{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T04:14:15Z","timestamp":1768450455114,"version":"3.49.0"},"reference-count":61,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,25]],"date-time":"2022-06-25T00:00:00Z","timestamp":1656115200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hanna Bremer Award for young female physical geographers of the Hanna Bremer Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Detection of geomorphological changes based on structure from motion (SfM) photogrammetry is highly dependent on the quality of the 3D reconstruction from high-quality images and the correspondingly derived point precision estimates. For long-term monitoring, it is interesting to know if the resulting 3D point clouds and derived detectable changes over the years are comparable, even though different sensors and data collection methods were applied. Analyzing this, we took images of a sinkhole terrestrially with a Nikon D3000 and aerially with a DJI drone camera in 2017, 2018, and 2019 and computed 3D point clouds and precision maps using Agisoft PhotoScan and the SfM_Georef software. Applying the \u201cmultiscale model to model cloud comparison using precision maps\u201d plugin (M3C2-PM) in CloudCompare, we analyzed the differences between the point clouds arising from the different sensors and data collection methods per year. Additionally, we were interested if the patterns of detectable change over the years were comparable between the data collection methods. Overall, we found that the spatial pattern of detectable changes of the sinkhole walls were generally similar between the aerial and terrestrial surveys, which were performed using different sensors and camera locations. Although the terrestrial data collection was easier to perform, there were often challenges due to terrain and vegetation around the sinkhole to safely acquire adequate viewing angles to cover the entire sinkhole, which the aerial survey was able to overcome. The local levels of detection were also considerably lower for point clouds resulting from aerial surveys, likely due to the ability to obtain closer-range imagery within the sinkhole.<\/jats:p>","DOI":"10.3390\/rs14133058","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T22:50:23Z","timestamp":1656283823000},"page":"3058","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Terrestrial and Airborne Structure from Motion Photogrammetry Applied for Change Detection within a Sinkhole in Thuringia, Germany"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9712-4859","authenticated-orcid":false,"given":"Helene","family":"Petschko","sequence":"first","affiliation":[{"name":"Department of Geography, Friedrich Schiller University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"given":"Markus","family":"Zehner","sequence":"additional","affiliation":[{"name":"Department of Geography, Friedrich Schiller University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"given":"Patrick","family":"Fischer","sequence":"additional","affiliation":[{"name":"Department of Geography, Friedrich Schiller University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1617-8308","authenticated-orcid":false,"given":"Jason","family":"Goetz","sequence":"additional","affiliation":[{"name":"Department of Geography, Friedrich Schiller University Jena, Loebdergraben 32, 07743 Jena, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1177\/0309133315615805","article-title":"Structure from Motion Photogrammetry in Physical Geography","volume":"40","author":"Smith","year":"2016","journal-title":"Prog. Phys. Geogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.geomorph.2014.01.006","article-title":"Modeling the Topography of Shallow Braided Rivers Using Structure-from-Motion Photogrammetry","volume":"213","author":"Javernick","year":"2014","journal-title":"Geomorphology"},{"key":"ref_3","unstructured":"Clarke, L.E., and Nield, J.M. (2015). Structure from Motion (SfM) Photogrammetry. Geomorphological Techniques, British Society for Geomorphology."},{"key":"ref_4","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_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/B978-0-444-64177-9.00001-1","article-title":"Structure from Motion Photogrammetric Technique","volume":"Volume 23","author":"Tarolli","year":"2020","journal-title":"Remote Sensing of Geomorphology"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Mar\u00edn-Buz\u00f3n, C., P\u00e9rez-Romero, A.M., Le\u00f3n-Bonillo, M.J., Mart\u00ednez-\u00c1lvarez, R., Mej\u00edas-Garc\u00eda, J.C., and Manzano-Agugliaro, F. (2021). Photogrammetry (SfM) vs. Terrestrial Laser Scanning (TLS) for Archaeological Excavations: Mosaic of Cantillana (Spain) as a Case Study. Appl. Sci., 11.","DOI":"10.3390\/app112411994"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1002\/esp.3366","article-title":"Topographic Structure from Motion: A New Development in Photogrammetric