Chun-Sun],
Digital Surface Models from High-Resolution Satellite Imagery,
PhEngRS(73), No. 11, November 2007, pp. 1225-1232.
WWW Link. 0709
An evaluation of commercial-off-the-shelf systems for DEM extraction from high-resolution satellite imagery with comparisons to SRTM. BibRef

Zhang, C.S.[Chun-Sun], Fraser, C.S.[Clive S.],
Generation of Digital Surface Model from High Resolution Satellite Imagery,
ISPRS08(B1: 785 ff).
PDF File. 0807
BibRef

Maddy, E.S., Barnet, C.D.,
Vertical Resolution Estimates in Version 5 of AIRS Operational Retrievals,
GeoRS(46), No. 8, August 2008, pp. 2375-2384.
IEEE DOI 0808
BibRef

Galiatsatos, N.[Nikolaos], Donoghue, D.N.M.[Daniel N. M.], Philip, G.[Graham],
High Resolution Elevation Data Derived from Stereoscopic Corona Imagery with Minimal Ground Control: An Approach Using Ikonos and Srtm Data,
PhEngRS(74), No. 9, September 2008, pp. 1093-1106.
WWW Link. 0804
A methodology to create a high quality DEM from CORONA imagery using horizontal ground control derived from Ikonos space imagery and vertical ground control from map-based contour lines. BibRef

Höhle, J.[Joachim],
DEM Generation Using a Digital Large Format Frame Camera,
PhEngRS(75), No. 1, January 2009, pp. 87-96.
WWW Link. 0902
On the basis of several tests with a digital, large format frame camera and discussions on the recent innovations in hardware and software, the current status in automated photogrammetric DEM generation is presented. BibRef

Milledge, D.G., Lane, S.N., Warburton, J.,
Optimization of Stereo-Matching Algorithms Using Existing DEM Data,
PhEngRS(75), No. 3, March 2009, pp. 323-333.
WWW Link. 0903
Stereo, Matching. A new method that uses existing digital elevation data to identify errors in elevation models and optimize the stereo matching algorithms that generate them. BibRef

Wang, J.F., Christakos, G., Hu, M.G.,
Modeling Spatial Means of Surfaces With Stratified Nonhomogeneity,
GeoRS(47), No. 12, December 2009, pp. 4167-4174.
IEEE DOI 0912
BibRef

Lee, P.J., Effendi, S.[Sutono],
Nongeometric Distortion Smoothing Approach for Depth Map Preprocessing,
MultMed(13), No. 2, 2011, pp. 246-254.
IEEE DOI 1103
BibRef

López, D.H.[David Hernández], García, B.F.[Beatriz Felipe], Piqueras, J.G.[José González], Alcázar, G.V.[Guillermo Villa],
An approach to the radiometric aerotriangulation of photogrammetric images,
PandRS(66), No. 6, November 2011, pp. 883-893.
Elsevier DOI 1112
Aerial images; Radiometric aerotriangulation; Calibration; Atmospheric correction; Bidirectional effects; Kernel-driven models BibRef

Fujisada, H., Urai, M., Iwasaki, A.,
Advanced Methodology for ASTER DEM Generation,
GeoRS(49), No. 12, December 2011, pp. 5080-5091.
IEEE DOI 1201

See also ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD). BibRef

Urai, M., Tachikawa, T., Fujisada, H.,
Data Acquisition Strategies for ASTER Global DEM Generation,
AnnalsPRS(I-4), No. 2012, pp. 199-202.
DOI Link 1209
BibRef

Fujisada, H., Urai, M., Iwasaki, A.,
Technical Methodology for ASTER Global DEM,
GeoRS(50), No. 10, October 2012, pp. 3725-3736.
IEEE DOI 1210

See also ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD). BibRef

Honkavaara, E.[Eija], Markelin, L.[Lauri], Rosnell, T.[Tomi], Nurminen, K.[Kimmo],
Influence of solar elevation in radiometric and geometric performance of multispectral photogrammetry,
PandRS(67), No. 1, January 2012, pp. 13-26.
Elsevier DOI 1202
Point cloud; Radiometry; Matching; Geometry; Photogrammetry BibRef

DeVore, R.[Ronald], Petrova, G.[Guergana], Hielsberg, M.[Matthew], Owens, L.[Luke], Clack, B.[Billy], Sood, A.[Alok],
Processing Terrain Point Cloud Data,
SIIMS(6), No. 1, 2013, pp. 1-31.
DOI Link 1304
BibRef

Robinson, N.[Natalie], Regetz, J.[James], Guralnick, R.P.[Robert P.],
EarthEnv-DEM90: A nearly-global, void-free, multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data,
PandRS(87), No. 1, 2014, pp. 57-67.
Elsevier DOI 1402
Global Digital Elevation Model (DEM) BibRef

