Unmanned Aerial Vehicles for Three‑dimensional Mapping and Change Detection Analysis

• Autorzy: Gbopa Adetola Olufunmilayo , Ayodele Emmanuel Gbenga , Okolie Chukwuma John , Ajayi Akinwumi Olaitan , Iheaturu Chima Jude

Identyfikatory

DOI

10.7494/geom.2021.15.1.41

• Języki publikacji: EN

Abstrakty

EN

Unmanned Aerial Vehicles (UAVs), commonly known as drones are increasingly being used for three dimensional (3D) mapping of the environment. This study utilised UAV technology to produce a revised 3D map of the University of Lagos as well as land cover change detection analysis. A DJI Phantom 4 UAV was used to collect digital images at a flying height of 90 m, and 75% fore and 65% side overlaps. Ground control points (GCPs) for orthophoto rectification were coordinated with a Trimble R8 Global Navigation Satellite System. Pix4D Mapper was used to produce a digital terrain model and an orthophoto at a ground sampling distance of 4.36 cm. The change detection analysis, using the 2015 base map as reference, revealed a significant change in the land cover such as an increase of 16,306.7 m2 in buildings between 2015 and 2019. The root mean square error analysis performed using 7 GCPs showed a horizontal and vertical accuracy of 0.183 m and 0.157 m respectively. This suggests a high level of accuracy, which is adequate for 3D mapping and change detection analysis at a sustainable cost.

Słowa kluczowe

EN

UAV technology; 3D mapping; orthophoto; land cover; change detection analysis

PL

Technologia UAV; mapowanie 3D; ortofoto; pokrycie terenu; analiza wykrywania zmian

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Geomatics and Environmental Engineering
• Rocznik: 2021
• Tom: Vol. 15, no. 1
• Strony: 41--61
• Opis fizyczny: Bibliogr. 24 poz., fot., rys., tab.