Measurement: Topographic Structure from Motion","volume":"38","author":"Fonstad","year":"2013","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.cageo.2011.09.012","article-title":"Multiview 3D Reconstruction in Geosciences","volume":"44","author":"Favalli","year":"2012","journal-title":"Comput. Geosci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1098\/rspb.1979.0006","article-title":"The Interpretation of Structure from Motion","volume":"203","author":"Ullman","year":"1979","journal-title":"Proc. R. Soc. Lond. Ser. B"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.geomorph.2012.08.021","article-title":"\u2018Structure-from-Motion\u2019 Photogrammetry: A Low-Cost, Effective Tool for Geoscience Applications","volume":"179","author":"Westoby","year":"2012","journal-title":"Geomorphology"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.geomorph.2016.06.027","article-title":"Erosion Processes in Calanchi in the Upper Orcia Valley, Southern Tuscany, Italy Based on Multitemporal High-Resolution Terrestrial LiDAR and UAV Surveys","volume":"269","author":"Neugirg","year":"2016","journal-title":"Geomorphology"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.geomorph.2016.11.009","article-title":"An Evaluation of the Effectiveness of Low-Cost UAVs and Structure from Motion for Geomorphic Change Detection","volume":"278","author":"Cook","year":"2017","journal-title":"Geomorphology"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1029\/2009WR008812","article-title":"Testing Space-Scale Methodologies for Automatic Geomorphic Feature Extraction from Lidar in a Complex Mountainous Landscape: Testing feature extraction methodologies","volume":"46","author":"Passalacqua","year":"2010","journal-title":"Water Resour. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1002\/esp.3648","article-title":"Investigating the Geomorphological Potential of Freely Available and Accessible Structure-from-Motion Photogrammetry Using a Smartphone: Digital terrain models using structure-from-motion and a smartphone","volume":"40","author":"Micheletti","year":"2015","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"107318","DOI":"10.1016\/j.geomorph.2020.107318","article-title":"Terrestrial SfM-MVS Photogrammetry from Smartphone Sensors","volume":"367","author":"Tavani","year":"2020","journal-title":"Geomorphology"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"110598","DOI":"10.1016\/j.measurement.2021.110598","article-title":"Assessment of the Trueness and Precision of Smartphone Photogrammetry for Rock Joint Roughness Measurement","volume":"188","author":"An","year":"2022","journal-title":"Measurement"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"F3","DOI":"10.1029\/2011JF002289","article-title":"Straightforward Reconstruction of 3D Surfaces and Topography with a Camera: Accuracy and Geoscience Application","volume":"117","author":"James","year":"2012","journal-title":"J. Geophys. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.geomorph.2010.10.039","article-title":"Geomorphic Change Detection Using Historic Maps and DEM Differencing: The Temporal Dimension of Geospatial Analysis","volume":"137","author":"James","year":"2012","journal-title":"Geomorphology"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.jvolgeores.2015.09.004","article-title":"Examining Rhyolite Lava Flow Dynamics through Photo-Based 3D Reconstructions of the 2011\u20132012 Lava Flowfield at Cord\u00f3n-Caulle, Chile","volume":"304","author":"Farquharson","year":"2015","journal-title":"J. Volcanol. Geotherm. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.jsg.2014.10.007","article-title":"Ground-Based and UAV-Based Photogrammetry: A Multiscale, High-Resolution Mapping Tool for Structural Geology and Paleoseismology","volume":"69","author":"Bemis","year":"2014","journal-title":"J. Struct. Geol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1656","DOI":"10.1002\/esp.3747","article-title":"From Experimental Plots to Experimental Landscapes: Topography, Erosion and Deposition in Sub-humid Badlands from Structure-from-Motion Photogrammetry","volume":"40","author":"Smith","year":"2015","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1736","DOI":"10.3390\/rs70201736","article-title":"Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)","volume":"7","author":"Turner","year":"2015","journal-title":"Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1274","DOI":"10.1002\/esp.4085","article-title":"Archival Photogrammetric Analysis of River-Floodplain Systems Using Structure from Motion (SfM) Methods: Archival Photogrammetric Analysis of River Systems Using SfM Methods","volume":"42","author":"Bakker","year":"2017","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"425","DOI":"10.5194\/esurf-4-425-2016","article-title":"Suitability of Ground-Based SfM\u2013MVS for Monitoring Glacial and Periglacial Processes","volume":"4","author":"Piermattei","year":"2016","journal-title":"Earth Surf. Dyn."