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Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Published by Lembaga Penerbangan dan Antariksa Nasional
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 179 Documents
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PENGKAJIAN PEMANFAATAN DATA TERRA-MODIS UNTUK EKSTRAKSI DATA SUHU PERMUKAAN LAHAN (SPL) BERDASARKAN BEBERAPA ALGORITMA Indah Prasasti; Katmoko Ari Sambodo; Ita Carolita
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 4, No.1 Juni (2007)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (251.149 KB)

Abstract

Land surface temperature (LST) is one primary parameters energy balance on the surface and also as primary climatology variable that controlling long-wave energy flux through atmosphere. The LST data is needed for drought estimating models which based on calculating of soil moisture lavel and/or evapotranspiration. TERRA satellite that brings sensor MODIS (Moderate Resolution Imaging Spectroradiometer) is an evironmental. Observation satellite that can be used for extracting LST data regionally. The MODIS relatively has width coverage; 2330 Km, and spatial resolution 250 m (1 and 2 channel) with high spectral resolution (36 channels), and temporal resolution that almost similar to the previous generation satellite called NOAA.
PENERAPAN ALGORITMA SPECTRAL ANGLE MAPPER (SAM) UNTUK KLASIFIKASI LAMUN MENGGUNAKAN CITRA SATELIT WORLDVIEW-2 Nunung Noer Aziizah; Vincentius Paulus Siregar; Syamsul Bahri Agus
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 2 Desember 2016
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (965.047 KB) | 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 WorldView-2 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. AbstrakPemanfaatan teknologi satelit penginderaan jauh (remote sensing) sangat berkembang untuk identifikasi dan memantau sumberdaya alam wilayah pesisir, seperti lamun. Di Indonesia khususnya pemetaan lamun memanfaatkan pustaka spektral dari spektrometer belum banyak dilakukan. Penelitian ini bertujuan untuk mengetahui besaran spektral lamun berdasarkan pengukuran in situ dan analisis citra satelit, memetakan lamun hingga tingkat spesies berdasarkan pustaka spektral pengukuran in situ dengan penerapan algoritma SAM dan menguji tingkat akurasinya. Penelitian dilaksanakan di ekosistem lamun Pulau Tunda, Banten. Citra satelit yang digunakan adalah WorldView-2 dan reflektansi spektral lamun diukur menggunakan spektrometer USB4000. Algoritma klasifikasi SAM memanfaatkan pustaka spektral dan mengkelaskan obyek dalam satu piksel secara homogen. Hasil klasifikasi berupa kelas lamun Enhalus acoroides, Cymodocea rotundata, Thalassia Hemprichi, dan Halophila ovalis. Akurasi yang dihasilkan sebesar 35.6 %. Luas area masing-masing kelas adalah 0.8 Ha untuk kelas Cymodocea rotundata, 2.79 Ha untuk kelas Enhalus acoroides, 3,7 Ha kelas Thalassia hemprichii, dan 3.5 Ha untuk Halophila ovalis. Klasifikasi lamun hingga tingkat spesies belum menghasilkan akurasi yang baik. Area lamun dengan jenis yang beragam dan jumlah saluran pada citra satelit multispektral diasumsikan menjadi penyebab rendahnya nilai akurasi.
PENGEMBANGAN MODEL PENDUGAAN KELENGASAN LAHAN MENGGUNAKAN DATA MODIS Dede Dirgahayu Domiri
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol.3, No.1 Juni (2006)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

