2,294
Views
4
CrossRef citations to date
0
Altmetric
Research Article

UAV DTM acquisition in a forested area – comparison of low-cost photogrammetry (DJI Zenmuse P1) and LiDAR solutions (DJI Zenmuse L1)

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Article: 2179942 | Received 24 Aug 2022, Accepted 09 Feb 2023, Published online: 01 Mar 2023

References

  • Aguilar, F. J., Rivas, J. R., Nemmaoui, A., Peñalver, A., & Aguilar, M. A. (2019). UAV-based digital terrain model generation under leaf-off conditions to support teak plantations inventories in tropical dry forests. A case of the coastal region of ecuador. Sensors, 19(8), 1934. https://doi.org/10.3390/s19081934
  • Almeida, A., Gonçalves, F., Silva, G., Souza, R., Treuhaft, R., Santos, W., Loureiro, D., & Fernandes, M. (2020). Estimating structure and biomass of a secondary Atlantic forest in Brazil using Fourier transforms of vertical profiles derived from UAV photogrammetry point clouds. Remote Sensing, 12(12), 3560. https://doi.org/10.3390/rs12213560
  • Balsi, M., Esposito, S., Fallavollita, P., & Nardinocchi, C. (2018). Single-tree detection in high-density LiDAR data from UAV-based survey. European Journal of Remote Sensing, 51(1), 679–20. https://doi.org/10.1080/22797254.2018.1474722
  • Birdal, A. C., Avdan, U., & Türk, T. (2017). Estimating tree heights with images from an unmanned aerial vehicle. Geomatics, Natural Hazards and Risk, 8(2), 1144–1156. https://doi.org/10.1080/19475705.2017.1300608
  • Braun, J., Braunová, H., Suk, T., Michal, O., Pěťovský, P., & Kurič, I. (2021). Structural and geometrical vegetation filtering-case study on mining area point cloud acquired by UAV LiDAR. Acta Montanistica Slovaca, 26(4), 661–674. ISSN 1335-1788. https://doi.org/10.46544/AMS.v26i4.06
  • Brodu, N., & Lague, D. (2012). 3D terrestrial LiDAR data classification of complex natural scenes using a multi-scale dimensionality criterion: Applications in geomorphology. Isprs Journal of Photogrammetry and Remote Sensing, 68, 121–134. 2012. https://doi.org/10.1016/j.isprsjprs.2012.01.006
  • Emtehani, S., Jetten, V., van Westen, C., & Shrestha, D. P. Quantifying Sediment Deposition Volume in Vegetated Areas with UAV Data. (2021). Remote Sensing, 13(12), 2391. 2021. https://doi.org/10.3390/rs13122391
  • Enwright, N. M., Kranenburg, C. J., Patton, B. A., Dalyander, P. S., Brown, J. A., Piazza, S. C., & Cheney, W. C. (2021). Developing bare-earth digital elevation models from structure-from-motion data on barrier islands. Isprs Journal of Photogrammetry and Remote Sensing, 180, 269. 2021. https://doi.org/10.1016/j.isprsjprs.2021.08.014
  • Fraštia, M., Liščák, P., Žilka, A., Pauditš, P., Bobáľ, P., Hronček, S., Sipina, S., Ihring, P., & Marčiš, M. Mapping of debris flows by the morphometric analysis of DTM: A case study of the Vrátna dolina Valley, Slovakia. (2019). Geografický časopis - Geographical Journal, 71(2), 101–120. ISSN 0016-7193. https://doi.org/10.31577/geogrcas.2019.71.2.06
  • Goodbody, T. R. H., Coops, N. C., Hermosilla, T., Tompalski, P., & Pelletier, G. (2018). Vegetation 525 phenology driving error variation in digital aerial photogrammetrically derived Terrain 526 models. Remote Sensing, 10(10), 1554. https://doi.org/10.3390/rs10101554
  • Graham, A., Coops, N. C., Wilcox, M., & Plowright, A. (2019). Evaluation of ground surface models derived from unmanned aerial systems with digital aerial photogrammetry in a disturbed conifer forest. Remote Sensing, 11(1), 84. https://doi.org/10.3390/rs11010084
  • Guerra-Hernández, J., Cosenza, D. N., Rodriguez, L. C. E., Silva, M., Tomé, M., Díaz-Varela, R. A., & González-Ferreiro, E. (2018). Comparison of ALS-and UAV (SfM)-derived high-density point clouds for individual tree detection in Eucalyptus plantations. International Journal of Remote Sensing, 39(15–16), 5211–5235. https://doi.org/10.1080/01431161.2018.1486519