Su, Y.J.[Yan-Jun], Guo, Q.H.[Qing-Hua],
A practical method for SRTM DEM correction over vegetated mountain areas,
PandRS(87), No. 1, 2014, pp. 216-228.
Elsevier DOI 1402
Digital elevation model (DEM) BibRef

Jang, W.S.[Woo-Seok], Ho, Y.S.[Yo-Sung],
Efficient depth map generation with occlusion handling for various camera arrays,
SIViP(8), No. 2, February 2014, pp. 287-297.
WWW Link. 1402
BibRef

Jang, W.S.[Woo-Seok], Ho, Y.S.[Yo-Sung],
Discontinuity preserving disparity estimation with occlusion handling,
JVCIR(25), No. 7, 2014, pp. 1595-1603.
Elsevier DOI 1410
Distance transform BibRef

Grumpe, A.[Arne], Wöhler, C.[Christian],
Recovery of elevation from estimated gradient fields constrained by digital elevation maps of lower lateral resolution,
PandRS(94), No. 1, 2014, pp. 37-54.
Elsevier DOI 1407
DEM/DTM generation BibRef

Fan, W.L.[Wei-Liang], Chen, J.M., Ju, W.M.[Wei-Min], Zhu, G.L.[Gao-Long],
GOST: A Geometric-Optical Model for Sloping Terrains,
GeoRS(52), No. 9, September 2014, pp. 5469-5482.
IEEE DOI 1407
terrain mapping BibRef

Fan, Y.C.[Yuan-Chao], Koukal, T.[Tatjana], Weisberg, P.J.[Peter J.],
A sun-crown-sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery,
PandRS(96), No. 1, 2014, pp. 94-105.
Elsevier DOI 1410
Diffuse radiation BibRef

Lee, C.[Changno], Oh, J.[Jaehong], Hong, C.H.[Chang-Hee], Youn, J.[Junhee],
Automated Generation of a Digital Elevation Model Over Steep Terrain in Antarctica From High-Resolution Satellite Imagery,
GeoRS(53), No. 3, March 2015, pp. 1186-1194.
IEEE DOI 1412
digital elevation models BibRef

Chen, C.F.[Chuan-Fa], Li, Y.Y.[Yan-Yan], Yan, C.Q.[Chang-Qing], Dai, H.L.[Hong-Lei], Liu, G.L.[Guo-Lin],
A Robust Algorithm of Multiquadric Method Based on an Improved Huber Loss Function for Interpolating Remote-Sensing-Derived Elevation Data Sets,
RS(7), No. 3, 2015, pp. 3347-3371.
DOI Link 1504
BibRef

Chen, C.F.[Chuan-Fa], Li, Y.Y.[Yan-Yan], Zhao, N.[Na], Yan, C.Q.[Chang-Qing],
Robust Interpolation of DEMs From Lidar-Derived Elevation Data,
GeoRS(56), No. 2, February 2018, pp. 1059-1068.
IEEE DOI 1802
digital elevation models, geophysical image processing, interpolation, iterative methods, optical radar, surface fitting BibRef

Chen, C.F.[Chuan-Fa], Li, Y.Y.[Yan-Yan],
A Fast Global Interpolation Method for Digital Terrain Model Generation from Large LiDAR-Derived Data,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Chen, Q.T.[Qi-Ting], Jia, L.[Li], Hutjes, R.[Ronald], Menenti, M.[Massimo],
Estimation of Aerodynamic Roughness Length over Oasis in the Heihe River Basin by Utilizing Remote Sensing and Ground Data,
RS(7), No. 4, 2015, pp. 3690-3709.
DOI Link 1505
BibRef

Chen, Q.[Qi], Wang, H.[Huan], Zhang, H.C.[Han-Chao], Sun, M.W.[Ming-Wei], Liu, X.G.[Xiu-Guo],
A Point Cloud Filtering Approach to Generating DTMs for Steep Mountainous Areas and Adjacent Residential Areas,
RS(8), No. 1, 2016, pp. 71.
DOI Link 1602
BibRef

Al-Rawabdeh, A.[Abdulla], He, F.N.[Fang-Ning], Moussa, A.[Adel], El-Sheimy, N.[Naser], Habib, A.[Ayman],
Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition,
RS(8), No. 2, 2016, pp. 95.
DOI Link 1603
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Shean, D.E.[David E.], Alexandrov, O.[Oleg], Moratto, Z.M.[Zachary M.], Smith, B.E.[Benjamin E.], Joughin, I.R.[Ian R.], Porter, C.[Claire], Morin, P.[Paul],
An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery,
PandRS(116), No. 1, 2016, pp. 101-117.
Elsevier DOI 1604
WorldView BibRef

