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INDONESIA
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 9 Documents
 1 
Search results for , issue "Vol. 17 Nr. 2 Desember 2020" : 9 Documents clear
METODE PEMANTAUAN EKSPLOITASI DAN REKLAMASI TAMBANG BATUBARA MENGGUNAKAN DATA SENTINEL-2 Samsul Arifin
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3323

Abstract

Abstract: Mining is an activity of extracting non-renewable natural resources, including coal. Mining cannot be separated from the aspect of the company, because the principle has the aim to be utilized to the community in meeting their needs. In realizing this mining activities must be optimally managed and utilized for the present and future. Monitoring and supervision of mining activities effectively and efficiently can be used technology that has data with wide scope and availability on an ongoing basis. Remote sensing technology has the capability above requirements used are Sentinel-2. Sentinel-2 has adequate spectral, spatial and temporal resolution. The purpose of this study was to develop a monitoring model for coal mine exploitation using Sentinel-2 data. Detection of geobiophysical parameters is a model for extracting changes in the earth's surface due to mining activities. Processing techniques and formulas that can be used to identify and monitor the phenomenon of changes in the earth's surface include the Normalized Difference Vegetation Index and Normalized Burn Ratio.
INTEGRASI READY DATA DAN PENGINDERAAN JAUH BERBASIS SIG UNTUK ANALISIS CEPAT PENILAIAN RISIKO BANJIR DI KECAMATAN SEMANU, GUNUNGKIDUL Kanita Shinta Wati; Sudaryatno Sudaryatno
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3383

Abstract

The high number of flood events in Indonesia is influenced by weather influences such as the tropical cyclone Cempaka on 27-29 November 2017. The incident caused disasters in 28 regencies / cities in Java. Semanu District is one of the areas in Gunungkidul Regency which was affected by tropical cyclones and submerged several residents' houses to a height of 2.7 meters. Therefore, information is needed related to the risk of flooding in Semanu District. This study has three objectives, namely to obtain and collect data related to flood disasters in Semanu District, compile detailed scale scale disaster risk mapping databases in Semanu District, and map flood disaster risk in Semanu District.The SPOT 7 image, DEM Alos Palsar, and secondary data are used for the components making up the flood threat component. The amount of data used in research requires the compilation of an appropriate database to make it easier to access data that has been collected and will be processed using spatial analysis based on GIS. Disaster risk mapping is carried out taking into account the threat, vulnerability and capacity factors that produce three classes of flood risk, namely low, medium and high risk. Making a Map of Land Use as basic information for the process of flood hazard analysis has an accuracy of 94.29%.The results of this study in general the Semanu District has three flood risk classes. The "high risk" class is 5988.86 Ha, the "moderate risk" is 2407.08 Ha, and the "low risk" class is 1803.88 Ha. The area that has the greatest risk of flooding is Pacarejo Village, which is located west of Semanu District. While the other areas that need to be watched out are Semanu Village and a number of small areas scattered in Candirejo, Dadapayu and Ngeposari Villages.
MODIFIKASI MODEL FOREST CANOPY DENSITY (FCD) PADA CITRA LANDSAT 8 MULTI-TEMPORAL UNTUK MONITORING PERUBAHAN TUTUPAN VEGETASI DI KECAMATAN SUKASADA-BALI A Sediyo Adi Nugraha; I Putu Ananda Citra
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3380

Abstract

Modifikasi model Forest Canopy Density (FCD) bertujuan untuk mengetahui seberapa besar peningkatan akurasi pada model FCD. Perubahan modifikasi model FCD dilakukan secara temporal pada tahun 2014 sampai tahun 2019 di Kecamatan Sukasada. Perubahan dilakukan pada indeks vegetasi dengan Soil Adjusted Vegetation Index (SAVI) dan indeks thermal dengan metode Split-Windows Algorithm (SWA). Modifikasi tersebut perlu dilakukan karena modifikasi model FCD sebelumnya berupa pengurangan penggunaan indikator. Berdasarkan hasil modifikasi model FCD yang dilakukan membuktikan model FCD SAVI memiliki akurasi sebesar 83.67% dan model FCD original sebesar 84%. Sedangkan penggunaan SWA pada model FCD memiliki kondisi konsisten sehingga dapat dinyatakan bahwa SWA mampu menyesuaikan terhadap modifikasi model FCD. Secara temporal (2014 – 2019) menunjukkan perubahan tutupan vegetasi tinggi menjadi tutupan vegetasi sedang sebesar 1115.28 Hektare. Disimpulkan bahwa model FCD SAVI memiliki perbedaan sebesar 0,33% dibandingkan model FCD aslinya. Hal ini dipengaruhi oleh kondisi variasi topografi wilayah yang menyebabkan efek bayangan.
PREDIKSI POLA PERSEBARAN TUMPAHAN MINYAK MENGGUNAKAN DATA CITRA SATELIT SENTINEL-1 DI PERAIRAN BINTAN, KEPULAUAN RIAU Tirsa Aulia Puspitasari; Mochamad Arif Zainul Fuad; Ety Parwati
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3348

