{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T12:04:35Z","timestamp":1771675475012,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,11,27]],"date-time":"2021-11-27T00:00:00Z","timestamp":1637971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Lately, affordable unmanned aerial vehicle (UAV)-lidar systems have started to appear on the market, highlighting the need for methods facilitating proper verification of their accuracy. However, the dense point cloud produced by such systems makes the identification of individual points that could be used as reference points difficult. In this paper, we propose such a method utilizing accurately georeferenced targets covered with high-reflectivity foil, which can be easily extracted from the cloud; their centers can be determined and used for the calculation of the systematic shift of the lidar point cloud. Subsequently, the lidar point cloud is cleaned of such systematic shift and compared with a dense SfM point cloud, thus yielding the residual accuracy. We successfully applied this method to the evaluation of an affordable DJI ZENMUSE L1 scanner mounted on the UAV DJI Matrice 300 and found that the accuracies of this system (3.5 cm in all directions after removal of the global georeferencing error) are better than manufacturer-declared values (10\/5 cm horizontal\/vertical). However, evaluation of the color information revealed a relatively high (approx. 0.2 m) systematic shift.<\/jats:p>","DOI":"10.3390\/rs13234811","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T01:45:02Z","timestamp":1638323102000},"page":"4811","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":85,"title":["A New Method for UAV Lidar Precision Testing Used for the Evaluation of an Affordable DJI ZENMUSE L1 Scanner"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0070-7172","authenticated-orcid":false,"given":"Martin","family":"\u0160troner","sequence":"first","affiliation":[{"name":"Department of Special Geodesy, Faculty of Civil Engineering, Czech Technical University in Prague, Th\u00e1kurova 7, 166 29 Prague, Czech Republic"}]},{"given":"Rudolf","family":"Urban","sequence":"additional","affiliation":[{"name":"Department of Special Geodesy, Faculty of Civil Engineering, Czech Technical University in Prague, Th\u00e1kurova 7, 166 29 Prague, Czech Republic"}]},{"given":"Lenka","family":"L\u00ednkov\u00e1","sequence":"additional","affiliation":[{"name":"Department of Special Geodesy, Faculty of Civil Engineering, Czech Technical University in Prague, Th\u00e1kurova 7, 166 29 Prague, Czech Republic"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"361","DOI":"10.46544\/AMS.v25i3.9","article-title":"The use of onboard UAV GNSS navigation data for area and volume calculation","volume":"25","author":"Urban","year":"2020","journal-title":"Acta Montan. Slovaca"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kovani\u010d, \u013d., Blistan, P., \u0160troner, M., Urban, R., and Blistanova, M. (2021). Suitability of Aerial Photogrammetry for Dump Documentation and Volume Determination in Large Areas. Appl. Sci., 11.","DOI":"10.3390\/app11146564"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Park, S., and Choi, Y. (2020). Applications of Unmanned Aerial Vehicles in Mining from Exploration to Reclamation: A Review. Minerals, 10.","DOI":"10.3390\/min10080663"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Klou\u010dek, T., Kom\u00e1rek, J., Surov\u00fd, P., Hrach, K., Janata, P., and Va\u0161\u00ed\u010dek, B. (2019). The Use of UAV Mounted Sensors for Precise Detection of Bark Beetle Infestation. Remote Sens., 11.","DOI":"10.3390\/rs11131561"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1080\/2150704X.2019.1649735","article-title":"Evaluation of a high resolution UAV imagery model for rooftop solar irradiation estimates","volume":"10","author":"Lagner","year":"2019","journal-title":"Remote Sens. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kovani\u010d, \u013d., Blistan, P., Urban, R., \u0160troner, M., Bli\u0161\u0165anov\u00e1, M., Barto\u0161, K., and Pukansk\u00e1, K. (2020). Analysis of the Suitability of High-Resolution DEM Obtained Using ALS and UAS (SfM) for the Identification of Changes and Monitoring the Development of Selected Geohazards in the Alpine Environment\u2014A Case Study in High Tatras, Slovakia. Remote Sens., 12.","DOI":"10.3390\/rs12233901"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Jaud, M., Bertin, S., Beauverger, M., Augereau, E., and Delacourt, C. (2020). RTK GNSS-Assisted Terrestrial SfM Photogrammetry without GCP: Application to Coastal Morphodynamics Monitoring. Remote Sens., 12.","DOI":"10.3390\/rs12111889"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"\u017dabota, B., and Kobal, M. (2021). Accuracy Assessment of UAV-Photogrammetric-Derived Products Using PPK and GCPs in Challenging Terrains: In Search of Optimized Rockfall Mapping. Remote Sens., 13.","DOI":"10.3390\/rs13193812"},{"key":"ref_9","first-page":"727","article-title":"Uav Photogrammetry and Vhr Satellite Imagery for Emergency Mapping. The October 2020 Flood in Limone Piemonte (Italy)","volume":"XLIII-B3-2","author":"Chiabrando","year":"2021","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"\u0160troner, M., Urban, R., Seidl, J., Reindl, T., and Brou\u010dek, J. (2021). Photogrammetry Using UAV-Mounted GNSS RTK: Georeferencing Strategies without GCPs. Remote Sens., 13.","DOI":"10.3390\/rs13071336"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Vacca, G., Dess\u00ec, A., and Sacco, A. (2017). The Use of Nadir and Oblique UAV Images for Building Knowledge. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6120393"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Los\u00e8, L.T., Chiabrando, F., and Tonolo, F.G. (2020). Boosting the Timeliness of UAV Large Scale Mapping. Direct Georeferencing Approaches: Operational Strategies and Best Practices. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9100578"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sanz-Ablanedo, E., Chandler, J.H., Rodr\u00edguez-P\u00e9rez, J.R., and Ord\u00f3\u00f1ez, C. (2018). Accuracy of Unmanned Aerial Vehicle (UAV) and SfM Photogrammetry Survey as a Function of the Number and Location of Ground Control Points Used. Remote Sens., 10.","DOI":"10.3390\/rs10101606"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"McMahon, C., Mora, O., and Starek, M. (2021). Evaluating the Performance of sUAS Photogrammetry with PPK Positioning for Infrastructure Mapping. Drones, 5.","DOI":"10.3390\/drones5020050"},{"key":"ref_15","first-page":"130","article-title":"Comparison of four UAV georeferencing methods for environmental monitoring purposes focusing on the combined use with airborne and satellite remote sensing platforms","volume":"75","author":"Planas","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geo-Inf."},{"key":"ref_16","first-page":"133","article-title":"The combination of laser scanning and structure from motion technology for creation of accurate exterior and interior orthophotos of St. Nicholas Baroque church","volume":"XL-5\/W1","author":"Koska","year":"2013","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_17","unstructured":"K\u0159emen, T. (2020). Advances and Trends in Geodesy, Cartography and Geoinformatics II. Advances and Trends in Geodesy, Cartography and Geoinformatics II, CRC Press."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Blistan, P., Jacko, S., Kovani\u010d, \u013d., Kondela, J., Pukansk\u00e1, K., and Barto\u0161, K. (2020). TLS and SfM Approach for Bulk Density Determination of Excavated Heterogeneous Raw Materials. Minerals, 10.","DOI":"10.3390\/min10020174"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Pukansk\u00e1, K., Barto\u0161, K., Bella, P., Ga\u0161inec, J., Blistan, P., and Kovani\u010d, \u013d. (2020). Surveying and High-Resolution Topography of the Ochtin\u00e1 Aragonite Cave Based on TLS and Digital Photogrammetry. Appl. Sci., 10.","DOI":"10.3390\/app10134633"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Mandlburger, G., Pfennigbauer, M., Schwarz, R., Fl\u00f6ry, S., and Nussbaumer, L. (2020). Concept and Performance Evaluation of a Novel UAV-Borne Topo-Bathymetric LiDAR Sensor. Remote Sens., 12.","DOI":"10.3390\/rs12060986"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Jakovljevic, G., Govedarica, M., Alvarez-Taboada, F., and Pajic, V. (2019). Accuracy Assessment of Deep Learning Based Classification of LiDAR and UAV Points Clouds for DTM Creation and Flood Risk Mapping. Geosciences, 9.","DOI":"10.3390\/geosciences9070323"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Balsi, M., Esposito, S., Fallavollita, P., Melis, M.G., and Milanese, M. (2021). Preliminary Archeological Site Survey by UAV-Borne Lidar: A Case Study. Remote Sens., 13.","DOI":"10.3390\/rs13030332"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lin, Y.-C., Cheng, Y.