Evaluate of THEOS Pan-sharpened Images using the Vegetation Indices for Orchard Classification

Authors

  • Satith Sangpradid Department of Geoinformatics, Faculty of Informatics, Mahasarakham University, Kantarawichai District, Maha Sarakham 44150

Keywords:

Optimum Index Factor, Fuzzy K-mean, Vegetation Indices, Unsupervised Classification, Remote Sensing

Abstract

THEOS pan-sharpened image is the high-resolution image. Nevertheless, the problem with the THEOS
pan-sharpened image is the issue of the agriculture classification. The objective of this research are to the evaluate of
THEOS pan-sharpened image using vegetation indices and the classification of orchard or perennial tree using fuzzy kmean. The NDVI and RVI used for evaluating the pan-sharpened image by used the OIF value to indicate the
optimum of four bands to classified land use using the fuzzy k-mean. The results of the combination of band NDVI
and RVI show the OIF value and the accuracy assessment of land use classification was higher than the original
image.

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Published

2020-12-25

How to Cite

Satith Sangpradid. (2020). Evaluate of THEOS Pan-sharpened Images using the Vegetation Indices for Orchard Classification. International Journal of Advance Research in Engineering, Science & Technology, 7(12), 1–9. Retrieved from https://ijarest.org/index.php/ijarest/article/view/1998

Issue

Vol. 7 No. 12 (2020): Volume: 07, Issue: 12 - December, 2020.

Section

Articles