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All Journal Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Andy Indradjad, Andy
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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PENGOLAHAN GEOLOKASI PRODUK DATA GAS RUMAH KACA (GRK) DARI SATELIT SUOMI NPP ATMS DAN CRIS DENGAN METODE INTERPOLASI RADIAL BASIS FUNCTION Indradjad, Andy; Dyatmika, Haris Suka; Salyasari, Noriandini Dewi; Fibriawati, Liana; Indriani, Masnita
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 1 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2018.v15.a2798

Abstract

Geolocation processing to produce spatial greenhouse gases data products consisting of CH4, CO2 and N20 gases has been carried out systematically. The greenhouse gases data are derived from Enviomental Data Record (EDR) Suomi NPP Satellite CrIS and ATMS Sensor products. During this process, there is an obstacle while performing the information data of greenhouse gases concentrations, due to the result of systematic processing files from EDR are still in netcdf format, so that it could not be distributed to users as they expected. The unique of unlimited netcdf format is that, it displays only numeric values with irregular resolution, unregistered and incompatible with commonly processing data software. This research aims to produce geolocation processing module in order to provide information of greenhouse gases data spatially by using coordinate pixel registration method into image data, convert Digital Number (DN) value with scale corresponding to Indonesian region and interpolation value between pixels with Radial Basis Function (RBF) method using linear function. The result from the geolocation processing module of greenhouse gases data product are concentration information from some altitude level. The product is in geotiff format with 50 km spasial resolusion.
ANALISIS METODE KOMPRESI BERDOMAIN WAVELET PADA CITRA SATELIT RESOLUSI SANGAT TINGGI Widipaminto, Ayom; Indradjad, Andy; Monica, Donna; Rokhmatullah, Rokhmatullah
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 16 No. 1 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v16i1.3348

Abstract

A problem that often arises in remote sensing images, especially very high-resolution images, is the large storage and bandwidth needed to transmit those images. On satellite images processing, a compression needs to be done on those satellites images to make it easier in terms of transmission and storage. This paper compare several wavelet-domain methods namely wavelet method, bandelet method, and CCSDS to find the best method to compress the very high-resolution satellites imageries Pleiades. Experiment results show that the method wavelet and bandelet is better in preserving the images quality with around 50 dB PSNR, while CCSDS is better in reducting the image size to the eighth of original image.
ANALISIS TINGKAT AKURASI TITIK HOTSPOT DARI S-NPP VIIRS DAN TERRA/AQUA MODIS TERHADAP KEJADIAN KEBAKARAN Indradjad, Andy; Purwanto, Judin; Sunarmodo, Wismu
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 16 No. 1 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v16i1.3351

Abstract

Accuracy analysis of the forest fire detection by using remote sensing data hotspots from SNPP and TERRA/AQUA has been carried out. The sensors used were MODIS sensors for TERRA/AQUA satellites and VIIRS sensors for S-NPP satellites. The detection of hotspots from remote sensing satellite data can be used as an early warning of forest fires. Hotspot can be derived from 2 sensors, namely MODIS and VIIRS sensors using algorithms that have been developed by science team from satellite developer. This hotspot information need to be accurately analysis by ground thruth of the fire events. This aims to analize the accuracy of hotspot information detection for forest fires. By comparing fire event data in 2018 and hotspot information data on hotspot databases owned by LAPAN. The results show that MODIS sensors are 39% and for VIIRS sensors are 20%. That result using 2 km of buffer radius which is the most significant result comparing others. It is clearly indicates that improvements are needed to improve the accuracy of hotspot derived from VIIRS data.
Co-Authors Ayom Widipaminto, Ayom Haris Suka Dyatmika, Haris Suka Indriani, Masnita Judin Purwanto, Judin Liana Fibriawati, Liana Monica, Donna Noriandini Dewi Salyasari, Noriandini Dewi Rokhmatullah, Rokhmatullah Wismu Sunarmodo, Wismu