Haris Suka Dyatmika, Liana Fibriawati


Cloud free mosaic simplified the remote sensing imagery. Multi-temporal image mosaic needed to make a cloud free mosaic i.e. in the area covered by cloud throughout year like Indonesia. One of the satellite imagery that was widely used for various purposes was Landsat 8 image due to the temporal, spatial and spectral resolution which was suitable for many utilization themes. Landsat 8 could be used for multi-temporal image mosaic of the entire region in Indonesia. Landsat 8 had 16 days temporal resolution which allowed a region (scene image) acquired in a several times one year. However, not all the acquired Landsat 8 scene was proper when used for multi-temporal mosaic. The purpose of this work was observing radiometric parameters for scene selection method so a good multi-temporal mosaic image could be generated and more efficient processing. This study analyzed the relationship between radiometric parameters from image i.e. histogram and Scattergram with scene selection for multi-temporal mosaic purposes. Histogram and Scattergram representing radiometric imagery context such as mean, standard deviation, median and mode which was displayed visually. The data used were Landsat 8 imagery with the Area of Interest (AOI) in Kalimantan and Lombok. Then the histogram and Scattergram of the image AOI was analyzed. From the histogram and Scattergram analysis could be obtained that less shift between the data’s histogram and the more Scattergram forming 45 degree angle for distribution of the data then indicated more similar to radiometric of the image.


Landsat 8; mosaic; histogram; Scattergram

Full Text:



Dean S and Illowsky B., (2009), Descriptive Statistics: Histogram, https://legacy-textbook-qa. [accessed on Oktober 20 2015].

Dyatmika HS, Fibriawati L., (2015), Pemilihan Scene Mosaik Multitemporal Citra Landsat 8 Berdasarkan Parameter Radiometrik dari Histogram dan Scattergram, Seminar Nasional Pengideraan Jauh (In Indonesian).

Elvidge CD, Yuan D, Weerackoon RD, Lunetta RS, (1995), Relative Radiometric Normalization of Landsat Multispectral Scanner (MSS) Data Using an Automatic Scattergram-Controlled Regression, Photogrametric Engineering & Remote Sensing, 61 (10): 1255-1260.

Harijono SWB, (2008), Analisis Dinamika Atmosferdi Bagian Utara Ekuator Sumaterapada Saat Peristiwa El-Ninodan Dipole Mode Positif Terjadi Bersamaan, Jurnal Sains Dirgantara 5(2):130-148.

Helmer EH, Ruefenacht B., (2005), Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching. Photogrammetric Engineering & Remote Sensing 71(9): 1079–1089.

Hoffman PE, Grinstein GG., (2002), Information Visualization in Data Mining and Knowledge Discovery. Morgan Kaufmann Publishers. University of Massachusetts, Lowell MA.

Justice CO, Vermote E, Townshend JRG. Defries R, Roy DP, Hall DK, Salomonson VV, Privette JL, Riggs G, Strahler A, Lucht W, Myneni RB, Knyazikhin Y, Running SW, Nemani RR, Wan Z, Huete AR, Leeuwen VW, Wolfe RE, Giglio L, Muller JP, Lewis P, Barnsley MJ., (1998), The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research. Geoscience and Remote Sensing IEEE Transactions 36(4):1228-1249.

Kaplan JJ, Gabrosek JG, Curtiss P, Malone C., (2014), Investigating Student Understanding of Histograms, Journal of Statistics Education 22(2).

LAPAN, (2014), The Remote Sensing Monitoring Program of Indonesia’s National Carbon Accounting System : Methodology and Products, Version 1. LAPAN – IAFCP. Jakarta.

Murinto, Willy PP, Sri H., (2008), Analisis Perbandingan Histogram Equalization dan Model Logarithmic Image Processing (LIP) untuk Image Enhancement. Jurnal Informatika 2(2):200-208.

Richards JA., (2013), Remote Sensing Digital Image Analysis.Springer-Verlag Berlin Heidelberg.

Su MS, Hwang WL, Cheng KY., (2004), Analysis on Multiresolution Mosaic Images: IEE Transaction on Image Processing 13(7).

USGS, (2015), LANDSAT 8 (L8) DATA USERS HANDBOOK. Department of the Interior U.S. Geological Survey.

Zhu X, Gao F, Liu D, Chen J., (2012), A Modified Neighborhood SimilarPixel Interpolator Approach for Removing Thick Clouds in Landsat images, IEEE Geoscienceand Remote sensing 3(9):521-525.


  • There are currently no refbacks.