{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T14:09:17Z","timestamp":1783433357647,"version":"3.54.6"},"reference-count":45,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T00:00:00Z","timestamp":1693440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41877004"],"award-info":[{"award-number":["41877004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42371060"],"award-info":[{"award-number":["42371060"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42275028"],"award-info":[{"award-number":["42275028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22KJB170016"],"award-info":[{"award-number":["22KJB170016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions of China","award":["41877004"],"award-info":[{"award-number":["41877004"]}]},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions of China","award":["42371060"],"award-info":[{"award-number":["42371060"]}]},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions of China","award":["42275028"],"award-info":[{"award-number":["42275028"]}]},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions of China","award":["22KJB170016"],"award-info":[{"award-number":["22KJB170016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>UAV-SfM photogrammetry is widely used in remote sensing and geoscience communities. Scholars have tried to optimize UAV-SfM for terrain modeling based on analysis of error statistics like root mean squared error (RMSE), mean error (ME), and standard deviation (STD). However, the errors of terrain modeling tend to be spatially distributed. Although the error statistic can represent the magnitude of errors, revealing spatial structures of errors is still challenging. The \u201cbest practice\u201d of UAV-SfM is lacking in research communities from the perspective of spatial structure of errors. Thus, this study designed various UAV-SfM photogrammetric scenarios and investigated the effects of image collection strategies and GCPs on terrain modeling. The error maps of different photogrammetric scenarios were calculated and quantitatively analyzed by ME, STD, and Moran\u2019s I. The results show that: (1) A high camera inclination (20\u201340\u00b0) enhances UAV-SfM photogrammetry. This not only decreases the magnitude of errors, but also mitigates its spatial correlation (Moran\u2019s I). Supplementing convergent images is valuable for reducing errors in a nadir camera block, but it is unnecessary when the image block is with a high camera angle. (2) Flying height increases the magnitude of errors (ME and STD) but does not affect the spatial structure (Moran\u2019s I). By contrast, the camera angle is more important than the flying height for improving the spatial structure of errors. (3) A small number of GCPs rapidly reduce the magnitude of errors (ME and STD), and a further increase in GCPs has a marginal effect. However, the structure of errors (Moran\u2019s I) can be further improved with increasing GCPs. (4) With the same number, the distribution of GCPs is critical for UAV-SfM photogrammetry. The edge distribution should be first considered, followed by the even distribution. The research findings contribute to understanding how different image collection scenarios and GCPs can influence subsequent terrain modeling accuracy, precision, and spatial structure of errors. The latter (spatial structure of errors) should be routinely assessed in evaluations of the quality of UAV-SfM photogrammetry.<\/jats:p>","DOI":"10.3390\/rs15174305","type":"journal-article","created":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T08:45:31Z","timestamp":1693557931000},"page":"4305","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Enhancing UAV-SfM Photogrammetry for Terrain Modeling from the Perspective of Spatial Structure of Errors"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7424-644X","authenticated-orcid":false,"given":"Wen","family":"Dai","sequence":"first","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 211800, China"},{"name":"Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruibo","family":"Qiu","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2989-8865","authenticated-orcid":false,"given":"Bo","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wangda","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9554-5462","authenticated-orcid":false,"given":"Guanghui","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Solomon Obiri Yeboah","family":"Amankwah","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8613-0003","authenticated-orcid":false,"given":"Guojie","family":"Wang","sequence":"additional","affiliation":[{"name":"Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland"},{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103962","DOI":"10.1016\/j.dib.2019.103962","article-title":"Unmanned aerial image dataset: Ready for 3D reconstruction","volume":"25","author":"Shahbazi","year":"2019","journal-title":"Data Brief"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.3390\/f5061212","article-title":"Estimating Soil Displacement from Timber Extraction Trails in Steep Terrain: Application of an Unmanned Aircraft for 3D 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