{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:40:13Z","timestamp":1760233213723,"version":"build-2065373602"},"reference-count":62,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ESA Third Party Mission project","award":["67754","BO 2933\/3-1","IGK 2018","491466077"],"award-info":[{"award-number":["67754","BO 2933\/3-1","IGK 2018","491466077"]}]},{"name":"DFG","award":["67754","BO 2933\/3-1","IGK 2018","491466077"],"award-info":[{"award-number":["67754","BO 2933\/3-1","IGK 2018","491466077"]}]},{"name":"IRTG-StRATEGy","award":["67754","BO 2933\/3-1","IGK 2018","491466077"],"award-info":[{"award-number":["67754","BO 2933\/3-1","IGK 2018","491466077"]}]},{"name":"MWFK Brandenburg, Germany","award":["67754","BO 2933\/3-1","IGK 2018","491466077"],"award-info":[{"award-number":["67754","BO 2933\/3-1","IGK 2018","491466077"]}]},{"name":"Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)","award":["67754","BO 2933\/3-1","IGK 2018","491466077"],"award-info":[{"award-number":["67754","BO 2933\/3-1","IGK 2018","491466077"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The generation of Digital Elevation Models (DEMs) through stereogrammetry of optical satellite images has gained great popularity across various disciplines. For the analysis of these DEMs, it is important to understand the influence of the input data and different processing steps and parameters employed during stereo correlation. Here, we explore the effects that image texture, as well as the use of different matching algorithms (Block Matching (BM) and More Global Matching (MGM)), can have on optical DEMs derived from the flexible, open-source Ames Stereo Pipeline. Our analysis relies on a \u223c2700 km2 clip of a SPOT6 tristereo scene covering the hyperarid, vegetation-free Pocitos Basin and adjacent mountain ranges in the northwestern Argentine Andes. A large, perfectly flat salt pan (paleolake bed) that covers the center of this basin is characterized by strong contrasts in image texture, providing a unique opportunity to quantitatively study the relationship between image texture and DEM quality unaffected by topography. Our findings suggest that higher image texture, measured by panchromatic variance, leads to lower DEM uncertainty. This improvement continues up to \u223c103 panchromatic variance, above which further improvements in DEM quality are independent of local image texture but instead may have sensor or geometric origins. Based on this behavior, we propose that image texture may serve as an important proxy of DEM quality prior to stereo correlation and can help to set adequate processing parameters. With respect to matching algorithms, we observe that MGM improves matching in low-texture areas and overall generates a smoother surface that still preserves complex, narrow (i.e., ridge and valley) features. Based on this sharper representation of the landscape, we conclude that MGM should be preferred for geomorphic applications relying on stereo-derived DEMs. However, we note that the correlation kernel selected for stereo-matching must be carefully chosen depending on local image texture, whereby larger kernels generate more accurate matches (less artifacts) at the cost of smoothing results. Overall, our analysis suggests a path forward for the processing and fusion of overlapping satellite images with suitable view-angle differences to improve final DEMs.<\/jats:p>","DOI":"10.3390\/rs15010085","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T07:31:56Z","timestamp":1672126316000},"page":"85","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Image Texture as Quality Indicator for Optical DEM Generation: Geomorphic Applications in the Arid Central Andes"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8504-8115","authenticated-orcid":false,"given":"Benjamin","family":"Purinton","sequence":"first","affiliation":[{"name":"Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5715-1801","authenticated-orcid":false,"given":"Ariane","family":"Mueting","sequence":"additional","affiliation":[{"name":"Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1323-6453","authenticated-orcid":false,"given":"Bodo","family":"Bookhagen","sequence":"additional","affiliation":[{"name":"Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1016\/S0098-3004(99)00019-9","article-title":"DEM generation by contour line dilation","volume":"25","author":"Taud","year":"1999","journal-title":"Comput. Geosci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Polidori, L., and El Hage, M. (2020). Digital Elevation Model Quality Assessment Methods: A Critical Review. Remote Sens., 12.","DOI":"10.3390\/rs12213522"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6456","DOI":"10.1109\/JSTARS.2022.3188922","article-title":"Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain","volume":"15","author":"Hugonnet","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6267","DOI":"10.1002\/2016GL069457","article-title":"High-resolution digital elevation model from tri-stereo Pleiades-1 satellite imagery for lava flow volume estimates at Fogo Volcano","volume":"43","author":"Bagnardi","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1002\/2017JF004512","article-title":"Using