Hartmann, W.[Wilfried], Havlena, M.[Michal], Schindler, K.[Konrad],
Recent developments in large-scale tie-point matching,
PandRS(115), No. 1, 2016, pp. 47-62.
Elsevier DOI 1604
Image matching BibRef

Li, H.F.[Hui-Fang], Xu, L.M.[Li-Ming], Shen, H.F.[Huan-Feng], Zhang, L.P.[Liang-Pei],
A general variational framework considering cast shadows for the topographic correction of remote sensing imagery,
PandRS(117), No. 1, 2016, pp. 161-171.
Elsevier DOI 1605
Topographic correction BibRef

Luethje, F.[Fritjof], Tiede, D.[Dirk], Eisank, C.[Clemens],
Terrain Extraction in Built-Up Areas from Satellite Stereo-Imagery-Derived Surface Models: A Stratified Object-Based Approach,
IJGI(6), No. 1, 2017, pp. xx-yy.
DOI Link 1702
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Zhang, Y.F.[Yan-Feng], Zhang, Y.J.[Yong-Jun], Mo, D.[Delin], Zhang, Y.[Yi], Li, X.[Xin],
Direct Digital Surface Model Generation by Semi-Global Vertical Line Locus Matching,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
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Che, E.[Erzhuo], Olsen, M.J.[Michael J.],
Fast ground filtering for TLS data via Scanline Density Analysis,
PandRS(129), No. 1, 2017, pp. 226-240.
Elsevier DOI 1706
Ground, filtering BibRef

Noh, M.J.[Myoung-Jong], Howat, I.M.[Ian M.],
The Surface Extraction from TIN based Search-space Minimization (SETSM) algorithm,
PandRS(129), No. 1, 2017, pp. 55-76.
Elsevier DOI 1706
Stereophotogrammetric BibRef

Dominik, W.A.[Wojciech A.],
Exploiting the Redundancy of Multiple Overlapping Aerial Images for Dense Image Matching Based Digital Surface Model Generation,
RS(9), No. 5, 2017, pp. xx-yy.
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Li, X.H.[Xing-Hua], Shen, H.F.[Huan-Feng], Feng, R.[Ruitao], Li, J.[Jie], Zhang, L.P.[Liang-Pei],
DEM generation from contours and a low-resolution DEM,
PandRS(134), No. Supplement C, 2017, pp. 135-147.
Elsevier DOI 1712
Contours, Dictionary learning, Digital elevation model (DEM), Sparse representation, Spatial regularization BibRef

Liu, X.W.[Xing-Wei], Wang, N.[Ning], Shao, J.L.[Jing-Li], Chu, X.F.[Xue-Feng],
An Automated Processing Algorithm for Flat Areas Resulting from DEM Filling and Interpolation,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
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Rupnik, E.[Ewelina], Pierrot-Deseilligny, M.[Marc], Delorme, A.[Arthur],
3D reconstruction from multi-view VHR-satellite images in MicMac,
PandRS(139), 2018, pp. 201-211.
Elsevier DOI 1804
VHR-satellite imagery, Multi-view, Bundle block adjustment, Dense image matching, Depth map fusion BibRef

Wu, B.[Bo], Liu, W.C.[Wai Chung], Grumpe, A.[Arne], Wöhler, C.[Christian],
Construction of pixel-level resolution DEMs from monocular images by shape and albedo from shading constrained with low-resolution DEM,
PandRS(140), 2018, pp. 3-19.
Elsevier DOI 1805
BibRef
Earlier:
Shape And Albedo From Shading (safs) For Pixel-level Dem Generation From Monocular Images Constrained By Low-resolution Dem,
ISPRS16(B4: 521-527).
DOI Link 1610
Moon, DEM, Shape and albedo from shading, Monocular image, LRO NAC BibRef