  • Guerra-Hernández, J., González-Ferreiro, E., Monleón, V. J., Faias, S. P., Tomé, M., & Díaz-Varela, R. A. (2017). Use of multi-temporal UAV-derived imagery for estimating individual tree growth in Pinus Pinea stands. Forests, 8(8), 300. https://doi.org/10.3390/f8080300
  • Hartley, R. J. L., Leonardo, E. M., Massam, P., Watt, M. S., Estarija, H. J., Wright, L., Melia, N., & Pearse, G. D. An Assessment of High-Density UAV Point Clouds for the Measurement of Young Forestry Trials. (2020). Remote Sensing, 12(24), 4039. 2020. https://doi.org/10.3390/rs12244039
  • Harwin, S., & Lucieer, A. Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery. (2012). Remote Sensing, 4(6), 1573–1599. 2012. https://doi.org/10.3390/rs4061573
  • James, M. R., & Robson, S. Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application. (2012). Journal of Geophysical Research: Earth Surface, 117(F3), F03017. 2012. https://doi.org/10.1029/2011JF002289
  • Jensen, J. L. R., & Mathews, A. J. (2016). Assessment of image-based point cloud products to generate a bare earth surface and estimate canopy heights in a woodland ecosystem. Remote Sensing, 8(1), 50. https://doi.org/10.3390/rs8010050
  • Jon, J., Koska, B., & Pospíšil, J. (2013). Autonomous Airship Equipped by Multi-Sensor Mapping Platform. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-5/W1(W1), 119–124. https://doi.org/10.5194/isprsarchives-XL-5-W1-119-2013
  • Jurjević, L., Gašparović, M., Liang, X., & Balenović, I. Assessment of CloseRange remote sensing methods for DTM estimation in a lowland deciduous forest. (2021). Remote Sensing, 13(11), 2063. 2021. https://doi.org/10.3390/rs13112063
  • Kachamba, D. J., Ørka, H. O., Næsset, E., Eid, T., & Gobakken, T. (2017). Influence of plot size on efficiency of biomass estimates in inventories of dry tropical forests assisted by photogrammetric data from an unmanned aircraft system. Remote Sensing, 9(6), 610. https://doi.org/10.3390/rs9060610
  • Kršák, B., Blišťan, P., Pauliková, A., Puškárová, P., Kovanič, Ľ., Palková, J., & Zelizňaková, V. (2016). Use of low-cost UAV photogrammetry to analyze the accuracy of a digital elevation model in a case study. Measurement, 91, 276–287. 2016. https://doi.org/10.1016/j.measurement.2016.05.028
  • Kucharczyk, M., Hugenholtz, C. H., & Zou, X. (2017). UAV–LIDAR accuracy in vegetated terrain. Journal of Unmanned Vehicle Systems, 6(4), 212–234. https://doi.org/10.1139/juvs-2017-0030
  • Kuželka, K., & Surový, P. (2018). Automatic detection and quantification of wild game crop damage using an unmanned aerial vehicle (UAV) equipped with an optical sensor payload: A case study in wheat. European Journal of Remote Sensing, 51(1), 241–250. https://doi.org/10.1080/22797254.2017.1419442
  • Leal-Alves, D. C., Weschenfelder, J., Albuquerque, M. D., Espinoza, J. M. D. A., Ferreira-Cravo, M., & Almeida, L. P. M. D. Digital elevation model generation using UAV-SfM photogrammetry techniques to map sea-level rise scenarios at Cassino Beach, Brazil. (2020). SN Applied Sciences, 2(12), 2181. 2020. https://doi.org/10.1007/s42452-020-03936-z
  • Liao, J., Zhou, J., & Yang, W. Comparing LiDAR and SfM digital surface models for three land cover types. (2021). Open Geosciences, 13(1), 497–504. 2021. https://doi.org/10.1515/geo-2020-0257
  • Lovitt, J., Rahman, M. M., & McDermid, G. J. Assessing the Value of UAV Photogrammetry for Characterizing Terrain in Complex Peatlands. (2017). Remote Sensing, 9(7), 715. 2017. https://doi.org/10.3390/rs9070715
  • Moravec, D., Komárek, J., Kumhálová, J., Kroulík, M., Prošek, J., & Klápště, P. (2017). Digital elevation models as predictors of yield: Comparison of an UAV and other elevation data sources. Agronomy Research, 15(1), 249–255.
