Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal International Journal of Remote Sensing and Earth Sciences (IJReSES) The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Haris Suka Dyatmika
Unknown Affiliation
Earth & Planetary Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
THE EFFECT OF JPEG2000 COMPRESSION ON REMOTE SENSING DATA OF DIFFERENT SPATIAL RESOLUTIONS Anis Kamilah Hayati; Haris Suka Dyatmika
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 2 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1204.693 KB) | DOI: 10.30536/j.ijreses.2017.v14.a2724

Abstract

The huge size of remote sensing data implies the information technology infrastructure to store, manage, deliver and process the data itself. To compensate these disadvantages, compressing technique is a possible solution. JPEG2000 compression provide lossless and lossy compression with scalability for lossy compression. As the ratio of lossy compression getshigher, the size of the file reduced but the information loss increased. This paper tries to investigate the JPEG2000 compression effect on remote sensing data of different spatial resolution. Three set of data (Landsat 8, SPOT 6 and Pleiades) processed with five different level of JPEG2000 compression. Each set of data then cropped at a certain area and analyzed using unsupervised classification. To estimate the accuracy, this paper utilized the Mean Square Error (MSE) and the Kappa coefficient agreement. The study shows that compressed scenes using lossless compression have no difference with uncompressed scenes. Furthermore, compressed scenes using lossy compression with the compression ratioless than 1:10 have no significant difference with uncompressed data with Kappa coefficient higher than 0.8.
ANALYSIS OF SCENE COMPATIBILITIES FOR MOSAIC OF LANDSAT 8 MULTI-TEMPORAL IMAGES BASED ON RADIOMETRIC PARAMETER Haris Suka Dyatmika; Liana Fibriawati
International Journal of Remote Sensing and Earth Sciences Vol. 13 No. 1 (2016)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2016.v13.a2713

Abstract

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.
THE EFFECT OF JPEG2000 COMPRESSION ON REMOTE SENSING DATA OF DIFFERENT SPATIAL RESOLUTIONS Anis Kamilah Hayati; Haris Suka Dyatmika
International Journal of Remote Sensing and Earth Sciences Vol. 14 No. 2 (2017)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2017.v14.a2724

Abstract

The huge size of remote sensing data implies the information technology infrastructure to store, manage, deliver and process the data itself. To compensate these disadvantages, compressing technique is a possible solution. JPEG2000 compression provide lossless and lossy compression with scalability for lossy compression. As the ratio of lossy compression getshigher, the size of the file reduced but the information loss increased. This paper tries to investigate the JPEG2000 compression effect on remote sensing data of different spatial resolution. Three set of data (Landsat 8, SPOT 6 and Pleiades) processed with five different level of JPEG2000 compression. Each set of data then cropped at a certain area and analyzed using unsupervised classification. To estimate the accuracy, this paper utilized the Mean Square Error (MSE) and the Kappa coefficient agreement. The study shows that compressed scenes using lossless compression have no difference with uncompressed scenes. Furthermore, compressed scenes using lossy compression with the compression ratioless than 1:10 have no significant difference with uncompressed data with Kappa coefficient higher than 0.8.
Co-Authors Anis Kamilah Hayati Anis Kamilah Hayati Liana Fibriawati