Lenoch, M.[Malte], Biebrach, P.[Pia], Grumpe, A.[Arne], Wöhler, C.[Christian],
Multi-view Shape from Shading Constrained by Stereo Image Analysis,
CVS17(325-335).
Springer DOI 1711
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Yang, X.Y.[Xiao-Yan], Li, L.[Long], Chen, L.G.[Long-Gao], Chen, L.Q.[Long-Qian], Shen, Z.P.[Zheng-Ping],
Improving ASTER GDEM Accuracy Using Land Use-Based Linear Regression Methods: A Case Study of Lianyungang, East China,
IJGI(7), No. 4, 2018, pp. xx-yy.
DOI Link 1805
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Fan, W.L.[Wei-Liang], Li, J.[Jing], Liu, Q.H.[Qin-Huo], Zhang, Q.[Qian], Yin, G.F.[Gai-Fei], Li, A.[Ainong], Zeng, Y.[Yelu], Xu, B.D.[Bao-Dong], Xu, X.J.[Xiao-Jun], Zhou, G.[Guomo], Du, H.Q.[Hua-Qiang],
Topographic Correction of Forest Image Data Based on the Canopy Reflectance Model for Sloping Terrains in Multiple Forward Mode,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
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Li, C.M.[Cheng-Ming], Guo, P.P.[Pei-Pei], Wu, P.[Pengda], Liu, X.L.[Xiao-Li],
Extraction of Terrain Feature Lines from Elevation Contours Using a Directed Adjacent Relation Tree,
IJGI(7), No. 5, 2018, pp. xx-yy.
DOI Link 1806
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Li, C.M.[Cheng-Ming], Liu, X.L.[Xiao-Li], Wu, W.[Wei], Hao, Z.W.[Zhi-Wei],
A Reconstruction Method for Broken Contour Lines Based on Similar Contours,
IJGI(8), No. 1, 2018, pp. xx-yy.
DOI Link 1901
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Collings, S.[Simon], Botha, E.J.[Elizabeth J.], Anstee, J.[Janet], Campbell, N.[Norm],
Depth from Satellite Images: Depth Retrieval Using a Stereo and Radiative Transfer-Based Hybrid Method,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
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Shahbazi, M.[Mozhdeh], Sohn, G.[Gunho], Théau, J.[Jérome],
High-density stereo image matching using intrinsic curves,
PandRS(146), 2018, pp. 373-388.
Elsevier DOI 1812
Dense matching, Intrinsic curves, Disparity search space, Occlusion, Energy function, Optimization BibRef

Oliveira, R.A.[Raquel A.], Tommaselli, A.M.G.[Antonio M.G.], Honkavaara, E.[Eija],
Generating a hyperspectral digital surface model using a hyperspectral 2D frame camera,
PandRS(147), 2019, pp. 345-360.
Elsevier DOI 1901
Image matching, Hyperspectral digital surface model, Hyperspectral 2D frame camera, Forest BibRef

Bittner, K.[Ksenia], d'Angelo, P.[Pablo], Körner, M.[Marco], Reinartz, P.[Peter],
DSM-to-LoD2: Spaceborne Stereo Digital Surface Model Refinement,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
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Bittner, K.[Ksenia], Körner, M.[Marco], Fraundorfer, F.[Friedrich], Reinartz, P.[Peter],
Multi-Task cGAN for Simultaneous Spaceborne DSM Refinement and Roof-Type Classification,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
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Campos, R.[Ricard], Quintana, J.[Josep], Garcia, R.[Rafael], Schmitt, T.[Thierry], Spoelstra, G.[George], Schaap, D.M.A.[Dick M. A.],
3D Simplification Methods and Large Scale Terrain Tiling,
RS(12), No. 3, 2020, pp. xx-yy.
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Yang, W.H.[Wen-Huan], Li, X.[Xin], Yang, B.[Bo], Fu, Y.[Yu],
A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
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Koziol, K.[Krystian], Maciuk, K.[Kamil],
New Heights of the Highest Peaks of Polish Mountain Ranges,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
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DOI Link 2205
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Ren, H.[He], Zhao, Y.L.[Yan-Ling], Xiao, W.[Wu], Wang, X.[Xin], Sui, T.[Tao],
An Improved Ground Control Point Configuration for Digital Surface Model Construction in a Coal Waste Dump Using an Unmanned Aerial Vehicle System,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
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Zarychta, R.[Roksana], Zarychta, A.[Adrian], Bzdega, K.[Katarzyna],
Progress in the Reconstruction of Terrain Relief Before Extraction of Rock Materials: The Case of Liban Quarry, Poland,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
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Wagle, N.[Nimisha], Acharya, T.D.[Tri Dev],
Past and Present Practices of Topographic Base Map Database Update in Nepal,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link 2006
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Syzdykbayev, M.[Meirman], Karimi, B.[Bobak], Karimi, H.A.[Hassan A.],
A Method for Extracting Some Key Terrain Features from Shaded Relief of Digital Terrain Models,
RS(12), No. 17, 2020, pp. xx-yy.
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Oh, J.H.[Jae-Hong], Han, Y.K.[You-Kyung],
A Double Epipolar Resampling Approach to Reliable Conjugate Point Extraction for Accurate Kompsat-3/3A Stereo Data Processing,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
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Kruk, E.[Edyta], Klapa, P.[Przemyslaw], Ryczek, M.[Marek], Ostrowski, K.[Krzysztof],
Influence of DEM Elaboration Methods on the USLE Model Topographical Factor Parameter on Steep Slopes,
RS(12), No. 21, 2020, pp. xx-yy.
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Tenthoff, M.[Moritz], Wohlfarth, K.[Kay], Wöhler, C.[Christian],
High Resolution Digital Terrain Models of Mercury,
RS(12), No. 23, 2020, pp. xx-yy.
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Wyszkowska, P.[Patrycja], Duchnowski, R.[Robert], Dumalski, A.[Andrzej],
Determination of Terrain Profile from TLS Data by Applying Msplit Estimation,
RS(13), No. 1, 2021, pp. xx-yy.
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Bhushan, S.[Shashank], Shean, D.[David], Alexandrov, O.[Oleg], Henderson, S.[Scott],
Automated digital elevation model (DEM) generation from very-high-resolution Planet SkySat triplet stereo and video imagery,
PandRS(173), 2021, pp. 151-165.
Elsevier DOI 2102
Photogrammetry, Stereo, Structure from motion (SfM), Commercial satellite imagery, SmallSat, CubeSat BibRef

