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ISSN : 2287-8327

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Vol.41 No.4
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How to utilize vegetation survey using drone image and image analysis software

Journal of Ecology and Environment / Journal of Ecology and Environment, (P)2287-8327; (E)2288-1220
2017, v.41 no.4, pp.114-119
https://doi.org/10.1186/s41610-017-0035-2

(Institute of Ecosystem Restoration Planning)

& (2017). How to utilize vegetation survey using drone image and image analysis software. Journal of Ecology and Environment, 41(4), 114-119, https://doi.org/10.1186/s41610-017-0035-2
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Abstract

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

keywords
Vegetation survey, Actual vegetation map, Drone image, Aerial image, Image analysis software

Reference

1.

Arboretum, K. N. (2015). Report of research and monitoring on wetlands of civil owned forest. Pocheon: Korea National Arboretum.

2.

Arboretum, K. N. (2016). Conservation projects of forest wetlands. Pocheon: Korea National Arboretum.

3.

Kim, S. M. (2014). Study of the UAV for application plans and landscape analysis. Journal of the Korean Institute of Traditional Landscape Architecture, 32, 213–220.

4.

Kim, J. W., & Lee, Y. K. (2006). Classification and assessment of plant communities. Seoul: World Science.

5.

Kim, B. J., Lee, Y. K., & Choi, J. K. (2015). Investigating applicability of unmanned aerial vehicle to the tidal flat zone. Korean Journal of Remote Sensing, 31, 461–471.

6.

Lee, W. G. (2015). Urban managements using drones. Busan: Busan Development Institute.

7.

Lee, S. J., & Choi, Y. S. (2015). Topographic survey at small-scale open-pit mines using a popular rotary-wing unmanned aerial vehicle (drone). Tunnel &Underground space, 25, 462–469.

8.

Lee, S. J., & Choi, Y. S. (2016). Comparison of topographic surveying results using a fixed-wing and a popular rotary-wing unmanned aerial vehicle (drone). Tunnel & Underground space, 26, 24–31.

9.

National Institute of Ecology. (2015). Monitoring of invasive alien species designated by the Wildlife Protection Act (II). Seocheon: National Institute of Ecology. Korea.

10.

Siebert, S., & Teizer, J. (2014). Mobile 3D mapping for surveying earthwork projects using an unmanned aerial vehicle (UAV) system. Automation in Construction, 41, 1–14.

11.

Tahar, K. N., Ahmad, A., & Wan Mohd Akib, W. A. A. (2011). UAV-based stereo vision for photogrammetric survey in aerial terrain mapping. Penang: Proceedings of IEEE International Conference on Computer Applications and Industrial Electronics.

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