Abstract

Bintan is one of the regions with annual cases of oil spills, which were excluded from tank cleaning and black waste disposal activities. In arranging oil spill response, it is important to know the areas that are potentially affected, using oil spill trajectory model by GNOME. SAR (Sentinel-1) data is used to create coordinates for oil spills location in GNOME. SAR data processing is using SNAP software, with Lee Algorithm filter (window 5x5). The areas that potentially exposed to oil spills are known based on Environmental Sensitivity Index (ESI). In this model, oil spill will reach the Bintan Coast within 2 to 5 days with average surface current speed of 4.28 m/s (West Monsoon). The estimated of oil total amount is 1,767 barrel, which 1,157 barrel polluted the coast, 606 barrel has evaporation and dispersion and the other 4 barrel was off map. The most sensitive area to oil spills are Trily Resort Center Bintan and Sebong Bay (Index 10D). The ESI average among the Bintan region are Index 3A and 3B such as Lagoi, Tanjung Berakit, Pulau Pangkil, Pulau Mapur, Cabana, Pulau Lobam, Pantai Mayang Sari, Pantai Indah Club Med Bintan, Bintan Lagoon Resort, Pantai Senggiling, and Pengudang.
Halaman Belakang Vol. 17 No. 2 Desember 2020 Redaksi Jurnal
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3623

Abstract

DINAMIKA LUASAN MANGROVE DI PESISIR PROBOLINGGO MENGGUNAKAN CITRA SATELIT Tubagus Solihuddin; Aristiya Putri Widyantara
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3216

Abstract

Indonesia has the most extensive mangrove ecosystem in the world. One of mangrove ecosystem is located at Probolinggo coastal area, East Java Province. The mangrove area changes, over time whether it's decreasing or increasing. This research aims to calculate the extent of mangrove ecosystem in the past 20 years and map the distribution of mangrove in three different times i.e. 1998, 2008, and 2018. The satellite imageries used in this research are 1998’s Landsat 5 TM imagery, 2008’s Landsat 7 ETM+ imagery, and 2018’s Landsat 8 OLI imagery. Object-Based Image Analysis (OBIA) was employed to classify the mangrove and calculate the area for the 1998, 2008, and 2018 respective year. Normalized Difference Vegetation Index (NDVI) was used to determine the density level of mangrove canopy based on an object’s response to spectrum radiation red and NIR. The result shows that the mangrove area decreased from 1998 to 2008 constituting 514 Ha, and 386 Ha respectively. The mangrove area increased to about 464 Ha in 2018. The average mangrove canopy densities referring to NDVI analysis are 0.22012, 0.119492, and -0.019555 in respective years of 1998, 2008, and 2018. Within these 20 years, based on BAPLAN Forestry’s table classification of mangrove forest density, the mangrove forest densities at Probolinggo coastal area are relatively low.
ANALISIS SPEKTRAL DARI SERAPAN DAN PANTULAN DAUN LAMUN MENGGUNAKAN SPEKTRORADIOMETER TRIOS-RAMSES DI NUSA LEMBONGAN DAN PEMUTERAN, BALI Alvidita Beatrix Indayani
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3384

Abstract

Knowledge and technological developments are needed to achieve the 14th sustainable development goals (SDGs), namely life below water.One of the developments in remote sensing technology is hyperspectral data for spectrometry analysis using underwater sensors. This study aims to determine the absorption and reflectance features as well as the specific location of the spectral channels of various seagrass leaf conditions. Spectral measurements were carried out on three species of seagrass, namely Cymodocea rotundata (Cr), Thalassia hemprichii (Th), and Enhalus acoroides (Ea) along with the physical conditions attached to seagrass leaves (green, yellow to brown, black, and covered leaves by epiphytic organisms) in shallow sea waters. Spectral measurements using a spectroradiometer equipped with an irradiance hyperspectral radiometer sensor from TriOS-RAMSES, have a spectral range of 320-950 nm and a spectral channel width of 3.3 nm. The measurement process is done with a Field of View (FOV) angle of seven degrees (70). The continuum removal algorithm is used to identify the spectral response features of various seagrass leaf conditions. The results show the location of absorption channels and reflections close together. The location of the absorption feature occurs in the blue channel region (463-493 nm) and the red-red edge channel (671-674 nm). The location of the reflected peaks in the green channel (560-577 nm) and red channel (648 nm) of various seagrass leaf conditions.
Halaman Depan Vol. 17 No. 2 Desember 2020 Redaksi Jurnal
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3622

Abstract

PEMANFAATAN DATA ENHANCED VEGETATION INDEX VIIRS DAN PERBANDINGAN DENGAN MODIS UNTUK PEMANTAUAN PERTUMBUHAN PADI DI PULAU JAWA Anisa Rarasati; Dony Kushardono
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 17 Nr. 2 Desember 2020
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2020.v17.a3361

Abstract

Beras merupakan salah satu makanan pokok masyarakat Indonesia yang banyak diproduksi di dalam negeri. Karena tingginya tingkat konsumsi beras, pemerintah perlu memprediksi produksi tanaman padi dalam negeri untuk membuat kebijakan. Prediksi produktifitas padi ini dapat dilakukan menggunakan data penginderaan jauh. Di Indonesia telah dibuat pedoman pengolahan prediksi padi oleh Pusat Pemanfaatan Penginderaan Jauh, LAPAN menggunakan enhanced vegetation index (EVI) yang berasal dari sensor Moderate Resolution Imaging Spectroradiometer (MODIS) satelit Terra. Selain itu, data MODIS juga banyak digunakan di bidang pertanian, khususnya padi. Tetapi data MODIS hampir berakhir masa berlakunya sehingga diperlukan data pengganti. Data Visible Infrared Imaging Radiometer Suite (VIIRS) didesain sebagai pengganti MODIS. Untuk itu, penelitian ini dilakukan untuk mengetahui hubungan EVI data dari VIIRS dan MODIS dalam tujuannya menggantikan data MODIS dalam pemantauan padi. Dan hasil yang didapatkan menunjukkan tingkat korelasi tinggi dengan R2 sebesar 0.84 antara kedua EVI tersebut. Oleh karena itu, EVI VIIRS memiliki potensi yang sangat baik untuk menggantikan EVI MODIS.

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