Stereo Satellite Imagery to Account for Ablation, Entrainment, and Compaction in Volume Calculations for Rock Avalanches on Glaciers: Application to the 2016 Lamplugh Rock Avalanche in Glacier Bay National Park, Alaska","volume":"123","author":"Coe","year":"2018","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.geomorph.2019.03.016","article-title":"DEM generation from Worldview-2 stereo imagery and vertical accuracy assessment for its application in active tectonics","volume":"336","author":"Wang","year":"2019","journal-title":"Geomorphology"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"363","DOI":"10.3389\/feart.2019.00363","article-title":"A Systematic, Regional Assessment of High Mountain Asia Glacier Mass Balance","volume":"7","author":"Shean","year":"2020","journal-title":"Front. Earth Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"W11519","DOI":"10.1029\/2012WR012223","article-title":"Modeling river bed morphology, roughness, and surface sedimentology using high resolution terrestrial laser scanning","volume":"48","author":"Brasington","year":"2012","journal-title":"Water Resour. Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"359","DOI":"10.5194\/esurf-4-359-2016","article-title":"Image-based surface reconstruction in geomorphometry\u2014Merits, limits and developments","volume":"4","author":"Eltner","year":"2016","journal-title":"Earth Surf. Dyn."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"211","DOI":"10.5194\/esurf-5-211-2017","article-title":"Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau","volume":"5","author":"Purinton","year":"2017","journal-title":"Earth Surf. Dyn."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"225","DOI":"10.3389\/feart.2018.00225","article-title":"The Need for a High-Accuracy, Open-Access Global DEM","volume":"6","author":"Schumann","year":"2018","journal-title":"Front. Earth Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"475","DOI":"10.5194\/esurf-7-475-2019","article-title":"Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset","volume":"7","author":"Smith","year":"2019","journal-title":"Earth Surf. Dyn."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"271","DOI":"10.5194\/tc-5-271-2011","article-title":"Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change","volume":"5","author":"Nuth","year":"2011","journal-title":"The Cryosphere"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Girod, L., Nuth, C., K\u00e4\u00e4b, A., McNabb, R., and Galland, O. (2017). MMASTER: Improved ASTER DEMs for Elevation Change Monitoring. Remote Sens., 9.","DOI":"10.3390\/rs9070704"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"758606","DOI":"10.3389\/feart.2021.758606","article-title":"Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes","volume":"9","author":"Purinton","year":"2021","journal-title":"Front. Earth Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1130\/G30013A.1","article-title":"Beyond threshold hillslopes: Channel adjustment to base-level fall in tectonically active mountain ranges","volume":"37","author":"Ouimet","year":"2009","journal-title":"Geology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.epsl.2012.02.005","article-title":"Spatiotemporal trends in erosion rates across a pronounced rainfall gradient: Examples from the southern Central Andes","volume":"327\u2013328","author":"Bookhagen","year":"2012","journal-title":"Earth Planet. Sci. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"821","DOI":"10.5194\/esurf-5-821-2017","article-title":"Bumps in river profiles: Uncertainty assessment and smoothing using quantile regression techniques","volume":"5","author":"Schwanghart","year":"2017","journal-title":"Earth Surf. Dyn."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"233","DOI":"10.3389\/feart.2018.00233","article-title":"Perspectives on Digital Elevation Model (DEM) Simulation for Flood Modeling in the Absence of a High-Accuracy Open Access Global DEM","volume":"6","author":"Hawker","year":"2018","journal-title":"Front. Earth Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"211","DOI":"10.5194\/esurf-7-211-2019","article-title":"A segmentation approach for the reproducible extraction and quantification of knickpoints from river long profiles","volume":"7","author":"Gailleton","year":"2019","journal-title":"Earth Surf. Dyn."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e2021JF006330","DOI":"10.1029\/2021JF006330","article-title":"Identification of Debris-Flow Channels Using High-Resolution Topographic Data: A Case Study in the Quebrada del Toro, NW Argentina","volume":"126","author":"Mueting","year":"2021","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, K., Sun, J., and Snavely, N. (2019). Leveraging Vision Reconstruction Pipelines for Satellite Imagery. arXiv.","DOI":"10.1109\/ICCVW.2019.00269"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.isprsjprs.2016.03.012","article-title":"An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery","volume":"116","author":"Shean","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1029\/2018EA000409","article-title":"The Ames Stereo Pipeline: NASA\u2019s Open Source Software for Deriving and Processing Terrain Data","volume":"5","author":"Beyer","year":"2018","journal-title":"Earth Space Sci."