ORIGINAL ARTICLE
Accuracy Investigation of Creating Orthophotomaps Based on Images Obtained by Applying Trimble-UX5 UAV
 
More details
Hide details
1
Department of Photogrammetry and Geoinformatics, National University Lviv Polytechnic, Institute of Geodesy, Karpinski St. 6, 79013 Lviv, Ukraine
 
2
Department of Geodesy, University of Agriculture in Krakow, Balicka St. 253a, 30-198 Krakow, Poland
 
 
Submission date: 2016-10-16
 
 
Acceptance date: 2017-05-27
 
 
Online publication date: 2017-08-01
 
 
Publication date: 2017-06-27
 
 
Reports on Geodesy and Geoinformatics 2017;103:106-118
 
KEYWORDS
ABSTRACT
The main purpose of this work is to confirm the possibility of making largescale orthophotomaps applying unmanned aerial vehicle (UAV) Trimble- UX5. A planned altitude reference of the studying territory was carried out before to the aerial surveying. The studying territory has been marked with distinctive checkpoints in the form of triangles (0.5 × 0.5 × 0.2 m). The checkpoints used to precise the accuracy of orthophotomap have been marked with similar triangles. To determine marked reference point coordinates and check-points method of GNSS in real-time kinematics (RTK) measuring has been applied. Projecting of aerial surveying has been done with the help of installed Trimble Access Aerial Imaging, having been used to run out the UX5. Aerial survey out of the Trimble UX5 UAV has been done with the help of the digital camera SONY NEX-5R from 200m and 300 m altitude. These aerial surveying data have been calculated applying special photogrammetric software Pix 4D. The orthophotomap of the surveying objects has been made with its help. To determine the precise accuracy of the got results of aerial surveying the checkpoint coordinates according to the orthophotomap have been set. The average square error has been calculated according to the set coordinates applying GNSS measurements. A-priori accuracy estimation of spatial coordinates of the studying territory using the aerial surveying data have been calculated: mx=0.11 m, my=0.15 m, mz=0.23 m in the village of Remeniv and mx=0.26 m, my=0.38 m, mz=0.43 m in the town of Vynnyky. The accuracy of determining checkpoint coordinates has been investigated using images obtained out of UAV and the average square error of the reference points. Based on comparative analysis of the got results of the accuracy estimation of the made orthophotomap it can be concluded that the value the average square error does not exceed a-priori accuracy estimation. The possibility of applying Trimble UX5 UAV for making large-scale orthophotomaps has been investigated. The aerial surveying output data using UAV can be applied for monitoring potentially dangerous for people objects, the state border controlling, checking out the plots of settlements. Thus, it is important to control the accuracy the got results. Having based on the done analysis and experimental researches it can be concluded that applying UAV gives the possibility to find data more efficiently in comparison with the land surveying methods. As the result, the Trimble UX5 UAV gives the possibility to survey built-up territories with the required accuracy for making orthophotomaps with the following scales 1: 2000, 1: 1000, 1: 500.
 
REFERENCES (30)
1.
Bajwa, S. & Tian, L. (2001). Aerial CIR remote sensing for weed density mapping in a soybean field. Transactions of the American Society of Agricultural Engineers, vol. 44(6), pp. 1965- 1974.
 
2.
Вовк, А.; Глотов, В.; Гуніна, А.; Маліцький, А.; Третяк, К.; Церклевич, А. (2015) Аналіз результатів для створення ортофотопланів та цифрових моделей рельєфу із застосуванням БПЛА TRIMBLE UX-5, Міжвідомчий наук.-техн. збірник “Геодезія, картографія і аерофотознімання”, № 81, pp. 89-102, http://ena.lp.edu.ua:8080/bits....
 
3.
Бурштинська, Х. В.(1999). Аерофотографія: Навчальний підручник. - Львів, 356.
 
4.
Catur, A. R. (2015). The 1st International Symposium on LAPAN-IPB Satellite for Food Security and Environmental Monitoring, The potential of UAV-based remote sensing for supporting precision agriculture in Indonesia. Procedia Environmental Sciences, vol. 24, pp. 245 - 253.
 
5.
Coppa, U., Guarnieri, A., Pirotti, F.& Vettore, A. (2009). Accuracy enhancement of unmanned helicopter positioning with low-cost system. Applied Geomatics, pp.85-95.
 
6.
Fernández-Hernandez, J., González-Aguilera, D., Rodríguez-Gonzálvez, P. & Mancera-Taboada, J. (2014). Image-based modelling from unmanned aerial vehicle (UAV) photogrammetry: an effective, low-cost tool for archaeological applications. Archaeometry, vol. 57, 1 pp. 128-145.
 
7.
Глотов, В. Церклевич, А., Збруцький, О., Колісніченко, В., Прохорчук, О., Карнаушенко, Р., Галецький, В. (2014) Аналіз і перспективи аерознімання з безпілотного літального апарата, Збірник наукових праць «Сучасні досягнення геодезичної науки та виробництва», № І(27), с. 131-136, http://ena.lp.edu.ua:8080/bits....
 
