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The quality of elevation models derived from UAV measurements varies depending on many variables (e.g. UAV equipment used, terrain conditions, etc.). In order to improve the quality of digital models based on UAV image data, additional GNSS-RTK measurements are usually made at ground control points. The aim of this article is to evaluate the mathematical accuracy of terrain models created without ground control points. The accuracy of the models is considered in two directions: vertical and horizontal. Vertical (elevation) accuracy is calculated based on airborne laser scanning (ALS) data and horizontal (location) accuracy is calculated through comparison with high-resolution orthophotomaps. The average elevation accuracy of all created UAV-based DEMs is found to be 2.7\u20132.8\u00a0m (MAE), 3.1\u20133.3\u00a0m (RMSE), and the average horizontal accuracy is 2.1\u00a0m. Despite the low accuracy of the UAV models, the topography is reflected very well in the spatial images. This may be related to the regular and symmetrical distribution of height errors. To improve the accuracy parameters of UAV-based DEMs, it is proposed that they be rapidly georeferenced based on orthophotomaps.\n<\/jats:p>","DOI":"10.1007\/s10707-023-00498-1","type":"journal-article","created":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T07:04:41Z","timestamp":1681196681000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Accuracy of UAV-based DEMs without ground control points"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1466-0128","authenticated-orcid":false,"given":"Bart\u0142omiej","family":"Szypu\u0142a","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,11]]},"reference":[{"key":"498_CR1","doi-asserted-by":"publisher","first-page":"7538","DOI":"10.1080\/01431161.2019.1591651","volume":"40","author":"D Fawcett","year":"2019","unstructured":"Fawcett D, Azlan B, Hill TC, Kho LK, Bennie J, Anderson K (2019) Unmanned aerial vehicle (UAV) derived structure-from-motion photogrammetry point clouds for oil palm (Elaeis guineensis) canopy segmentation and height estimation. 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