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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 5 Documents
 1 
Search results for , issue "Vol. 13 No. 2 (2016)" : 5 Documents clear
PENERAPAN ALGORITMA SPECTRAL ANGLE MAPPER (SAM) UNTUK KLASIFIKASI LAMUN MENGGUNAKAN CITRA SATELIT WORLDVIEW-2 Aziizah, Nunung Noer; Siregar, Vincentius Paulus; Agus, Syamsul Bahri
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 2 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2016.v13.a2205

Abstract

Remote sensing technology has been developed for monitoring and identification of coastal environment and resources, such as seagrasses. In Indonesia, particularly seagrass mapping spectrometer utilizing spectral library has not been done. This study aimed to determine the spectral signature based in situ measurement and image analysis, analyze the implementation of the algorithm Spectral Angle Mapper (SAM) and test accuracy in mapping seagrass to species level based on spectral libraries. Research conducted in seagrass Tunda Island, Banten. Satellite imagery used is WorldView2 and the seagrass spectral reflectance was measured using a spectrometer USB4000. SAM classification algorithm utilizing spectral libraries and classify objects in a single pixel can be homogeneous. Classification results in the form of class Enhalus acoroides, Cymodocea rotundata, Thalassia hemprichii, and Halophila ovalis. The resulting accuracy of 35.6%. The area of each class is 0.8 hectares for the class Cymodocea rotundata, 2.79 hectares for Enhalus acoroides, class Thalassia hemprichii 3.7 hectares, and 3.5 hectares for Halophila ovalis. Classification of seagrass to species level yet produce good accuracy. Seagrass area with a variety of species and number of channels on a multispectral satellite image is assumed to be the cause of the low value of accuracy.
MODEL PELAKSANAAN DISEMINASI INFORMASI PENGINDERAAN JAUH BERBASIS TEKNOLOGI TERBUKA Sarno, Sarno
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 2 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2016.v13.a2515

Abstract

National Earth Observation System at the Remote Sensing Application Center organize the functions of remote sensing information dissemination to the user. Space Law Number 21 of 2013 Article 22, Paragraph 1, mandates that the use of data and dissemination of remote sensing information shall be based on the guidelines set by the Institution. This research aims to analyze reference implementation of remote sensing information dissemination. The method used in this study is prototyping with an open technology. Stages of research include the identification of technology components and evaluation of the general architecture to simplify the development, design models and implementation of the system by reforming, repeatedly testing and integration of open source software. The results showed that the model or reference implementation has been successfully implemented and tested through prototypes. Application of the prototype into a fully operational system can be developed at low cost and user friendly interface.
KLASIFIKASI PENUTUP/PENGGUNAAN LAHAN DENGAN DATA SATELIT PENGINDERAAN JAUH HIPERSPEKTRAL (HYPERION) MENGGUNAKAN METODE NEURAL NETWORK TIRUAN Kushardono, Dony
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 2 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2016.v13.a2516

Abstract

Hyperspectral remote sensing data has numerous spectral information for the land-use/landcover (LULC) classification, but a large number of hyperspectral band data is becoming a problem in the LULC classification. This research proposes the use of the back propagation neural network for LULC classification with hyperspectral remote sensing data. Neural network used in this study is three layers, in which to test input layer has a number of neurons as many as 242 to process all band data, 163 neurons, and 50 neurons to process the data band has a high average digital number, and data bands at wavelengths of visible to near infrared. The results showed the use of all the data band hyperspectral on classification with the neural network has the highest classification accuracy of up to 98% for 18 LULC class, but it takes a very long time. Selecting a number of bands of precise data for classification with a neural network, in addition to speeding up data processing time, can also provide sufficient accuracy classification results.
METODE PENENTUAN TITIK KOORDINAT ZONA POTENSI PENANGKAPAN IKAN PELAGIS BERDASARKAN HASIL DETEKSI TERMAL FRONT SUHU PERMUKAAN LAUT Hamzah, Rossi; Prayogo, Teguh; Marpaung, Sartono
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 2 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2016.v13.a2364

Abstract

Information points coordinate of potential fishing zones (PFZ) is required by user that to be more effective in conducting fishing operation. The results of thermal front detection using single image edge detection (SIED) as shape contour lines. This research aims to determine points coordinate for potential fishing zone based on detection of thermal fronts sea surface temperatures. To determine point coordinate performed segmentation on detection result according to size fishnet grid. Contour line contained in each grid is a polygon shape. Centroid of each polygon is point coordinate of PFZ. The result of sea surface temperature data processing from Terra/Aqua MODIS and Suomi NPP VIIRS satellite indicates that method of determination the centroid of polygon is very effective in determining the point coordinate of PFZ. Using that method the processing stages of satellite data to be faster, more efficient and practical due to the information of PFZ is already as points coordinate.
ALGORITMA DUA DIMENSI UNTUK ESTIMASI MUATAN PADATAN TERSUSPENSI MENGGUNAKAN DATA SATELIT LANDSAT-8, STUDI KASUS: TELUK LAMPUNG Arief, Muchlisin; Adawiah, Syifa W.; Hartuti, Maryani; Parwati, Ety
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 2 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2016.v13.a2517

Abstract

Remote sensing technique is a powerful tool for monitoring the coastal zone. Optical sensors can be used to measure water quality parameters Total Suspended Matter (MPT). In order to be able to extract information MPT, the satellite data need to be validated with in situ measurements that make the relationship between the reflectance band with concentration MPT measurement results. In this model, do the correlation between the measurement results with the reflectance values band 3 and band 4. then obtained a linear equation, then calculated using the argument of a ratio of 60:75 to each of the correlation coefficient, the obtained linear equation two Dimension T (X3, X4) = 2313.77 X3 + 4741.11 X4 + 314.95. Based on the concentration MPT of dated June 3, 2015 was lower than in the west to the east. this is because the east is already contaminated with the plant, effluent solids by humans, while the west for still many floating net fish, and mangrove. Based on the results of measurement and calculation results, is still far from perfect (accuracy 60%), one factor is the value thresholding, when determining the boundary between: clouds, sea, and land. Generally indicates that the model is still in need for repair.

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