Optimum Index Factor and Cloud Removal on the Landsat Imagery Data Processing

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M.S. Ziliwu, Tulus, Sutarman, M. Zarlis, Z. Situmorang, A.S. Harahap

2018 Journal of Physics: Conference Series Vol. 1116 Issue 2 Conference paper Cited by 3 SDG 13SDG 17 Quartile

Abstract

The research by using landsat imagery data which is a remote observation and recording technology equipped with Enhanced Thematic Mapper Plus (ETM +) sensor has been conducted. Landsat-7 has a sensor that produces images with 7 bands of 1, 2, 3, 4, 5, and 7 with spatial resolution of 30×30 m and band 6 with a spatial resolution of 120×120 m. The image processing begins with obtaining the best combination of Optimum Index Factor (OIF) is one of the methods used to get the proper combination.Landsat data imagery also contains cloud cover which can interfere and hamper in the process of obtaining more accurate landsat image data. Cloud removal by using K-Means Clustering process can separate and clusterize each object in the image based on the closest color and distance so that clouds and other land cover can be clustered and freed from the cloud visually. © Published under licence by IOP Publishing Ltd.

Affiliations

Postgraduate School, Department of Technical Information, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Medan, Indonesia; Department of Mathematics, Faculty of Mathematic and Natural Sciences, Universitas Sumatera Utara, Medan, Indonesia; Faculty of Computer Science, Universitas Katolik Santo Thomas, Medan, Indonesia

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