Oil-Palm Plantation Identification from Satellite Images Using Google Earth Engine
| Main Authors: | Puttinaovarat, Supattra; Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani campus, Surat Thani, Thailand, Horkaew, Paramate; School of Computer Engineering, Institute of Engineering, Suranaree University of Technology Nakhon Ratchasima, Thailand |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
International Journal on Advanced Science, Engineering and Information Technology
, 2018
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| Subjects: | |
| Online Access: |
http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/2415 http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/2415/pdf_718 |
Daftar Isi:
- Oil-palm plantation is a crucial determinant for land-use planning and agricultural studies. Remote sensing techniques have elevated limitations of the on-site survey as computerized imaging is much efficient and economical. This paper presents a ubiquitous application of Gabor analysis for extracting oil-palm plantation from satellite images. The proposed system was built on the cloud-based Google Earth Engine. Herein, THEOS images were convoluted with Gabor kernels, and both K-Means and SVM then learned their responses for comparison. Experimental results showed that SVM could better identify the plantation areas with precision, recall, and accuracy of 92.98%, 88.96%, and 94.24% respectively.