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1111\/phor.12218","article-title":"Multitemporal Monitoring of a Coastal Landslide through SfM-Derived Point Cloud Comparison","volume":"32","author":"Esposito","year":"2017","journal-title":"Photogramm. Rec."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"827","DOI":"10.5194\/tc-11-827-2017","article-title":"Terrain Changes from Images Acquired on Opportunistic Flights by SfM Photogrammetry","volume":"11","author":"Girod","year":"2017","journal-title":"Cryosphere"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.rse.2018.03.013","article-title":"Modeling the Precision of Structure-from-Motion Multi-View Stereo Digital Elevation Models from Repeated Close-Range Aerial Surveys","volume":"210","author":"Goetz","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1002\/esp.4502","article-title":"Automated Co-Registration and Calibration in SfM Photogrammetry for Landslide Change Detection: Automated SfM Co-Registration for Landslide Change Detection","volume":"44","author":"Peppa","year":"2019","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Nesbit, P., and Hugenholtz, C. (2019). Enhancing UAV\u2013SfM 3D Model Accuracy in High-Relief Landscapes by Incorporating Oblique Images. Remote Sens., 11.","DOI":"10.3390\/rs11030239"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1139\/juvs-2019-0006","article-title":"Evaluation of SfM for Surface Characterization of a Snow-Covered Glacier through Comparison with Aerial Lidar","volume":"8","author":"Bash","year":"2020","journal-title":"J. Unmanned Veh. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3293","DOI":"10.1002\/esp.4965","article-title":"Optimization of UAVs-SfM Data Collection in Aeolian Landform Morphodynamics: A Case Study from the Gonghe Basin, China","volume":"45","author":"Luo","year":"2020","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"e2020JF006053","DOI":"10.1029\/2020JF006053","article-title":"Movement of Sediment Through a Burned Landscape: Sediment Volume Observations and Model Comparisons in the San Gabriel Mountains, California, USA","volume":"126","author":"Rengers","year":"2021","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1111\/phor.12219","article-title":"Application of Photogrammetry for Mapping of Solution Collapse Breccia Pipes on the Colorado Plateau, USA","volume":"32","author":"Klawitter","year":"2017","journal-title":"Photogramm. Rec."},{"key":"ref_34","unstructured":"(2019, August 05). CloudCompare [GPL Software]. CloudCompare, (Version 2.10). Available online: http:\/\/www.cloudcompare.org\/."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.isprsjprs.2013.04.009","article-title":"Accurate 3D Comparison of Complex Topography with Terrestrial Laser Scanner: Application to the Rangitikei Canyon (N-Z)","volume":"82","author":"Lague","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Nourbakhshbeidokhti, S., Kinoshita, A., Chin, A., and Florsheim, J. (2019). A Workflow to Estimate Topographic and Volumetric Changes and Errors in Channel Sedimentation after Disturbance. Remote Sens., 11.","DOI":"10.3390\/rs11050586"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1016\/j.isprsjprs.2021.11.018","article-title":"Correspondence-Driven Plane-Based M3C2 for Lower Uncertainty in 3D Topographic Change Quantification","volume":"183","author":"Zahs","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1002\/esp.4125","article-title":"3-D Uncertainty-Based Topographic Change Detection with Structure-from-Motion Photogrammetry: Precision Maps for Ground Control and Directly Georeferenced Surveys","volume":"42","author":"James","year":"2017","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2081","DOI":"10.1002\/esp.4637","article-title":"Guidelines on the Use of Structure-from-motion Photogrammetry in Geomorphic Research","volume":"44","author":"James","year":"2019","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.geomorph.2015.05.011","article-title":"Reproducibility of UAV-Based Earth Topography Reconstructions Based on Structure-from-Motion Algorithms","volume":"260","author":"Clapuyt","year":"2016","journal-title":"Geomorphology"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"De Marco, J., Maset, E., Cucchiaro, S., Beinat, A., and Cazorzi, F. (2021). Assessing Repeatability and Reproducibility of Structure-from-Motion Photogrammetry for 3D Terrain Mapping of Riverbeds. Remote Sens., 13.","DOI":"10.3390\/rs13132572"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Niederheiser, R., Mokro\u0161, M., Lange, J., Petschko, H., Prasicek, G., and Oude Elberink, S. (2016, January 12\u201319). Deriving 3D Point Clouds from Terrestrial Photographs\u2014Comparison of Different Sensors and Software. Proceedings of the ISPRS Archives, Prague, Czech