Twórcy

autor

Gbopa Adetola Olufunmilayo

• University of Lagos, Department of Surveying and Geoinformatics, Nigeria

• https://orcid.org/0000-0003-2476-573X

autor

Ayodele Emmanuel Gbenga

• University of Lagos, Department of Surveying and Geoinformatics, Nigeria

• https://orcid.org/0000-0003-2684-2276

autor

Okolie Chukwuma John

• University of Lagos, Department of Surveying and Geoinformatics, Nigeria

• https://orcid.org/0000-0003-4542-7051

autor

Ajayi Akinwumi Olaitan

• University of Lagos, Department of Surveying and Geoinformatics, Nigeria

• https://orcid.org/0000-0001-9135-1153

autor

Iheaturu Chima Jude

• Imo State University, Department of Surveying and Geoinformatics, Nigeria

• https://orcid.org/0000-0003-0472-9715

Bibliografia

• [1] Nex F., Remondino F.: UAV for 3D mapping applications: a review. AppliedGeomatics, vol. 6, 2014, pp. 1–15. https://doi.org/10.1007/s12518-013-0120-x.
• [2] Zaragoza M.I., Caroti G., Piemonte A., Riedel B., Tengen D., Niemeier W.: Structure from motion (SfM) processing of UAV images and combination with terrestrial laser scanning, applied for a 3D-documentation in a hazardous situation. Geomatics, Natural Hazards and Risk, vol. 8, issue 2, 2017, pp. 1492–1504.
• [3] Schultz R.J.: Leveling. [in:] Brinker R.Ch., Minnick R. (eds.), The Surveying Handbook. 2nd ed., Springer Science + Business Media, Dordrech 1995, pp. 113–139.
• [4] Wahr J.: Geodesy and Gravity: Class Notes. Samizdat Press, Colorado 1996.
• [5] Luh H.S.: High resolution survey for topographic surveying. IOP Conference Series: Earth and Environmental Science, vol. 18, 2014, 012067. https://doi.org/10.1088/1755-1315/18/1/012067.
• [6] Remondino F., Barazzetti L., Nex F., Scaioni M., Sarazzi D.: UAV Photogrammetry for mapping and 3D modeling – Current status and future perspectives. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVIII-1/C22, 2011, pp. 25–31. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-25-2011.
• [7] Gustafsson H.: Unmanned Aerial Vehicles for Geographic Data Capture: A Review. Examensarbete Teknik, Grundnivå, 15 Hp, Stockholmsverige, 2017. https://www.diva-portal.org/smash/get/diva2:1116742/FULLTEXT01.pdf [access: 27.09.2018].
• [8] Lahoti S., Lahoti A., Saito O.: Application of Unmanned Aerial Vehicle (UAV) for Urban Green Space Mapping in Urbanizing Indian Cities. [in:] Avtar R., Watanabe T. (eds.), Unmanned Aerial Vehicle: Applications in Agriculture and Environment, Springer, Cham 2020, pp. 177–188. https://doi.org/10.1007/978-3-030-27157-2_13.
• [9] Iizuka K., Itoh M., Shiodera S., Matsubara T., Dohar M., Watanabe K.: Advantages of unmanned aerial vehicle(UAV) photogrammetry for landscape analysis compared with satellite data: A case study of postmining sites in Indonesia. Cogent Geoscience, vol. 4(1), 2018, 1498180. https://doi.org/10.1080/23312041.2018.1498180.
• [10] Ruwaimana M., Satyanarayana B., Otero V.M., Muslim A., Syafiq A.M., Ibrahim S. et al.: The advantages of using drones over space‑borne imagery in the mapping of mangrove forests. PLoS ONE, vol. 13(7), 2018, e0200288. https://doi.org/10.1371/journal.pone.0200288.
• [11] Koeva M., Muneza M., Gevaert C., Gerke M., Nex F.: Using UAVs for map creation and updating. A case study in Rwanda. Survey Review, vol. 50, issue 361, 2018, pp. 312–325. https://doi.org/10.1080/00396265.2016.1268756.
• [12] Sarp G., Erener A., Duzgun S., Sahin K.: An approach for detection of buildings and changes in buildings using orthophotos and point clouds: A case study of Van Erriş earthquake. European Journal of Remote Sensing, vol. 47(1), 2014, pp. 627–642.
• [13] Qin R.: An Object‑Based Hierarchical Method for Change Detection Using Unmanned Aerial Vehicle Images. Remote Sensing, vol. 6, 2014, pp. 7911–7932. https://doi.org/10.3390/rs6097911.
• [14] Freire S., Santos T., Navarro A., Soares F., Silva J., Afonso N., Fonseca A., Tenedório J.: Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 90, 2014, pp. 1–9.
• [15] Yao H., Qin R., Chen X.: Unmanned Aerial Vehicle for Remote Sensing Applications – A Review. Remote Sensing, vol. 11, 2019, 1443. https://doi.org/10.3390/rs11121443.
• [16] Akar Ö.: Mapping land use with using Rotation Forest algorithm from UAV images. European Journal of Remote Sensing, vol. 50(1), 2017, pp. 269–279. https://doi.org/10.1080/22797254.2017.1319252.
• [17] Qian Y.G., Zhou W.Q., Yan J.L., Li W.F., Han L.J.: Comparing machine learning classifiers for object‑based land cover classification using very high resolution imagery. Remote Sensing, vol. 7(1), 2015, pp. 153–168. https://doi.org/10.3390/rs70100153.
• [18] Jumaat N.F.H., Ahmad B., Dutsenwai H.S.: Land cover change mapping using high resolution satellites and unmanned aerial vehicle. IOP Conference Series: Earth and Environmental Science, vol. 169(1), 2018, 012076. https://doi.org/10.1088/1755-1315/169/1/012076.
• [19] Franklin S.E., Wulder M.A.: Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas. Progress in Physical Geography: Earth and Environment, vol. 26(2), 2002, pp. 173–205.
• [20] Iheaturu C.J., Ayodele E.G., Okolie C.J.: An Assessment of the Accuracy of Structure‑from‑Motion (SfM) Photogrammetry for 3D Terrain Mapping. Geomatics, Landmanagement and Landscape, no. 2, 2020, pp. 65–82.
• [21] Smith M.W., Vericat D.: From experimental plots to experimental landscapes: to‑ pography, erosion and deposition in sub‐humid badlands from structure‐from‐motion photogrammetry. Earth Surface Processes and Landforms, vol. 40, no. 12, 2015, pp. 1656–1671.
• [22] Smith M.W., Carrivick J.L., Quincey D.J.: Structure from motion photogrammetry in physical geography. Progress in Physical Geography, vol. 40, no. 2, 2016, pp. 247–275.
• [23] NSSDA: Geospatial Positioning Accuracy Standards. Part 3: National Standard for Spatial Data Accuracy. Federal Geographic Data Committee Secretariat, Reston, Virginia, 1998. https://www.fgdc.gov/standards/projects/accuracy/part3 [access: 28.10.2020].
• [24] Greenwalt C.R., Schultz M.E.: Principles and Error Theory and Cartographic Applications. ACIC Technical Report No. 96, Aeronautical Chart and Information Center, U.S. Air Force, St. Louis 1968.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)