  • Moudrý, V., Gdulová, K., Fogl, M., Klápště, P., Urban, R., Komárek, J., Moudrá, L., Štroner, M., Barták, V., & Solský, M. (2019). Comparison of leaf-off and leaf-on combined UAV imagery and airborne LiDAR for assessment of a post-mining site terrain and vegetation structure: Prospects for monitoring hazards and restoration success. Applied Geography, 104, 32–41. https://doi.org/10.1016/j.apgeog.2019.02.002
  • Moudrý, V., Moudrá, L., Barták, V., Bejček, V., Gdulová, K., Hendrychová, M., Moravec, D., Musil, P., Rocchini, D., Šťastný, K., Volf, O. & Šálek, M. (2021). The role of the vegetation structure, primary productivity and senescence derived from airborne LiDAR and hyperspectral data for birds diversity and rarity on a restored site. Landscape and Urban Planning, 210, 104064. https://doi.org/10.1016/j.landurbplan.2021.104064
  • Nesbit, P. R., Hubbard, S. M., & Hugenholtz, C. H. Direct Georeferencing UAV-SfM in High-Relief Topography: Accuracy Assessment and Alternative Ground Control Strategies along Steep Inaccessible Rock Slopes. (2022). Remote Sensing, 14(3), 490. 2022. https://doi.org/10.3390/rs14030490
  • Nesbit, P. R., & Hugenholtz, C. H. Enhancing UAV–SfM 3D Model Accuracy in High-Relief Landscapes by Incorporating Oblique Images. (2019). Remote Sensing, 11(3), 239. 2019. https://doi.org/10.3390/rs11030239
  • Nikolakopoulos, K., Kavoura, K., Depountis, N., Kyriou, A., Argyropoulos, N., Koukouvelas, I., & Sabatakakis, N. (2017). Preliminary results from active landslide monitoring using multidisciplinary surveys. European Journal of Remote Sensing, 50(1), 280–299. https://doi.org/10.1080/22797254.2017.1324741
  • Piras, M., Taddia, G., Forno, M. G., Gattiglio, M., Aicardi, I., Dabove, P., Lo Russo, S., & Lingua, A. (2017). Detailed geological mapping in mountain areas using an unmanned aerial vehicle: Application to the Rodoretto Valley. NW Italian Alps, Geomatics, Natural Hazards and Risk, 8(1), 137–149. https://doi.org/10.1080/19475705.2016.1225228
  • Prata, G. A., Broadbent, E. N., de Almeida, D. R. A., St. Peter, J., Drake, J., Medley, P., Corte, A. P. D., Vogel, J., Sharma, A., Silva, C. A., Zambrano, A. M. A., Valbuena, R., & Wilkinson, B. Single-Pass UAV-Borne GatorEye LiDAR Sampling as a Rapid Assessment Method for Surveying Forest Structure. (2020). Remote Sensing, 12(24), 4111. 2020. https://doi.org/10.3390/rs12244111
  • Resop, J. P., Lehmann, L., & Hession, W. C. Drone laser scanning for modeling riverscape topography and vegetation: Comparison with traditional aerial LiDAR. (2019). Drones, 3(2), 35. 2019. https://doi.org/10.3390/drones3020035
  • Rybansky, M. Determination of Forest Structure from Remote Sensing Data for Modeling the Navigation of Rescue Vehicles. (2022). Applied Sciences, 12(8), 3939. 2022. https://doi.org/10.3390/app12083939
  • Salach, A., Bakuła, K., Pilarska, M., Ostrowski, W., Górski, K., & Kurczyński, Z. Accuracy Assessment of Point Clouds from LiDAR and Dense Image Matching Acquired Using the UAV Platform for DTM Creation. (2018). ISPRS International Journal of Geo-Information, 7(9), 342. 2018. https://doi.org/10.3390/ijgi7090342