-T., Zhou, T., Ravi, R., Hasheminasab, S.M., Flatt, J.E., Troy, C., and Habib, A. (2019). Evaluation of UAV LiDAR for Mapping Coastal Environments. Remote Sens., 11.","DOI":"10.3390\/rs11242893"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"589","DOI":"10.5194\/isprs-archives-XLII-2-W13-589-2019","article-title":"Comparison of UAV lidar and imagery for beach monitoring","volume":"XLII-2\/W13","author":"Shaw","year":"2019","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zimmerman, T., Jansen, K., and Miller, J. (2020). Analysis of UAS Flight Altitude and Ground Control Point Parameters on DEM Accuracy along a Complex, Developed Coastline. Remote Sens., 12.","DOI":"10.3390\/rs12142305"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Feroz, S., and Abu Dabous, S. (2021). UAV-Based Remote Sensing Applications for Bridge Condition Assessment. Remote Sens., 13.","DOI":"10.3390\/rs13091809"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1007\/s40789-019-00264-5","article-title":"A review of UAV monitoring in mining areas: Current status and future perspectives","volume":"6","author":"Ren","year":"2019","journal-title":"Int. J. Coal Sci. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Tan, J., Zhao, H., Yang, R., Liu, H., Li, S., and Liu, J. (2021). An Entropy-Weighting Method for Efficient Power-Line Feature Evaluation and Extraction from LiDAR Point Clouds. Remote Sens., 13.","DOI":"10.3390\/rs13173446"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1007\/s12517-021-06947-1","article-title":"Automatic detection of power transmission lines and risky object locations using UAV LiDAR data","volume":"14","author":"Dihkan","year":"2021","journal-title":"Arab. J. Geosci."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Salach, A., Baku\u0142a, K., Pilarska, M., Ostrowski, W., G\u00f3rski, K., and Kurczy\u0144ski, Z. (2018). Accuracy Assessment of Point Clouds from LiDAR and Dense Image Matching Acquired Using the UAV Platform for DTM Creation. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7090342"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Gomes Pereira, L., Fernandez, P., Mourato, S., Matos, J., Mayer, C., and Marques, F. (2021). Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study. Remote Sens., 13.","DOI":"10.3390\/rs13030419"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Chen, J., Zhang, Z., Zhang, K., Wang, S., and Han, Y. (2020). UAV-Borne LiDAR Crop Point Cloud Enhancement Using Grasshopper Optimization and Point Cloud Up-Sampling Network. Remote Sens., 12.","DOI":"10.3390\/rs12193208"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Torresan, C., Berton, A., Carotenuto, F., Chiavetta, U., Miglietta, F., Zaldei, A., and Gioli, B. (2018). Development and Performance Assessment of a Low-Cost UAV Laser Scanner System (LasUAV). Remote Sens., 10.","DOI":"10.3390\/rs10071094"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Hu, T., Sun, X., Su, Y., Guan, H., Sun, Q., Kelly, M., and Guo, Q. (2020). Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications. Remote Sens., 13.","DOI":"10.3390\/rs13010077"},{"key":"ref_35","first-page":"119","article-title":"Autonomous airship equipped by multi-sensor mapping platform","volume":"XL-5\/W1","author":"Jon","year":"2013","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"012100","DOI":"10.1088\/1755-1315\/169\/1\/012100","article-title":"Accuracy evaluation of digital terrain model based on different flying altitudes and conditional of terrain using UAV LiDAR technology","volume":"169","author":"Fuad","year":"2018","journal-title":"IOP Conf. Series Earth Environ. Sci."},{"key":"ref_37","first-page":"89","article-title":"Comparison of Airborne Laser Scanning of Low and High Above Ground Level for Selected Infrastructure Objects","volume":"8","author":"Siwiec","year":"2018","journal-title":"J. Appl. Eng. Sci."},{"key":"ref_38","first-page":"87","article-title":"The potential of light laser scanners developed for unmanned aerial vehicles\u2014The review and accuracy","volume":"XLII-2\/W2","author":"Pilarska","year":"2016","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/23\/4811\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:36:36Z","timestamp":1760168196000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/23\/4811"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,27]]},"references-count":38,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["rs13234811"],"URL":"https:\/\/doi.org\/10.3390\/rs13234811","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,27]]}}}