},{"key":"ref_25","unstructured":"Beyer, R., Alexandrov, O., McMichael, S., Broxton, M., Lundy, M., Husmann, K., Edwards, L., Nefian, A., Smith, B., and Shean, D. (2022, September 28). NeoGeographyToolkit\/StereoPipeline 3.0.0. Available online: https:\/\/zenodo.org\/record\/5140581#.Y6FiCBVBy70."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3289","DOI":"10.3390\/s90503289","article-title":"A Procedure for High Resolution Satellite Imagery Quality Assessment","volume":"9","author":"Crespi","year":"2009","journal-title":"Sensors"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.isprsjprs.2014.04.007","article-title":"Radiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pl\u00e9iades-1A stereo images for 3D information extraction","volume":"100","author":"Poli","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1146\/annurev.earth.25.1.139","article-title":"The evolution of the altiplano-puna plateau of the central andes","volume":"25","author":"Allmendinger","year":"1997","journal-title":"Annu. Rev. Earth Planet. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1146\/annurev.earth.35.031306.140158","article-title":"Tectonics and Climate of the Southern Central Andes","volume":"35","author":"Strecker","year":"2007","journal-title":"Annu. Rev. Earth Planet. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Bookhagen, B., and Strecker, M.R. (2008). Orographic barriers, high-resolution TRMM rainfall, and relief variations along the eastern Andes. Geophys. Res. Lett., 35.","DOI":"10.1029\/2007GL032011"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.epsl.2018.07.034","article-title":"Glacial chronology and production rate cross-calibration of five cosmogenic nuclide and mineral systems from the southern Central Andean Plateau","volume":"500","author":"Luna","year":"2018","journal-title":"Earth Planet. Sci. Lett."},{"key":"ref_32","unstructured":"Leister-Taylor, V., Jacob, P., Schrader, H., and Kahabka, H. (2020). Copernicus Digital Elevation Model Product Handbook, AIRBUS. Technical Report GEO.2018-1988-2."},{"key":"ref_33","unstructured":"AIRBUS (2022, September 28). SPOT Imagery User Guide; Technical Report; AIRBUS and ESA: 2022. Available online: https:\/\/earth.esa.int\/eogateway\/documents\/20142\/37627\/SPOT-6-7-imagery-user-guide.pdf."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"566802","DOI":"10.3389\/feart.2020.566802","article-title":"Automated Processing of Declassified KH-9 Hexagon Satellite Images for Global Elevation Change Analysis Since the 1970s","volume":"8","author":"Dehecq","year":"2020","journal-title":"Front. Earth Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.isprsjprs.2020.12.012","article-title":"Automated digital elevation model (DEM) generation from very-high-resolution Planet SkySat triplet stereo and video imagery","volume":"173","author":"Bhushan","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s11265-006-4190-4","article-title":"Survey on block matching motion estimation algorithms and architectures with new results","volume":"42","author":"Huang","year":"2006","journal-title":"J. VLSI Signal Process. Syst. Signal Image Video Technol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/TPAMI.2007.1166","article-title":"Stereo Processing by Semiglobal Matching and Mutual Information","volume":"30","author":"Hirschmuller","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Bebis, G., Boyle, R., Parvin, B., Koracin, D., Kuno, Y., Wang, J., Wang, J.X., Wang, J., Pajarola, R., and Lindstrom, P. (2009). 3D Lunar Terrain Reconstruction from Apollo Images. International Symposium on Visual Computing, Springer.","DOI":"10.1007\/978-3-642-10331-5"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Nefian, A.V., Husmann, K., Broxton, M., To, V., Lundy, M., and Hancher, M.D. (2009, January 7\u201310). A bayesian formulation for sub-pixel refinement in stereo orbital imagery. Proceedings of the 2009 16th IEEE International Conference on Image Processing (ICIP), Cairo, Egypt.","DOI":"10.1109\/ICIP.2009.5413749"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Facciolo, G., Franchis, C.D., and Meinhardt, E. (2015). MGM: A Significantly More Global Matching for Stereovision. British Machine Vision Conference 2015 (BMVC 2015), BMVA Press.","DOI":"10.5244\/C.29.90"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"59","DOI":"10.5194\/isprs-annals-III-3-59-2016","article-title":"Texture-aware dense image matching using ternary census transform","volume":"III-3","author":"Hu","year":"2016","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"627","DOI":"10.5194\/esurf-4-627-2016","article-title":"How does grid-resolution modulate the topographic expression of geomorphic processes?","volume":"4","author":"Grieve","year":"2016","journal-title":"Earth Surf. Dyn."