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Lalu Muhamad Jaelani
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Department of Geomatics Engineering, Faculty of Civil, Planning, and Geo-engineering; Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia. Phone 031-5929486, 031-5929487
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Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 14128098     EISSN : 2549726X     DOI : https://doi.org/10.12962/inderaja
Core Subject : Science, Agriculture, Engineering,
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital (the Journal of Remote Sensing and Digital Image Processing) is a scientific journal dedicated to publishing research and development in technology, data, and the utilization of remote sensing. The journal encompasses the scope of remote sensing as outlined in Law No. 21 of 2013 on Space Affairs, which includes: (1) data acquisition; (2) data processing; (3) data storage and distribution; (4) utilization and dissemination of information. The journal was first published by the Indonesian National Institute of Aeronautics and Space (LAPAN) in June 2004 and received its initial accreditation as a "B" Accredited Scientific Periodical Magazine from LIPI in 2012. In 2015, the journal successfully maintained its "B" Accredited status. From 2018 to 2021, the journal was accredited as SINTA 2 with certificate number 21/E/KPT/2018. Starting from March 2025, the journal has been managed by the Institut Teknologi Sepuluh Nopember (ITS), in collaboration with the Geoinformatics Research Center of BRIN and the Indonesian Society for Remote Sensing (ISRS/MAPIN). The journal encompasses the scope of remote sensing as outlined in Law No. 21 of 2013 on Space Affairs, which includes: data acquisition; data processing; data storage and distribution; utilization and dissemination of information.
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Ilmu Bumi dan Planet (Lain-Lain)
Articles 4 Documents
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Search results for , issue "Vol. 13 No. 1 (2016)" : 4 Documents clear
IDENTIFIKASI STRUKTUR GEOLOGI DAN PENGARUHNYA TERHADAP SUHU PERMUKAAN TANAH BERDASARKAN DATA LANDSAT 8 DI LAPANGAN PANASBUMI BLAWAN Azhari, Anjar Pranggawan; Maryanto, Sukir; Rachmansyah, Arief
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 1 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v13i1.3316

Abstract

This paper presents the use of remote sensing methods for identifying geological structures on the Blawan-Ijen geothermal field and its system. Remote sensing data, specifically Landsat 8 and DEM SRTM, were utilized to extract lineaments from the 753 multispectral band and derive land surface temperature (LST) from a single thermal infrared band using a retrieval method. Surface emissivity was determined based on the Normalized Difference Vegetation Index (NDVI) of the study area. Remote sensing analysis proved to be an effective approach for identifying geological structures from the surface that control thermal manifestations in the Blawan geothermal field. The results indicate that the Blawan fault is the primary structure in the geothermal field, associated with high LST and hot springs. Interpretation suggests that the reservoir of the Blawan-Ijen geothermal system extends from Plalangan to the southwest area.
ANALISIS TEMPERATUR DAN UAP AIR BERBASIS SATELIT TERRA/AQUA (MODIS, LEVEL-2) Sipayung, Sinta Berliana; Krismianto, Krismianto; Risyanto, Risyanto
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 1 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v13i1.3317

Abstract

Terra and Aqua satellites that consist of multiple sensors including MODIS instruments, which is operated to detect the phenomena that exist on land, sea and atmosphere. Not a lot of data extracted especially for Indonesia region the associated with atmospheric data, because the product is still in the raw data (level-0). For data extraction of level-0 to level-2 needed software IMAPP (International MODIS/airs Processing Package) so displays some data atmospheric parameters including MOD 04 - Aerosol, MOD 05 - Total precipitable Water (Water Vapor), MOD 06 - Cloud, MOD 07 - Atmospheric Profiles, MOD 08 - gridded Atmospheric and MOD 35 in HDF4 format (Hierarchical Data Format-4) swath. This paper discussed only MOD07/MYD07 atmospheric profiles level-2 related parameters such as the temperature of the atmosphere at an altitude of 780 hPa and water vapor at a height of 700 hPa. This study aimed to analyze the phenomena in the atmosphere, based on extraction method Atmospheric Profiles in the resolution 1km, that consists of temperature and moisture level 2, in the format hdf4 daily swath into data daily and monthly grid in .dat format, in the period of December 2014, January, July, and August 2015, especially in the area of Indonesia. The comparison between the results of the extraction swath and grid data from Terra/Aqua MODIS, that parameter atmospheric for the temperature has R-sqare an average of 0.72 and water vapor 0.74, while the RMSE temperature and water vapor are 0.88 and 0.29.
PERBANDINGAN HASIL KLASIFIKASI LIMBAH LUMPUR ASAM DENGAN METODE SPECTRAL ANGLE MAPPER DAN SPECTRAL MIXTURE ANALYSIS BERDASARKAN CITRA LANDSAT - 8 Sulma, Sayidah; Pasaribu, Junita Monika; Fitriana, Hana Listi; Haryani, Nanik Suryo
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 1 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v13i1.3318

Abstract

The utilization of remote sensing data is an alternative way that could be used for rapid detection of large coverage hazardous waste area. This study aims to classify the acid sludge contaminated area using Landsat 8 by applying Spectral Angle Mapper (SAM) classification method with two spectral reference sources, namely field spectral measurement using a spectrometer and endmember spectral from the image, and then compare the classification results. The accuracy level of SAM classification result showed that classification using endmember spectral from the image as the reference spectral reached 66,7%, whereas classification using field spectral measurement as spectral reference only reached 33,3%. The accuracy level of Spectral Mixture Analysis (SMA) classification result showed that classification using endmember spectral from the image as the reference spectral reached 62,5%. The affecting factors for the low accuracy is the significant differences of the spectral profiles obtained from spectrometer with spectral Landsat-8 due to differences of spatial and altitude.
PERBANDINGAN METODE KLASIFIKASI PENUTUP LAHAN BERBASIS PIKSEL DAN BERBASIS OBYEK MENGGUNAKAN DATA PiSAR-L2 Manalu, R. Johannes; Sutanto, Ahmad; Trisakti, Bambang
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 1 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v13i1.3319

Abstract

PiSAR-L2 program is an experimental program for PALSAR-2 sensor installed on ALOS-2. Research collaboration had been conducted between the Japan Aerospace Exploration Agency (JAXA) and Ministry for Research and Technology of Indonesia in 2012 to assess the ability of PiSAR-L2 data for some applications. This paper explores the utilization of PiSAR-L2 data for land cover classification in forest area using pixel-based and object-based methods, then carried out comparison between the two methods. PiSAR-L2 data full polarization with 2.1 level for Riau province was used. Field data conducted by JAXA team and landcover map from WWF were used as references to collect input and evaluation sample. Pre-processing was done by doing backscatter conversion and filtering, then classification was conducted and it’s accuracy was tested. Two methods were used, 1) Maximum Likelihood Enhance Neighbor classifier for pixel-based and 2) Support Vector Machine for object based classification. The effect of spatial resolution on classification result was also analyzed. The results show that pixel-based produced mixed pixels "salt and pepper", the classification accuracies were 62% for 2.5 m and 83% for 10 m spatial resolution. While the object-based has some advantages: high homogeneity (absence of mixed pixels), clear and sharp boundary among classes, and high accuracy (97% for 10 m spatial resolution), although it was still found errors in some classes.

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