This research aims to estimate the land moisture condition of the agricultural land, especially for paddy fields based on MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data with 250 m and 500 m spatial resolution and daily temporal resolution. An index called Land Moisture Index (LMI) is created from 1st principle component result of NDSI (Normalize Difference Soil Index), and NDVI (Normalize Difference Vegetation Index), NDWI (Normalize Difference Water Index). There is a high correlation between the LMI and the soil moisture (LM) for the agricultural land with the soil moisture then more 75%, as the increasing of LM is followed by the increasing of the LMI. Based on the above method, the land moisture can be derived spatially from the agricultural land, and especially on the paddy fields for drought prediction.
DETEKSI LIMBAH ACID SLUDGE MENGGUNAKAN METODE RED EDGE BERBASIS DATA PENGINDERAAN JAUH (DETECTION OF ACID SLUDGE WASTE USING RED EDGE METHOD BASED ON REMOTE SENSING DATA) Nanik Suryo Haryani
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 11 No.2 Desember 2014
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Seiring dengan pertambahan penduduk dan industrialisasi, masalah pencemaran limbah berbahaya dan beracun (B3) semakin meningkat. Peningkatan didorong dengan penanganan tidak bijak baik dari sektor rumah tangga maupun industri. Pemantauan atau deteksi daerah atau zona yang terkena limbah adalah sangat krusial untuk mengetahui daerah mana saja yang masih terkontaminasi limbah B3. Penginderaan jauh merupakan salah satu alat yang dapat digunakan untuk deteksi kegiatan tersebut. Beberapa penelitian telah memanfaatkan data penginderaan jauh untuk mendeteksi lokasi atau daerah terkontaminasi dengan beberapa indek vegetasi, suhu permukaan, maupun indek-indeks lainnya. Penelitian ini mengusulkan metode red edge dari data Landsat TM untuk mendeteksi pencemaran limbah B3 di Pertamina RU-V Balikpapan. Berdasarkan review yang dilakukan bahwa metode red edge potensial untuk mendeteksi limbah B3, dimana dalam hal ini deteksi limbah acid sludge dihubungkan dengan perlakuan pemulihan lahan seperti netralisasi, bioremediasi, solidifikasi  dan pematian acid sludge di daerah yang terkontaminasi dapat dilihat pergeseran spektralnya. Penelitian ini menyimpulkan bahwa berdasarkan pola red edge yang dihasilkan, dapat dilakukan pemantauan kondisi limbah B3 yang sudah mengalami perlakuan atau belum. Kata kunci: Limbah B3, Acid Sludge, red edge, Spektral, Infra merah
PEMANFAATAN DATA MODIS UNTUK IDENTIFIKASI DAERAH BEKAS TERBAKAR (BURNED AREA) BERDASARKAN PERUBAHAN NILAI NDVI DI PROVINSI KALIMANTAN TENGAH TAHUN 2009 - Suwarsono; Fajar Yulianto; - Parwati; Totok Suprapto
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 6, (2009)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Land and forest fire are the natural disasters that often occur in Indonesian regions, especially Sumatera and Kalimantan. The disasters cause deep impacts to environments and human beings, so it is necessary to conduct mitigation. The research area took place in Central Kalimantan Province. The objective of the research is to applicate the MODIS remote sensing imagery for supporting the land and forest fire mitigation efforts, that is identifying the burned area. The analyzing is done by using methods of NDVI changes before and after land and forest burned periods in 2009 . The stages of the research consist of; fire hotspot frequency analyzing, NDVI changes calculation, threshold of NDVI changes establishing, and burned area estimation based on the threshold result. The results of the research show that the burned area in Central Kalimantan can be identified by using MODIS based on NDVI changes. The total numbers of burned area in 2009 are 122.900 hectares, most of them occured in Pulangpisau, Kapuas, Katingan and Kotawaringin District. The results are needed to be verified in the next further research based on the field survey and or by using the high resolution imageries such as Landsat, SPOT-2 or 4, ALOS, Ikonos or Quickbird. Key Words: MODIS, Burned Area, NDVI, Central Kalimantan
Full Paper Inderaja Vol 14 No 1 Juni 2017 Redaksi Jurnal
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 Juni 2017
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Full Paper Inderaja Vol 14 No 1 Juni 2017
PENGEMBANGAN METODE PENDUGAAN KEDALAMAN PERAIRAN DANGKAL MENGGUNAKAN DATA SATELIT SPOT-4 STUDI KASUS: TELUK RATAI, KABUPATEN PESAWARAN (METHODE DEVELOPMENT FOR SHALLOW WATER DEPTH BATHYMETRIC ESTIMATION USING SPOT-4 SATELLITE DATA, A CASE STUDY: RATAI BAY, PESAWARAN DISTRICT) Muchlisin Arief; Maryani Hastuti; Wikanti Asriningrum; Ety Parwati; Syarif Budiman; Teguh Prayogo; Rossi Hamzah
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 10 No. 1 Juni 2013
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (976.22 KB)