Maciuk, K.[Kamil], Apollo, M.[Michal], Mostowska, J.[Joanna], Lepeška, T.[Tomáš], Poklar, M.[Mojca], Noszczyk, T.[Tomasz], Kroh, P.[Pawel], Krawczyk, A.[Artur], Borowski, L.[Lukasz], Pavlovcic-Prešeren, P.[Polona],
Altitude on Cartographic Materials and Its Correction According to New Measurement Techniques,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
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Yan, L.[Li], Tang, X.F.[Xing-Fen], Zhang, Y.[Yi],
High Accuracy Interpolation of DEM Using Generative Adversarial Network,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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Lastilla, L.[Lorenzo], Belloni, V.[Valeria], Ravanelli, R.[Roberta], Crespi, M.[Mattia],
DSM Generation from Single and Cross-Sensor Multi-View Satellite Images Using the New Agisoft Metashape: The Case Studies of Trento and Matera (Italy),
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Tao, Y.[Yu], Michael, G.[Greg], Muller, J.P.[Jan-Peter], Conway, S.J.[Susan J.], Putri, A.R.D.[Alfiah R. D.],
Seamless 3D Image Mapping and Mosaicing of Valles Marineris on Mars Using Orbital HRSC Stereo and Panchromatic Images,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Roncella, R.[Riccardo], Bruno, N.[Nazarena], Diotri, F.[Fabrizio], Thoeni, K.[Klaus], Giacomini, A.[Anna],
Photogrammetric Digital Surface Model Reconstruction in Extreme Low-Light Environments,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
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Yu, A.Z.[An-Zhu], Guo, W.[Wenyue], Liu, B.[Bing], Chen, X.[Xin], Wang, X.[Xin], Cao, X.F.[Xue-Feng], Jiang, B.C.[Bing-Chuan],
Attention aware cost volume pyramid based multi-view stereo network for 3D reconstruction,
PandRS(175), 2021, pp. 448-460.
Elsevier DOI 2105
Multi-view stereo, 3D Reconstruction, Cost Volume, Coarse-to-fine, Deep Learning BibRef

Jurjevic, L.[Luka], Gašparovic, M.[Mateo], Liang, X.[Xinlian], Balenovic, I.[Ivan],
Assessment of Close-Range Remote Sensing Methods for DTM Estimation in a Lowland Deciduous Forest,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Tao, Y.[Yu], Douté, S.[Sylvain], Muller, J.P.[Jan-Peter], Conway, S.J.[Susan J.], Thomas, N.[Nicolas], Cremonese, G.[Gabriele],
Ultra-High-Resolution 1 m/pixel CaSSIS DTM Using Super-Resolution Restoration and Shape-from-Shading: Demonstration over Oxia Planum on Mars,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Lai, Z.C.[Zheng-Chao], Liu, F.[Fei], Guo, S.W.[Shang-Wei], Meng, X.T.[Xian-Tong], Han, S.[Shaokun], Li, W.H.[Wen-Hao],
Onboard Real-Time Dense Reconstruction in Large Terrain Scene Using Embedded UAV Platform,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Tao, Y.[Yu], Xiong, S.[Siting], Conway, S.J.[Susan J.], Muller, J.P.[Jan-Peter], Guimpier, A.[Anthony], Fawdon, P.[Peter], Thomas, N.[Nicolas], Cremonese, G.[Gabriele],
Rapid Single Image-Based DTM Estimation from ExoMars TGO CaSSIS Images Using Generative Adversarial U-Nets,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Štroner, M.[Martin], Urban, R.[Rudolf], Lidmila, M.[Martin], Kolár, V.[Vilém], Kremen, T.[Tomáš],
Vegetation Filtering of a Steep Rugged Terrain: The Performance of Standard Algorithms and a Newly Proposed Workflow on an Example of a Railway Ledge,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Tao, Y.[Yu], Muller, J.P.[Jan-Peter], Conway, S.J.[Susan J.], Xiong, S.[Siting],
Large Area High-Resolution 3D Mapping of Oxia Planum: The Landing Site for the ExoMars Rosalind Franklin Rover,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Li, J.Q.[Jian-Qiang], Chen, Z.Z.[Zhuang-Zhuang], Chen, J.[Jie], Lin, Q.Z.[Qiu-Zhen],
Diversity-Sensitive Generative Adversarial Network for Terrain Mapping Under Limited Human Intervention,
Cyber(51), No. 12, December 2021, pp. 6029-6040.
IEEE DOI 2112
Generative adversarial networks, Data models, Training data, Robots, Terrain mapping, Collaboration, multiagent system BibRef

