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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 6 Documents
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Search results for , issue "Vol. 16 No. 1 (2019)" : 6 Documents clear
PENGARUH TINGGI MUKA AIR GAMBUT SEBAGAI INDIKATOR PERINGATAN DINI BAHAYA KEBAKARAN DI SUNGAI JANGKANG - SUNGAI LIONG Febrianti, Nur; Murtilaksono, Kukuh; Barus, Baba
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.v16i1.3346

Abstract

Disasters of forest and land fires are increasingly concerned. The nature of peat soil which is easy to lose water and high organic matter content causes peat soils to be very sensitive to fire. Therefore it is necessary to know indicators for early warning of fires on peatlands. The purpose of this study is to determine the critical groundwater level (GWL) as an indicator of peatland fires on the Jangkang River - Sungai Liong. Determination of the critical point of peatland fires as a fire early warning is done by calculating the difference from the value of the undefined TMA with a range of possible errors. The TMA value is obtained from the estimation of several methods, namely data on the physical properties of the soil, the drought index, and a combination of both. The TMA estimation of the physical properties of the soil has a range of fires at depths of 74.3 - 107 cm. In estimating TMA using a drought index, potential fires occur in TMA ranging from 27 - 101 cm. While the combined estimates of the physical properties of the soil and the drought index ranged from 66.8 - 98.8 cm the occurrence of fires on peatland. The results of this study show that the estimated TMA from a combination of field data and drought index provides fairly good accuracy. Thus TMA can be an early warning indicator of the danger of peatland fires. This TMA estimation can give faster results and pretty good accuracy. But this estimation model for TMA does not necessarily apply directly to other research locations. The critical point of peat soil water depth ranges from 27 to 74 cm. The depth of the peatland surface should be maintained less than the critical point, if not then the potential for peatland fires will increase.
ANALISIS PENINGKATAN KUALITAS GEOMETRI DENGAN MENGGUNAKAN TITIK IKAT BUNDLE ADJUSTMENT (STUDI KASUS DATA PLEIADES WILAYAH KABUPATEN MADIUN DAN KABUPATEN MAGETAN) Sari, Inggit Lolita; Brahmantara, Randy Prima
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.v16i1.3347

Abstract

Recently, the utilization of very high spatial resolution data such as Pleaides has reached at a high demand. Particularly to support disaster mitigation, where automation and fast image processing are necessary and unavoidable. Pleiades imagery has been acquired at LAPAN ground station starting in 2018. This study examines the improvement of the Pleiades images geometry accuracy processed using the bundle adjustment (BA) method in order to support image mosaicking where case study is located in the Madiun regency and the Magetan regency. This method uses parameters to relate the geometry between scenes by using tie points. These points are located in the intersection area between scenes. Geometry quality assessment of the imagery produced using BA correction are measured by comparing between the coordinate of the imagery and the coordinates obtained from the field measurement. The assessment shows that BA geometry correction has improved the geometry quality of the images which nearly similar to the field measurement and achieved a better geometry accuracy compare to the images processed without BA method.
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.
PENGEMBANGAN METODE KLASIFIKASI LAHAN SAWAH BERBASIS INDEKS CITRA LANDSAT MULTIWAKTU Parsa, Made; Dirgahayu, Dede; Harini, Sri
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.v16i1.3349

Abstract

Research on the development of a paddy field classification model based on Landsat remote sensing images aims to obtain a rapid classification of paddy field models. This study uses input multitemporal Landsat images (path/row 122/064) in 2017. The research was conducted in Subang regency, which is one of the center of West Java rice production. The method used in this study is the threshold method for the multi-temporal Landsat image index. As a reference, detailed scale spatial information on paddy fields base is used which is supplemented with data from field surveys using drones. First, an atmospheric correction of Landsat images was carried out using DOS (Dark Object Subtraction) Method, then transformation image to several indices: Enhance vegetation Index (EVI), Normal Difference Water Index (NDWI), and Normal Difference bare Index (NDBI) was carried out. For cloudy images, the index is filled with interpolation techniques from the index value before and after. The next step is smoothing index and statistical analysis to obtain minimum, maximum, mean, median, range (maximum - minimum), EVI_planting, EVI_harvesting, mean_planting-harvesting, mean_vegetative, mean_generative, NDWI_planting, NDWI_harvesting, NDBI_planting, and NDBI_harvesting. Classification accuracy is calculated by using the confusion matrix technique using detailed scale spatial information references. Based on the analysis and test of accuracy that has been done on several models, the highest accuracy is generated by the 1.5 stdev threshold model four index parameters (EVI_min, EVI_Max, EVI_range, and EVI_mean) with an accuracy of 86.56% and a kappa value of 0.716.
Pengembangan Tiling database untuk Penyimpanan Data Penginderaan Jauh pada Pembangunan LAPAN Engine Widipaminto, Ayom; Safitri, Yuvita Dian; Sunarmodo, Wismu; 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.v16i1.3350

Abstract

Remote sensing image data is included in the unstructured data category which is characterized by large volumes of data and is regularly updated. Special techniques are needed in large capacity data storage and supported by high-capacity data processing machines. This study aims to find a design representation of remote sensing image data that is more efficient in storage and processing than conventional methods. The design proposed is with the concept of tiling databases, namely the method of breaking down image data into small size pieces with certain identities and then entering them into a database. The test results compared to the conventional method found that the storage volume can be reduced by up to 25%, the speed of reading the data also increases by about 21%. This system can support the development of LAPAN Engine because it offers a storage strategy that is more effective in terms of volume, and efficient in terms of the speed of reading data even though the tiling process into the database takes pretty long time.
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.

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