Cloud removal on satellite imagery using blended model: case study using quick look of high-resolution image of Indonesia

Abstract

The problem with the acquisition of satellite imagery in the tropics, especially in the area around the equator is that it is almost covered by clouds throughout the year. Users need cloud cover information and the possibility of obtaining cloudless satellite images before they get the data. An overview of the availability of cloud coverage distribution, especially those presented in a spatial format, was very beneficial and increased efficiency for users to select image data in the area of interest (AoI). This study aimed to develop a cloud removal, so-called blended cloud removal (BCR) model, which was applied in a part of West Java Province. The data used for this study were 33 images of quick looks at high-resolution satellite images of the 2013-2015 period that could be obtained free of charge on the website. The results showed that the distribution of efficiency was that AoI-1 obtained 99.67% efficiency of cloud removal image, AoI-2 was 76.51%, and AoI-3 obtained 98.34%. These three AoI locations have an average efficiency of 91.50%. As a result, there was substantial evidence that fewer than 10% of cloud cover remains after cloud removal. This suggests that by using the BCR model, a considerable change in cloud cover for the AoI location might be obtained, meeting the Geospatial Information Agency’s standards.