Stucker, C.[Corinne], Schindler, K.[Konrad],
ResDepth: A deep residual prior for 3D reconstruction from high-resolution satellite images,
PandRS(183), 2022, pp. 560-580.
Elsevier DOI 2201
Convolutional neural network (CNN), 3D reconstruction, Digital surface model (DSM), Scene refinement, Satellite imagery BibRef

Qi, C.[Chen], Liu, S.C.[Shao-Chuang], Xu, Y.M.[Ya-Ming], Xu, A.G.[Ai-Gong], Zhang, J.L.[Jian-Li], Ma, Y.Q.[You-Qing], Li, M.L.[Ming-Lei], Xu, X.C.[Xin-Chao], Yang, H.[Huan], Yan, Y.Z.[Yong-Zhe],
Trajectory Recovery and Terrain Reconstruction Based on Descent Images under Dual-Restrained Conditions: Tianwen-1,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
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Li, S.J.[Si-Jin], Li, K.[Ke], Xiong, L.Y.[Li-Yang], Tang, G.[Guoan],
Generating Terrain Data for Geomorphological Analysis by Integrating Topographical Features and Conditional Generative Adversarial Networks,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Dong, Y.T.[Yu-Ting], Zhao, J.[Ji], Li, C.Y.[Cai-Yong], Liao, M.S.[Ming-Sheng],
Gapless-REMA100: A gapless 100-m reference elevation model of Antarctica with voids filled by multi-source DEMs,
PandRS(186), 2022, pp. 70-82.
Elsevier DOI 2203
Reference Elevation Model of Antarctica (REMA), Digital Elevation Model (DEM), Gapless, Void-fill, Delta surface method BibRef

White, C.T.[Corey T.], Reckling, W.[William], Petrasova, A.[Anna], Meentemeyer, R.K.[Ross K.], Mitasova, H.[Helena],
Rapid-DEM: Rapid Topographic Updates through Satellite Change Detection and UAS Data Fusion,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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Pan, Y.W.[Yun-Wen], Xia, J.Q.[Jun-Qiang], Yang, K.[Kejun],
A Method for Digital Terrain Reconstruction Using Longitudinal Control Lines and Sparse Measured Cross Sections,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
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Pimenova, O.[Olga], Roberts, C.[Craig], Rizos, C.[Chris],
Regional 'Bare-Earth' Digital Terrain Model for Costa Rica Based on NASADEM Corrected for Vegetation Bias,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Arévalo-Verjel, A.N.[Alba Nely], Lerma, J.L.[José Luis], Prieto, J.F.[Juan F.], Carbonell-Rivera, J.P.[Juan Pedro], Fernández, J.[José],
Estimation of the Block Adjustment Error in UAV Photogrammetric Flights in Flat Areas,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Liao, P.[Puyun], Chen, G.Z.[Guan-Zhou], Zhang, X.D.[Xiao-Dong], Zhu, K.[Kun], Gong, Y.F.[Yuan-Fu], Wang, T.[Tong], Li, X.W.[Xian-Wei], Yang, H.[Haobo],
A linear pushbroom satellite image epipolar resampling method for digital surface model generation,
PandRS(190), 2022, pp. 56-68.
Elsevier DOI 2208
Epipolar Resampling, Linear Pushbroom Sensor Satellite, Ortho Rectification, Rational Function Model, Digital Surface Model BibRef

Chen, X.N.[Xiao-Nan], Wang, J.[Jun], Peng, Q.H.[Qi-Hang], Zhang, G.Y.[Guo-Yong],
A Constrained Block-Term Tensor Decomposition Framework for Spectrum Cartography,
SPLetters(29), 2022, pp. 1699-1703.
IEEE DOI 2208
Tensors, Noise robustness, Manifolds, Complexity theory, Radio transmitters, Matrix decomposition, Convergence, tensor completion BibRef

