Kustiyo and Anis Kamilah Hayati (2016) Haze Removal in the Visible Bands of Landsat 8 Oli over Shallow Water Area. International Journal of Remote Sensing and Earth Sciences, 13 (2). pp. 151-157. ISSN 0216-6739
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Abstract
Haze is one of radiometric quality parameters in remote sensing imagery. With certain atmospheric correction, haze is possible to be removed. Nevertheless, an efficient method for haze removal is still a challenge. Many methods have been developed to remove or to minimize the haze disruption. While most of the developed methods deal with removing haze over land areas, this paper tried to focus to remove haze from shallow water areas. The method presented in this paper is a simple subtraction algorithm between a band that reflected by water and a band that absorbed by water. This paper used data from Landsat 8 with visible bands as a band that reflected by water while the band that absorbed by water represented by NIR, SWIR-1, and SWIR-2 bands. To validate the method, a reference data which relatively clear of cloud and haze contamination is selected. The pixel numbers from certain points are selected and collected from data scene, results scene and reference scene. Those pixel numbers, then being compared each other to get a correlation number between data scene to reference scene and between result scene and reference scene. The comparison shows that the method using NIR, SWIR-1, and SWIR-2 all significantly improved correlations numbers between result scene with reference scene to higher than 0.9. The comparison also indicates that haze removal result using NIR band had the highest correlation with reference data..
Item Type: | Article |
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Uncontrolled Keywords: | haze removal, shallow water, Landsat 8 |
Subjects: | Taksonomi LAPAN > Teknologi Penginderaan Jauh > Penelitian, Pengkajian, dan Pengembangan > Teknologi dan Data Penginderaan Jauh > Perolehan Data > Koreksi Radiometrik |
Divisions: | LAPAN > Deputi Penginderaan Jauh > Pusat Teknologi dan Data Penginderaan Jauh |
Depositing User: | Administrator Repository |
Date Deposited: | 30 Aug 2021 12:03 |
Last Modified: | 20 Jul 2022 02:38 |
URI: | https://karya.brin.go.id/id/eprint/11203 |