8.
Haarbrink, R. & Eisenbeiss, H. (2008). Accurate DSM production from unmanned helicopter systems. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B1, pp. 1259 - 1264.
 
9.
Hadjimitsis, D., Clayton, C. & Hope, V. (2004). An assessment of the effectiveness of atmospheric correction algorithms through the remote sensing of some reservoirs. International Journal of Remote Sensing, vol. 25, no. 18, pp. 3651-3674.
 
10.
Hartley, R. & Zisserman, A., (2003). Multiple view geometry in computer vision, Cambridge University Press, NewYork, pp. 485-486.
 
11.
Klinken, R., Shepherd, D., Parr, R., Robinson, T. & Anderson, L. (2007). Mapping mesquite (prosopis) distribution and density using visual aerial surveys. Rangeland Ecology Management, vol. 60, pp. 408-416.
 
12.
Маслянко, В. Я. (2014) Применение 3d-технологий при оперативном планировании и проектировании открытых горных работ. XII всероссийское совещание по проблемам управления ВСПУ-2014, Москва, с. 4337-4347, http://vspu2014.ipu.ru/proceed....
 
13.
Mahiny, A. & Turner B. A (2007). Comparison of Four Common Atmospheric Correction Methods. Photogrammetric Engineering and Remote Sensing, vol.73, No 4, pp. 361-368.
 
14.
Mayr, W. (2013). Unmanned aerial systems-for the rest of us. In: 54th Photogrammetric Week. Institut für Photogrammetrie, Universität Stuttgart, pp. 151-163.
 
15.
Mikrut, S. (2016). Classical photogrammetry and UAV - selected ascpects. The International Archives of the Photogrammetry, Remote Sensing and Spatial information sciences, Volume XLI-B1, 2016 XXIII ISPRS Congress, 12-19 July 2016, Prague, Czech Republic, pp. 947 - 952.
 
16.
Mitch, B., Reid, A., Ramos, F. & Sukkarieh, S. (2010). Airborne Vision-Based Mapping and Classification of Large Farmland Environments. Journal of Field Robotics, vol. 27(5), pp. 632-655.
 
17.
Nebiker, S., Annen, A., Scherrer, M. & Oesch, D. (2008). A light-weight multispectral sensor for micro UAV - opportunities for very high resolution airborne remote sensing. The International Archives of the Photogrammetry, Remote Sensing and Spatial information sciences, vol. XXXVII, Part B1, Beijing, China, pp. 1193-1200.
 
18.
Petrie, G. (2013). Commercial operation of lightweight UAVs for aerial imaging and mapping. GEOInformatics, vol. 16, pp. 28-39.
 
19.
Rehak, M., Mabillard, R. & Skaloud, J. (2013). A micro-UAV with the capability of direct georeferencing. International Society for Photogrammetry and Remote Sensing, Spatial Inform., Sci. XL-1/W2, pp. 317-323.
 
20.
Sandmann, H. & Lertzman, K. (2003). Combining highresolution aerial photography with gradient-directed transects to guide field sampling and forest mapping in mountainous terrain. Forest Science, vol. 49(3), pp. 429-443.
 
21.
Smith, G. М. & Milton, E., J. (1999). The use of the empirical line method to calibrate remotely sensed data to reflectance. International Journal of Remote Sensing, vol. 20(13), pp. 2653-2662.
 
22.
Steffen, R. & Förstner, W. (2008). On visual real time mapping for unmanned aerial vehicles. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVII, Part B1, Beijing, China, pp. 57-62.
 
23.
Vallet, J., Panissod, F., Strecha, C. & Tracol, M. (2011). Photogrammetric performance of an ultra light weight swinglet UAV. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVIII- 1/C22, pp. 253-258.
 
24.
Vasuki, Y., Holden, Р., Kovesi, P. & Micklethwaite, S. (2014). Semi-automatic mapping of geological Structures using UAV-based photogrammetric data: An image analysis approach. Computers & Geosciences, 2014, vol. 69, pp. 22-32.
 
25.
Whelan, B. & James, T. (2010). An introduction to Precision Agriculture for Australian grains. Australian Centre for Precision Agriculture, University of Sydney for the Grains Research and Development Corporation.; p. 208.
 
26.
Zhang, N., Wang, V. & Wang, N. (2002). Precision agriculture - A worldwide overview. Computers and Electronics in Agriculture, No. 36, pp.113-132.
 
27.
Wang, J., Lin, Z. & Li. C. (2004). Reconstruction of buildings from a single UAV image. XX-th ISPRS Congress Istanbul, Turkey, pp. 100-103.
 
28.
Накидной монтаж и оценка качества материалов аэрофотосъемки.
 
30.
Trimble UX5 Aerial Imaging Solution: http://trl.trimble.com/docusha....
 
eISSN:2391-8152
ISSN:2391-8365
Journals System - logo
Scroll to top