Review of Effective Vegetation Mapping Using the UAV (Unmanned Aerial Vehicle) Method

DOI: 10.4236/jgis.2014.66060   PDF   HTML   XML   7,011 Downloads   9,877 Views   Citations


We tried more precise mapping of vegetation using UAV (unmanned aerial vehicle), as a new method of creating vegetation maps, and we objected to be clearly the efficient mapping of vegetation using the UAV method by comparing vegetation maps created by analysing aerial photographs taken by a UAV and an aircraft (manned flight). The aerial photography using UAV was conducted in the Niida River estuary (the secondary river flowing into Minamisoma City in Fukushima Prefecture, Japan). The photography period was in August 2013. We analysed the aerial photographs using ArcGis 9 (Esri Japan Corporation, Tokyo, Japan). The aerial photographs of the main plant communities (Phragmites australisTypha domingensis, and Miscanthus sacchariflorus) taken by the UAV could clearly discriminate each plant community at the 1/50 scale. Moreover, it could clearly discriminate the shape of a plant at the 1/10 scale. We compared the vegetation maps by analysing the aerial photos taken by a UAV (2013 shooting) and an aircraft (2011 shooting). As a result, the vegetation map created by the UAV method could clearly discriminate community distributions. We conclude that vegetation surveys using UAV are possible and are capable of a highly precise community division in places where field reconnaissance is difficult. The UAV method is effective and will contribute to the improvement of research methods in the future; this method may reduce research costs associated with a reduction in field survey days and man-power.

Share and Cite:

Kaneko, K. and Nohara, S. (2014) Review of Effective Vegetation Mapping Using the UAV (Unmanned Aerial Vehicle) Method. Journal of Geographic Information System, 6, 733-742. doi: 10.4236/jgis.2014.66060.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Environment Agency (2000) Technology Assessment of Natural Environment. Ministry of Finance Printing Bureau, Tokyo, 29-30.
[2] Organization for Landscape and Urban Green Infrastructure (2000) Ecological Network in the Urban. Gyo-sei, Tokyo, 141-142.
[3] Mathubayashi, K., Nemoto, J., Momose, H., Fujuwara, N. and Hioki, Y. (2002) Development of Vegetation Mapping Technique and Mapping Precision Using High Resolution Satellite Data. The Japanese Society of Revegetation Technology, 28, 127-131.
[4] Suzuki, T., Hashizume, T. and Suzuki, S. (2011) The Easy Building Measurement by Utilizing Small Autonomous Flying Robot (UAV). Building Construction Planning, 740, 65-69.
[5] Salami, E., Barrado, C. and Pastor, E. (2014) UAV Flight Experiments Applied to the Remote Sensing of Vegetation Area. Remote Sensing, 6, 11051-11081.
[6] Dunford, R., Michel, K., Gagnage, M., Piégay, H. and Trémelo, M.L. (2013) Potential and Constraints of Unmanned Aerial Vehicle Technology for the Characterization of Mediterranean Riparian Forest. International Journal of Remote Sensing, 30, 4915-4935.
[7] Nex, F. and Remondino, F. (2013) UAV for 3D Mapping Applications: A Review. Applied Geomatics, 6, 1-15.
[8] Arnold, T., Biasio, M.D., Fritz, A. and Leitner, R. (2013) UAV-Based Measurement of Vegetation Indices for Environmental Monitoring. 2013 Seventh International Conference on Sensing Technology, Wellington, 3-5 December 2013, 708-711.
[9] Wallace, L. (2013) Assessing the Stability of Canopy Maps Produced from UAV-LiDAR Data. Proceedings of 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, 21-26 July 2013, 3879-3882.
[10] Laliberte, A.S. and Rango, A. (2009) Texture and Scale in Object-Based Analysis of Subdecimeter Resolution Unmanned Aerial Vehicle (UAV) Imagery. IEEE Transactions Geoscience and Remote Sensing, 47, 761-770.
[11] Strecha, C., Fletcher, A., Lechner, A., Erskine, P. and Fua, P. (2012) Developing Species specific Vegetation Maps Using Multi-Spectral Hyperspatial Imagery from Unmanned Aerial Vehicle. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, I-3, XXII ISPRS Congress, 25 August-1 September 2012, Melbourne.
[12] Hung, C., Bryson, M. and Sukkarieh, S. (2012) Multi-Class Predictive Template for Tree Crown Detection. ISPRS Journal of Photogrammetry and Remote Sensing, 68, 170-183.
[13] Oguma, H., Usami, M., Shimazaki, H. and Ishihama, F. (2010) A High-Resolution Remote Sensing by Radio Control Helicopter and Apply to Species Discrimination of Individual Level of Wetland Herbaceous Plant. 57th Annual Conference of Ecological Society of Japan, Tokyo, 15-20 March 2010, Abstract.
[14] Eisenbeiss, H. (2004) A Mini Unmanned Aerial Vehicle (UAV): System Overview and Image Acquisition, International Workshop on Processing and Visualization Using High Resolution Imagery, Pitsanulok, 18-20 November 2004. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVI-5/W1.
[15] Berni, J., Zarco-Tejada, P., Suarez, L. and Fereres, E. (2009) Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring from an Unmanned Aerial Vehicle. IEEE Transactions on Geoscience and Remote Sensing, 47, 722-738.
[16] Berni, J., Zarco-Tejada, P., Suarez, L. and Fereres, E. (2014) Remote Sensing of Vegetation from UAV Platforms Using Lightweight Multispectral and Thermal Imaging Sensors. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, 38, 6.
[17] Jensen, A.M., Chen, Y., McKee, M., Hardy, T. and Barfuss, S.L. (2009) AggieAir—A Low-Cost Autonomous Multispectral Remote Sensing Platform: New Developments and Applications. Proceedings of 2009 IEEE International Geoscience and Remote Sensing Symposium, Cape Town, 12-17 July 2009, IV-995-IV-998.
[18] Ishihama, F., Watabe, Y. and Oguma, H. (2012) Validation of a High-Resolution, Remotely Operated Aerial Remote-Sensing System for the Identification of Herbaceous Plant Species. Applied Vegetation Science, 15, 383-389.
[19] Remondino, F., Barazzetti, L., Nex, F., Scaioni, M. and Sarazzi, D. (2011) UAV Photogrammetry for Mapping and 3D Modelling—Current Status and Future Perspectives. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVIII-I/C22 UAV-g 2011, Conference on Unmanned Aerial Vehicle in Geomatics, Zurich, 1-7.

comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.