  • Santise, M., Fornari, M., Forlani, G., & Roncella, R. (2014). Evaluation of DEM generation accuracy from UAS imagery. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-5, 529–536. 2014, XL-. https://doi.org/10.5194/isprsarchives-XL-5-529-2014
  • Simpson, J., Smith, T., & Wooster, M. (2017). Assessment of errors caused by forest vegetation structure in airborne LiDAR-derived DTMs. Remote Sensing, 9(11), 1101. https://doi.org/10.3390/rs9111101
  • Štroner, M., Urban, R., Lidmila, M., Kolář, V., & Křemen, T. Vegetation Filtering of a Steep Rugged Terrain: The Performance of Standard Algorithms and a Newly Proposed Workflow on an Example of a Railway Ledge. (2021). Remote Sensing, 13(15), 3050. 2021. https://doi.org/10.3390/rs13153050
  • Štroner, M., Urban, R., & Línková, L. A New Method for UAV LiDAR Precision Testing Used for the Evaluation of an Affordable DJI ZENMUSE L1 Scanner. (2021). Remote Sensing, 13(23), 4811. 2021. https://doi.org/10.3390/rs13234811
  • Štroner, M., Urban, R., Reindl, T., Seidl, J., & Brouček, J. Evaluation of the georeferencing accuracy of a photogrammetric model using a quadrocopter with onboard GNSS RTK. (2020). Sensors, 20(8), 2318. 2020. https://doi.org/10.3390/s20082318
  • Štroner, M., Urban, R., Seidl, J., Reindl, T., & Brouček, J. Photogrammetry Using UAV-Mounted GNSS RTK: Georeferencing Strategies without GCPs. (2021). Remote Sensing, 13(7), 1336. 2021. https://doi.org/10.3390/rs13071336
  • Taddia, Y., Pellegrinelli, A., Corbau, C., Franchi, G., Staver, L. W., Stevenson, J. C., & Nardin, W. High-Resolution Monitoring of Tidal Systems Using UAV: A Case Study on Poplar Island, MD (USA). (2021). Remote Sensing, 13(7), 1364. 2021. https://doi.org/10.3390/rs13071364
  • Taddia, Y., Stecchi, F., & Pellegrinelli, A. Coastal mapping using DJI phantom 4 RTK in post-processing kinematic mode. (2020). Drones, 4(2), 9. 2020. https://doi.org/10.3390/drones4020009
  • Teppati Losè, L., Chiabrando, F., & Giulio Tonolo, F. Boosting the Timeliness of UAV Large Scale Mapping. Direct Georeferencing Approaches: Operational Strategies and Best Practices. (2020). ISPRS International Journal of Geo-Information, 9(10), 578. 2020. https://doi.org/10.3390/ijgi9100578
  • Tomaštík, J., Mokroš, M., Saloň, Š., Chudý, F., & Tunák, D. Accuracy of photogrammetric UAV-based point clouds under conditions of partially-open forest canopy. (2017). Forests, 8(5), 151. 2017. https://doi.org/10.3390/f8050151
  • Wang, Y., & Koo, K. -Y. Vegetation removal on 3D point cloud reconstruction of cut-slopes using U-net. (2022). Applied Sciences, 12(1), 395. 2022. https://doi.org/10.3390/app12010395
  • Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., & Yan, G. An easy-to-use airborne LiDAR data filtering method based on cloth simulation. (2016). Remote Sensing, 8(6), 501. 2016. https://doi.org/10.3390/rs8060501