Abstract

Pendugaan batimetri perairan dangkal menggunakan data satelit penginderaan jauh semakin umum dilakukan. Namun, ketika metode tersebut diimplementasikan untuk wilayah dengan lingkungan yang berbeda, maka hasilnya menunjukkan adanya penyimpangan. Untuk meminimalkan penyimpangan tersebut, maka dilakukan penggabungan informasi diperoleh dari pengukuran lapangan dengan nilai reflektansi citra satelit SPOT-4. Pada makalah ini diusulkan pengembangan metode pendugaan kedalaman perairan didasarkan pada fungsi korelasi antara nilai kedalaman dari hasil pengukuran langsung menggunakan alat “handheld echo-sounder” dengan penjumlahan resultante nilai reflektansi (band1 dan band3). Algorithma pendugaan batimetri di perairan dangkal di Teluk Ratai terdiri dari metode thresholding dan fungsi korelasi. Nilai threshold (T) untuk kedalaman 0.5 meter ditentukan dari pengamatan grafik fungsi korelasi polynomial ordre lima dan besarnya adalah 0.35
RANCANG BANGUN SISTEM PENYEDIA DATA HiRID MTSAT-1R - Suhermanto
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 5, (2008)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

On the transition of operational Geostationary Meteorological Satellite GMS-5 to MTSAT-1R, HiRID’s data packet was introduced. HiRID uses the same frame as of the S-VISSR, with some modifications to accommodate the additional information because of performance improvement of its data imaging system. Performance improvement of instrument is associated with addition of IR4 channel and radiometric resolution improvement of infrared channel to 10 bits/ pixel. The operating lifetime of HiRID as transition data packet to the MTSAT-1R HRIT is limited in the view of giving a grace period to the Earth station operators to upgrade the receiving systems towards HRIT operationalization. This paper reviews the efforts to obtain MTSAT-1R HiRID data and adjustments made in the sub-receiver systems, sub-system of data pre-processing. The discussion includes a glance of RF system integration, data extraction techniques and information extraction of documentation sector, focusing the discussion on the different of structures of HiRID data packets and S-VISSR as well as techniques that are applied to extract image data and any information contained therein. Keyword:S-VISSR, HiRID, Sub-commutation, Decomposition
Front Pages Inderaja Vol. 14 No. 1 Juni 2017 Redaksi Jurnal
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 Juni 2017
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Front Pages Inderaja Vol. 14 No. 1 Juni 2017
PENGKAJIAN NILAI VEGETASI DATA MODIS DENGAN MENERAPKAN BEBERAPA ALGORITMA PENGOLAHAN DATA INDEKS VEGETASI Indah Prasati
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 1, No.1 Juni (2004)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.726 KB)

Abstract

The vegetation index (VI) that is extracted from MODIS data using several algorithms still needs to develop and to study. It is due to MODIS (Moderate Resolution Imaging Spectroradiometer) data that is relatively new in the operation and data application. The study aims to compare sensitivity application of 3 algorithms for extraction of vegetation index data. The simulation in this research is using MODIS data level 1B with all resolution (250m, 500m, and 1000m) for Kalimantan Island dated May 17, 2002 by applying NDVI algorithm (Normalized Difference Vegetation Index), SAVI (Soil Adjusted Vegetation Index),and SARVI (Soil and Atmosphere Resistant Vegetation Index). The result of this research shows that the application of SAVI and SARVI algorithms in cloud-dominated location will have higher vegetation index value as much as 0.001 - 0.04 unit with SAVI model, if compared with SAVI and can be higher or lower compared with SARVI value, depending on the condition of how much influential factor of atmospheric water vapor, aerosol content and canopy background that can be reduced and corrected by applying the SARVI model. In the meanwhile, in urban area, the applying of SAVI model will be lower as much as 0.14-0.15 unit, and about 0.1-0.15 unit with SARVI model if compared with NDVI.

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