Brahmantara, Randy Prima
Remote Sensing Technology and Data Centre - LAPAN, Jakarta, 13710, Indonesia

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SUPERVISED HAZE TRANSFORM METHOD FOR HAZE DETECTION AND REMOVAL IN SPOT 6/7 IMAGERY Sulyantara, D. Heri; Ulfa, Kurnia; Prabowo, Yudhi; Siwi, Sukentyas Estuti; Brahmantara, Randy Prima
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 2 Desember 2018
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (752.426 KB) | DOI: 10.30536/j.pjpdcd.2018.v15.a3060

Abstract

Multispectral satellite images often contaminated by haze and cirrus. It will reduce the accuracy of data interpretation. There are some haze detection and removal methods that have been developed by the experts. However, haze detection and removal still remains become the one of the challenges for optical multispectral data correction. This paper purposed to remove haze on SPOT 6/7 imagery by determining the haze and cloud threshold using the Supervised Haze Transform (SHT). The method is used on hazy SPOT 6/7 imagery. This method is developed based on the reflectance slope of blue and red visible bands by taking the training sample in a clear, a little haze, and lots of haze area of vegetation and bare soil. The vegetation and bare soil in this case are attempted to have the same land cover. Visual comparison is showed by the result of haze detection using manual threshold and mean threshold. The best result haze detection by using the manual threshold. So that, The best result haze detection was the using of manual threshold. So that, the haze removal in  SPOT 6/7 imagery can not be done massifly. Therefore, it is necessary to have an algorithm by inputting the image and corresponding threshold to produce a haze-free image more quickly and efficiently.
Analisis Misalignment Citra Multispektral Terhadap Citra Pankromatik Pada Data Worldview-2 Brahmantara, Randy Prima; Kustiyo, Kustiyo
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 1 Juni 2018
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (428.595 KB) | DOI: 10.30536/j.pjpdcd.2018.v15.a2800

Abstract

The standard data of Worldview-2 owned by LAPAN is Ortho-Ready Standard level 2 (OR2A) data consisting of 4 multispectral bands (blue, green, red, NIR) and one panchromatic band each 2 m and 0,5 m spatial resolution. Both images have different metadata and RPC, making it possible to perform geometric corrections separately. This paper discusses the analysis of the inaccuracies of multispectral image positions to panchromatic images compared to those that have been systematically geometric corrected. The method used is fast fourier transform phase matching by taking 500 binding points between the two images. The measurement results prove that the multispectral image of the Worldview-2 data of the OR2A level has a larger shift compared with multispectral image that has been systematically geometric corrected. The multispectral image of the OR2A data shifts are 2,14 m on the X-axis and 0,42 m on the Y-axis. While the multispectral image that has been systematically geometric corrected shifts are 1,72 m on the X-axis and 0,54 m on the Y-axis.ABSTRAKData standar Worldview-2 yang dimiliki oleh LAPAN merupakan data Ortho-Ready Standard level 2 (OR2A) yang terdiri dari 4 kanal multispektral (biru, hijau, merah, NIR) dan satu kanal pankromatik masing-masing memiliki resolusi spasial 2 meter dan 0,5 meter. Kedua kanal tersebut memiliki metadata dan RPC yang berbeda, sehingga memungkinkan untuk melakukan koreksi geometrik secara terpisah. Tulisan ini membahas tentang analisis misalignment citra multispektral terhadap citra pankromatik dibandingkan dengan yang telah terkoreksi geometrik sistematik. Metode yang digunakan adalah fast fourier transform phase matching dengan mengambil 500 titik ikat antara kedua citra tersebut. Hasil pengukuran membuktikan bahwa citra multispektral data Worldview-2 level OR2A memiliki pergeseran yang lebih besar dibandingkan dengan citra multispektral yang terkoreksi geometrik sistematik. Citra multispektral data OR2A bergeser 2,14 meter pada sumbu X dan 0,42 meter pada sumbu Y. Sedangkan citra multispektral data terkoreksi geometrik sistematik bergeser 1,72 meter pada sumbu X dan 0,54 meter pada sumbu Y.
Geometric Accuracy Assessment of Very High-Resolution Optical Data Orthorectified using TerraSAR-X DSM to Support Disaster Management in Indonesia Sari, Inggit Lolita; Siwi, Sukentyas Estuti; Brahmantara, Randy Prima; Dyatmika, Haris Suka; Suprijanto, Agus; Pradono, Kuncoro Adi
International Journal on Advanced Science, Engineering and Information Technology Vol 8, No 6 (2018)
Publisher : International Journal on Advanced Science, Engineering and Information Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2972.221 KB) | DOI: 10.18517/ijaseit.8.6.7486

Abstract

Advanced remote sensing satellite data with detail spatial resolution can be an alternative to aerial photography and outweigh in providing rapid and vast spatial, remote area, and consist of multispectral bands to produce continues information. The various types of very high spatial resolution satellite, benefit in producing information for large-scale mappings, such as updating an urban map and supporting disaster management for mitigation, preparedness, emergency response, and recovery effectively and efficiently. Large-scale mapping information for disaster management, particularly for quick response is essential to map the impacted sites, measure the number of houses and infrastructure damaged and determine the evacuation area. However, in producing large-scale mapping, the information should refer to the geospatial specification standard, such as accurate geometric, detail thematic information and completeness. This study aims to identify the use of Pleiades imagery for supporting large-scale mapping, including for disaster management by assessing the geometry accuracy from a standard product acquired from the ground station and precise orthorectification using different types of DSM, including TerraSAR-X and improvement using ground control points. The results show that the improved accuracy to meet geometric accuracy standard for scale 1:5000 can be achieved using a primary product data which process using an insertion of GCPs and selecting the better DSM, while for the standard ortho product can be achieved using shifting the coordinate position of the image. Assessment of the thematic extraction visually shows that the imagery meets the information for large-scale mapping, but detail attribution requires information from field data.