Aires, A.S.[Alysson Soares], Junior, A.M.[Ademir Marques], Zanotta, D.C.[Daniel Capella], Spigolon, A.L.D.[André Luiz Durante], Veronez, M.R.[Mauricio Roberto], Gonzaga, L.[Luiz],
Digital Outcrop Model Generation from Hybrid UAV and Panoramic Imaging Systems,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
Top view terrain is not sufficient. BibRef

Zhang, X.[Xin], Xie, B.[Baorong], Liu, S.J.[Shi-Jie], Tong, X.H.[Xiao-Hua], Ding, R.[Rongli], Xie, H.[Huan], Hong, Z.H.[Zhong-Hua],
A Two-Step Block Adjustment Method for DSM Accuracy Improvement with Elevation Control of ICESat-2 Data,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Wong, L.[Leslie], Vien, B.S.[Benjamin Steven], Kuen, T.[Thomas], Bui, D.N.[Dat Nha], Kodikara, J.[Jayantha], Chiu, W.K.[Wing Kong],
Non-Contact In-Plane Movement Estimation of Floating Covers Using Finite Element Formulation on Field-Scale DEM,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Tao, P.J.[Peng-Jie], Xi, K.[Ke], Niu, Z.Q.[Zhuang-Qun], Chen, Q.[Qi], Liao, Y.F.[Yi-Fan], Liu, Y.X.[Yu-Xuan], Liu, K.B.[Kun-Bo], Zhang, Z.X.[Zu-Xun],
Optimal selection from extremely redundant satellite images for efficient large-scale mapping,
PandRS(194), 2022, pp. 21-38.
Elsevier DOI 2212
Chosse best iamges. Optical satellite images, Data redundancy reduction, Optimized image retrieval, Large-scale mapping, Markov random field BibRef

Lv, B.[Benchao], Liu, J.C.[Jian-Chen], Wang, P.[Ping], Yasir, M.[Muhammad],
DSM Generation from Multi-View High-Resolution Satellite Images Based on the Photometric Mesh Refinement Method,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
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Zhao, W.F.[Wu-Fan], Persello, C.[Claudio], Stein, A.[Alfred],
Semantic-aware unsupervised domain adaptation for height estimation from single-view aerial images,
PandRS(196), 2023, pp. 372-385.
Elsevier DOI 2302
Height estimation, Unsupervised domain adaptation, Semantic consistency, Generative adversarial network, Optical remote sensing imagery BibRef

Xu, S.B.[Shi-Biao], Pan, B.B.[Bing-Bing], Zhang, J.G.[Ji-Guang], Zhang, X.P.[Xiao-Peng],
Accurate and Serialized Dense Point Cloud Reconstruction for Aerial Video Sequences,
RS(15), No. 6, 2023, pp. 1625.
DOI Link 2304
serialized structure-from-motion (SfM) and dense point cloud reconstruction. BibRef

Zhang, T.Q.[Tian-Qi], Liu, D.[Desheng],
Reconstructing Digital Terrain Models from ArcticDEM and WorldView-2 Imagery in Livengood, Alaska,
RS(15), No. 8, 2023, pp. 2061.
DOI Link 2305
BibRef

Li, S.J.[Si-Jin], Yang, X.[Xin], Zhou, X.Y.[Xing-Yu], Tang, G.[Guoan],
Quantification of Surface Pattern Based on the Binary Terrain Structure in Mountainous Areas,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Wen, L.[Lekang], He, J.[Jun], Huang, X.[Xu],
Mountain Segmentation Based on Global Optimization with the Cloth Simulation Constraint,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Dai, W.[Wen], Qiu, R.[Ruibo], Wang, B.[Bo], Lu, W.D.[Wang-Da], Zheng, G.H.[Guang-Hui], Amankwah, S.O.Y.[Solomon Obiri Yeboah], Wang, G.J.[Guo-Jie],
Enhancing UAV-SfM Photogrammetry for Terrain Modeling from the Perspective of Spatial Structure of Errors,
RS(15), No. 17, 2023, pp. 4305.
DOI Link 2310
BibRef

Yao, S.[Shun], Cheng, Y.M.[Yong-Mei], Yang, F.[Fei], Mozerov, M.G.[Mikhail G.],
A continuous digital elevation representation model for DEM super-resolution,
PandRS(208), 2024, pp. 1-13.
Elsevier DOI Code:
WWW Link. 2402
DEM super-resolution, Neural implicit representation, Continuous DEM model, Elevation bias prediction BibRef

Odriozola, G.M.[Gonzalo Muradás], Pauly, K.[Klaas], Oswald, S.[Samuel], Raymaekers, D.[Dries],
Automating Ground Control Point Detection in Drone Imagery: From Computer Vision to Deep Learning,
RS(16), No. 5, 2024, pp. 794.
DOI Link 2403
BibRef

