Development of Landsat-8 Image Radiometric Quality Score using Haze and Cloud Detection Algorithm

Image radiometric quality score is the score that shows how good the image from radiometric error, at least there are two parameters derived from Landsat-8 image that can be used to assess the radiometric quality, there are haze and cloud. This study used the Landsat-8 ortho rectified ready images, Top Of Atmospheric (TOA) and Bidirectional Reflectance Distribution Function (BRDF) algorithm were applied in radiometric correction. The haze identification technique was analyzed from the 2 dimensional (2D) histogram (scatterplot) between blue and red bands using supervised algorithm. The cloud identification was derived using the visible and cirrus band, visible band was used to detect the thick cloud, but the cirrus band to detect cirrus cloud. The identification result was transformed into 100 levels, score 1 shows pixel with lowest quality, and score 100 shows highest quality in radiometric. The minimum score was used in combining the haze and cloud images score to generate final radiometric score. The results shows that all the 5 scenes processed are no omission error, but some commission error, so that this algorithm is good enough for making the image mosaic.