Republic.","DOI":"10.5194\/isprsarchives-XLI-B5-685-2016"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1002\/uog.5256","article-title":"Reliability, Repeatability and Reproducibility: Analysis of Measurement Errors in Continuous Variables","volume":"31","author":"Bartlett","year":"2008","journal-title":"Ultrasound Obstet. Gynecol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Mikita, T., Janata, P., and Surov\u00fd, P. (2016). Forest Stand Inventory Based on Combined Aerial and Terrestrial Close-Range Photogrammetry. Forests, 7.","DOI":"10.3390\/f7080165"},{"key":"ref_45","unstructured":"Bauriegl, A., Biewald, W., B\u00fcchner, K.H., Deicke, M., Herold, U., Kind, B., Rindfleisch, K., Schmidt, S., Schulz, G., and Schulze, S. (2004). Subrosion und Baugrund in Th\u00fcringen, Th\u00fcringer Landesanstalt f\u00fcr Umwelt und Geologie. Schriftenreihe der Th\u00fcringer Landesanstalt f\u00fcr Umwelt und Geologie."},{"key":"ref_46","unstructured":"Mikos, M., Tiwari, B., Yin, Y., and Sassa, K. (2017). Erosion Processes and Mass Movements in Sinkholes Assessed by Terrestrial Structure from Motion Photogrammetry. WLF: Workshop on World Landslide Forum, Proceedings of the Advancing Culture of Living with Landslides, Ljubljana, Slovenia, 29 May\u20132 June 2017, Springer International Publishing."},{"key":"ref_47","unstructured":"Petschko, H., Goetz, J., and Zehner, M. (2022). Terrestrial and Aerial Photos, GCPs and Derived Point Clouds of a Sinkhole in Northern Thuringia [Data set]. Zenodo."},{"key":"ref_48","first-page":"113","article-title":"Neuer Erdfall bei Bad Frankenhausen","volume":"56","author":"Brust","year":"2010","journal-title":"Mitt. Verb. Dtsch. H\u00f6hlen-Karstforscher EV"},{"key":"ref_49","unstructured":"(2022). Annual Observations of Precipitation in Mm\u2014Station Artern, DWD Climate Data Center (CDC)."},{"key":"ref_50","unstructured":"Waltham, T., Bell, F.G., and Culshaw, M. (2005). Sinkholes and Subsidence: Karst and Cavernous Rocks in Engineering and Construction, Springer."},{"key":"ref_51","unstructured":"Agisoft LLC (2016). Agisoft PhotoScan User Manual Professional Edition, Version 1.2, Frontiers Media SA."},{"key":"ref_52","first-page":"9","article-title":"Case Report: Optimization of Topographic Change Detection with UAV Structure-from-Motion Photogrammetry Through Survey Co-Alignment","volume":"2","author":"Nijland","year":"2021","journal-title":"Front. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"7772","DOI":"10.1029\/2019WR025251","article-title":"Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area","volume":"55","author":"Goetz","year":"2019","journal-title":"Water Resour. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1080\/2150704X.2018.1519641","article-title":"The Reproducibility of SfM Algorithms to Produce Detailed Digital Surface Models: The Example of PhotoScan Applied to a High-Alpine Rock Glacier","volume":"10","author":"Hendrickx","year":"2019","journal-title":"Remote Sens. Lett."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1007\/s11263-006-9967-1","article-title":"Evaluation of Features Detectors and Descriptors Based on 3D Objects","volume":"73","author":"Moreels","year":"2007","journal-title":"Int. J. Comput. Vis."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1413","DOI":"10.1002\/esp.3609","article-title":"Mitigating Systematic Error in Topographic Models Derived from UAV and Ground-Based Image Networks","volume":"39","author":"James","year":"2014","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Lin, J., Wang, R., Li, L., and Xiao, Z. (2019, January 5\u20137). A Workflow of SfM-Based Digital Outcrop Reconstruction Using Agisoft PhotoScan. Proceedings of the 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC), IEEE, Xiamen, China.","DOI":"10.1109\/ICIVC47709.2019.8980982"},{"key":"ref_58","unstructured":"Feurer, D., and Vinatier, F. (2018). The Time-SIFT Method: Detecting 3-D Changes from Archival Photogrammetric Analysis with Almost Exclusively Image Information. arXiv."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive Image Features from Scale-Invariant Keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.isprsjprs.2012.01.006","article-title":"3D Terrestrial Lidar Data Classification of Complex Natural Scenes Using a Multiscale Dimensionality Criterion: Applications in Geomorphology","volume":"68","author":"Brodu","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., and Yan, G. (2016). An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sens., 8.","DOI":"10.3390\/rs8060501"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3058\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:38:25Z","timestamp":1760139505000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3058"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,25]]},"references-count":61,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133058"],"URL":"https:\/\/doi.org\/10.3390\/rs14133058","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,25]]}}}