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1016\/j.isprsjprs.2009.02.003","article-title":"Accuracy assessment of digital elevation models by means of robust statistical methods","volume":"64","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural Features for Image Classification","volume":"SMC-3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.cageo.2015.04.003","article-title":"MAD: Robust image texture analysis for applications in high resolution geomorphometry","volume":"81","author":"Trevisani","year":"2015","journal-title":"Comput. Geosci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"4823","DOI":"10.1109\/TGRS.2013.2285187","article-title":"Assessing global digital elevation models using the runway method: The advanced spaceborne thermal emission and reflection radiometer versus the shuttle radar topography mission case","volume":"52","author":"Becek","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","unstructured":"Mudd, S.M., Clubb, F.J., Grieve, S.W.D., Milodowski, D.T., Hurst, M.D., Gailleton, B., and Valters, D.A. (2022, September 28). LSDTopoTools2. Available online: https:\/\/zenodo.org\/record\/3245041#.Y6FeVhVBy70."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"103414","DOI":"10.1016\/j.earscirev.2020.103414","article-title":"A comprehensive system of definitions of land surface (topographic) curvatures, with implications for their application in geoscience modelling and prediction","volume":"211","author":"Evans","year":"2020","journal-title":"Earth-Sci. Rev."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Hurst, M.D., Mudd, S.M., Walcott, R., Attal, M., and Yoo, K. (2012). Using hilltop curvature to derive the spatial distribution of erosion rates. J. Geophys. Res. Earth Surf., 117.","DOI":"10.1029\/2011JF002057"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1002\/esp.3884","article-title":"How long is a hillslope?","volume":"41","author":"Grieve","year":"2016","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"309","DOI":"10.5194\/esurf-4-309-2016","article-title":"A nondimensional framework for exploring the relief structure of landscapes","volume":"4","author":"Grieve","year":"2016","journal-title":"Earth Surf. Dyn."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"4283","DOI":"10.1002\/2013WR015167","article-title":"Objective extraction of channel heads from high-resolution topographic data","volume":"50","author":"Clubb","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1724","DOI":"10.1002\/2015JF003747","article-title":"The relationship between drainage density, erosion rate, and hilltop curvature: Implications for sediment transport processes","volume":"121","author":"Clubb","year":"2016","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1029\/2019JF005025","article-title":"Clustering River Profiles to Classify Geomorphic Domains","volume":"124","author":"Clubb","year":"2019","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1029\/2018JF004827","article-title":"A Network-Based Flow Accumulation Algorithm for Point Clouds: Facet-Flow Networks (FFNs)","volume":"124","author":"Rheinwalt","year":"2019","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"706","DOI":"10.1002\/esp.5263","article-title":"Evaluation of high-resolution DEMs from satellite imagery for geomorphic applications: A case study using the SETSM algorithm","volume":"47","author":"Atwood","year":"2022","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1080\/15481603.2015.1008621","article-title":"Automated stereo-photogrammetric DEM generation at high latitudes: Surface Extraction with TIN-based Search-space Minimization (SETSM) validation and demonstration over glaciated regions","volume":"52","author":"Noh","year":"2015","journal-title":"GISci. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1038\/ngeo2999","article-title":"A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016","volume":"10","author":"Brun","year":"2017","journal-title":"Nat. Geosci."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Facciolo, G., De Franchis, C., and Meinhardt-Llopis, E. (2017, January 21\u201326). Automatic 3D Reconstruction from Multi-date Satellite Images. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, HI, USA.","DOI":"10.1109\/CVPRW.2017.198"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Aati, S., and Avouac, J.P. (2020). Optimization of Optical Image Geometric Modeling, Application to Topography Extraction and Topographic Change Measurements Using PlanetScope and SkySat Imagery. Remote Sens., 12.","DOI":"10.3390\/rs12203418"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Lastilla, L., Belloni, V., Ravanelli, R., and Crespi, M. (2021). DSM Generation from Single and Cross-Sensor Multi-View Satellite Images Using the New Agisoft Metashape: The Case Studies of Trento and Matera (Italy). Remote Sens., 13.","DOI":"10.3390\/rs13040593"},{"key":"ref_62","unstructured":"Agisoft (2022, September 28). Agisoft Metashape Professional. Available online: https:\/\/www.geoscan.aero\/en\/software\/agisoft\/metashape_pro."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/85\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:49:49Z","timestamp":1760147389000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/85"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,23]]},"references-count":62,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15010085"],"URL":"https:\/\/doi.org\/10.3390\/rs15010085","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,12,23]]}}}