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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
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Search results for , issue "Vol. 12 No. 1 (2015)" : 5 Documents clear
PEMETAAN ZONA GEOMORFOLOGI EKOSISTEM TERUMBU KARANG MENGGUNAKAN METODE OBIA, STUDI KASUS DI PULAU PARI Anggoro, Ari; Siregar, Vincentius P.; Agus, Syamsul B.
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 1 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i1.3306

Abstract

This study used object-based image analysis (OBIA) for geomorphic zones map of coral reef ecosystem in Pari Islands. The application of OBIA methods was used multiresolution segmentation algorithm with different scale parameter for each level. Classification methods for level 1 and 2 were used contextual editing classification. The results showed an overall accuracy for level 1 was 97% (reef level) and level 2 was 87% (geomorphic zone). Thus OBIA methods can be used and well-defined as an alternative for geomorphic zones map in other regions.
KLASIFIKASI DAERAH TERCEMAR LIMBAH ACID SLUDGE MENGGUNAKAN METODE SPECTRAL MIXTURE ANALYSIS BERBASIS DATA LANDSAT 8 Haryani, Nanik Suryo; Sulma, Sayidah; Pasaribu, Junita Monika; Fitriana, Hana Listi
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 1 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i1.3307

Abstract

The existence waste materials in an area potentially triggers the contamination, and in turns will damages the environment particularly in the vicinity of waste disposal location. This research is aimed to analyze the acid sludge waste contaminated area using the remote sensing satellite Landsat 8. The applied methodology for analyzing the spectral of contaminated area is using spectral mixture analysis method. The result shows that the spectral analysis using this method with spectral reference based on endmember images convey the better output. This is caused by the availability of the SWIR wave length in Landsat 8. The SWIR wave length is sensitive against a highly contaminated substance like as sand and sludge, and contributes to non land contaminated substance like vegetation. Further the index classification based on images endmember shows the result which matching better to the field condition. Based on accuracy review, the result shows the classification accuracy based on this index as 62.5 %.
PENGUJIAN MODEL PENDEKATAN PROBABILITAS BERBASIS PERUBAHAN PENUTUP LAHAN CITA LANDSAT TUNGGAL MULTIWAKTU UNTUK PEMETAAN LAHAN SAWAH Parsa, I Made
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 1 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i1.3308

Abstract

Tests on a model of probability approach to paddy field mapping based on land cover changes that has been done in several districts in West Java showed overall accuracy an average only 65.5%. It is thought to be related to the use of annual multitemporal Landsat mosaic results so often seem illogical because the image is derived from some of the data obtained at different seasons. In this regard has been done phase II trial of the model using multitemporal Landsat-8 singles data (not mosaic data). The objective of this research is to test the validity of the probability model on multitemporal land cover changes for rice field mapping. The method used in this trial is unsupervised classification methods for mapping multitemporal land cover. Merging multitemporal land cover change in the timeframe in accordance with the date of acquisition date. Analysis of probability as a rice field area, where if two of the land cover types were detected, bare land or otherwise classified as land with probability 1, if only observed one land cover change, bare land becomes water, water or bare land is classified as a probability of 0.3. Accuracy tests using confusion matrix between the field probability image and rice field reference level 1: 5,000. The evaluation results show that the rice field probability image reached 79.7% with lowest accuracy 67.7% (Babelan Sub-districts) and the highest 86.7% (Sukamandi Sub-districts). Comparison of results with previous results showed a high significant difference with an average increase of more than 600% accuracy. Based on these results it can concluded that the probability model based on multitemporal land cover changes for rice field mapping has good accuracy.
PENDETEKSIAN POTENSI CADANGAN KARBON DI ATAS PERMUKAAN PADA HUTAN MANGROVE DI KUBU RAYA MENGGUNAKAN CITRA ALOS PALSAR Hudaya, Yudi Fatwa; Hartono, Hartono; Murti, Sigit Heru; Hadiyan, Yayan
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 1 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i1.3309

Abstract

The need for sufficient forest carbon stock measurement system which encompasses a faster and covering broader geographic area is now growing, one of which is the use of synthetic aperture radar (SAR). The objectives of this study were to demonstrate the advantage of ALOS PALSAR application for carbon quantification in mangroves, which apparently provided better relationship in between the L-band backscatters of ALOS PALSAR and the actual aboveground allometric based forest carbon stock of mangroves, compared with previous studies in other types of forest. i.e in tropics or temperate lowland until mountain forests. The better relationship explained by the coefficient determination (R²) of 62 % based on HH polarization with the equation model of Y = 1647.20 + 6.8288BS_HV + 279.48BS_HV + 2870. While previous studies mentioned the R² were only 16 - 76%. The models obtained subsequently were subjected to total carbon quantification and their distributions were mapped. The quantity of aboveground biomass of mangrove forest in Kubu Raya Regency was (Mega grams) or 5.3 Mt (Mega grams), the quantity of carbon dioxide (CO2) sequestration reached 19 451 Mt (Megagrams) equivalent. The 71,069.21 ha area of mangrove forest has the potential to reduce the rate of GHG (Green House Gas) emissions from forestry sector by 0.76%.
ANALISIS PEMANFAATAN DAN VALIDASI HOTSPOT VIIRS NIGHTFIRE UNTUK IDENTIFIKASI KEBAKARAN HUTAN DAN LAHAN DI INDONESIA Zubaidah, Any; Vetrita, Yenni; Priyatna, M.; Ayu D., Kusumaning
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 1 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i1.3310

Abstract

Suomi National Polar-Orbiting Partnership (Suomi NPP) that was launched on 28 October 2011 was a new generation of weather satellites of NASA. It has been continuing to develop algorithms for environmental monitoring applications including fire hotspot which is a global product. Therefore, an evaluation for the specific region is necessary. This paper is aimed to validate the VIIRS Nightfire (VNF) in Indonesia, particularly in Riau Province. MODIS fire hotspot (MOD 14) nighttime was used as well as a comparison. Statistical analysis was performed to calculate the precise location of hotspots at 1 and 2 km radius buffering of the detected fire. A field survey and SPOT 5 imagery which has a higher spatial resolution. Accuracy was calculated from them all the hotspots were detected in a period of 3 weeks which is adapted to the availability of SPOT 5 imagery, by considering the analysis of single and dissolve buffering. The result shows that VNF has an average accuracy rate of 84.31%. This result can be compared with the analysis of the MODIS hotspots product. Thus, VNF was very significant to be used along with MODIS hotspots, in particular for monitoring land/ forest fires at night.

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