Crop Classification Using Imagery of Drone

DOI

10.2991/eers-15.2015.22How to use a DOI?

Keywords

component; drone; object based method; crops classifition; remote sensing

Abstract

Drone have several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude i.e. 80~400m, they can obtain good quality images even in cloudy weather. Therefore, they are ideal for acquiring spatial data in cases of small agricultural field with mixed crop, abundant in South Korea. This study discuss the use of low cost the drone based remote sensing for classifying crops. The study area is a main producer of Chinese cabbage and radish. This study acquired image using fixed wing drone on September 23, 2014. An object-based technique is used for classification of crops. The results showed that scale 250, shape 0.1, color 0.9, compactness 0.5 and smoothness 0.5 were the optimum parameter values in image segmentation. As a result, the kappa coefficient was 0.82 and the overall accuracy of classification was 84.7%. The drone images taken at the appropriate time will be able to solve the difficulties of remote sensing data acquisition of agricultural area.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jin-ki Park
AU  - Jonghwa Park
PY  - 2015/09
DA  - 2015/09
TI  - Crop Classification Using Imagery of Drone
BT  - Proceedings of the 2015 International Conference on Environmental Engineering and Remote Sensing
PB  - Atlantis Press
SP  - 91
EP  - 94
SN  - 2352-538X
UR  - https://doi.org/10.2991/eers-15.2015.22
DO  - 10.2991/eers-15.2015.22
ID  - Park2015/09
ER  -