Gosciewski, D.[Dariusz], Gerus-Gosciewska, M.[Malgorzata], Szczepanska, A.[Agnieszka],
Application of Polynomial Interpolation for Iterative Complementation of the Missing Nodes in a Regular Network of Squares Used for the Construction of a Digital Terrain Model,
RS(16), No. 6, 2024, pp. 999.
DOI Link 2403
BibRef

Naeini, A.A.[Amin Alizadeh], Sheikholeslami, M.M.[Mohammad Moein], Sohn, G.[Gunho],
Advancing Physically Informed Autoencoders for DTM Generation,
RS(16), No. 11, 2024, pp. 1841.
DOI Link 2406
BibRef

Lin, H.[Huai], Yang, Y.[Yuande], Li, L.Y.[Lei-Yu], Wang, Q.H.[Qi-Hua], Guo, M.[Minyi],
Elevation Changes of A'nyemaqen Snow Mountain Revealed with Satellite Remote Sensing,
RS(16), No. 13, 2024, pp. 2446.
DOI Link 2407
BibRef

Wan, Q.F.[Qi-Feng], Guan, Y.Z.[Yu-Zheng], Zhao, Q.[Qiang], Wen, X.[Xiang], She, J.F.[Jiang-Feng],
Constraining the Geometry of NeRFs for Accurate DSM Generation from Multi-View Satellite Images,
IJGI(13), No. 7, 2024, pp. 243.
DOI Link 2408
BibRef

Jain, A.[Aryamaan], Sharma, A.[Avinash], Rajan, K.S.,
Learning Based Infinite Terrain Generation with Level of Detailing,
3DV24(1048-1058)
IEEE DOI 2408
Training, Solid modeling, Image edge detection, Computational modeling, Superresolution, Games, terrain generation, terrain super-resolution BibRef

Gómez, A.[Alvaro], Randall, G.[Gregory], Facciolo, G.[Gabriele], von Gioi, R.G.[Rafael Grompone],
Improving the Pair Selection and the Model Fusion Steps of Satellite Multi-View Stereo Pipelines,
WACV23(6333-6342)
IEEE DOI 2302
Point cloud compression, Satellites, Systematics, Computational modeling, Pipelines, Predictive models, Applications: Remote Sensing BibRef

Gómez, A.[Alvaro], Randall, G.[Gregory], Facciolo, G.[Gabriele], von Gioi, R.G.[Rafael Grompone],
An experimental comparison of multi-view stereo approaches on satellite images,
WACV22(707-716)
IEEE DOI 2202
Deep learning, Training, Satellites, Pipelines, Imaging, Image reconstruction, Remote Sensing Stereo Processing BibRef

Bullinger, S., Bodensteiner, C., Arens, M.,
3D Surface Reconstruction From Multi-date Satellite Images,
ISPRS21(B2-2021: 313-320).
DOI Link 2201
BibRef

d'Angelo, P., Reinartz, P.,
Digital Elevation Models From Stereo, Video and Multi-view Imagery Captured By Small Satellites,
ISPRS21(B2-2021: 77-82).
DOI Link 2201
BibRef

Zhao, H.[Huai], Guo, L.[Li], Wang, X.[Xia], Huang, B.[Bo], Wang, Y.Z.[Yi-Zhe], Xie, S.[Sanwu], Zhu, R.Y.[Ren-Yi], Wang, Y.Y.[Yang-Yang], Liu, J.X.[Jia-Xing],
Improved Global 1:50000 Scale Surveying and Mapping 4D Product Generation Approach Using the Public Geographic Information Data,
ICIVC21(367-371)
IEEE DOI 2112
Satellites, Europe, Standards, Remote sensing, global 1:50000 scale surveying and mapping, block adjustment, public geographic information data BibRef

Liu, X., Zhang, Y., Huang, X., Wan, Y., Zhang, Y., Wang, S.,
Terrain-adaptive Ground Filtering of Airborne Lidar Data Based On Saliency-aware Thin Plate Spline,
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Bittner, K., Liebel, L., Körner, M., Reinartz, P.,
Long-short Skip Connections In Deep Neural Networks for DSM Refinement,
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Mahphood, A., Arefi, H., Hosseininaveh, A., Naeini, A.A.,
Dense Multi-view Image Matching for DSM Generation From Satellite Images,
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Li, Z., Wegner, J.D., Lucchi, A.,
Topological Map Extraction From Overhead Images,
ICCV19(1715-1724)
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cartography, feature extraction, geophysical image processing, graph theory, image representation, image segmentation, Machine learning BibRef