Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
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.
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147 Documents
<![CDATA[STANDARISASI KOREKSI DATA SATELIT MULTIWAKTU DAN MULTISENSOR (LANDSAT TM/ETM+ DAN SPOT-4) ]]>
<![CDATA[Trisakti, Bambang]]>;
<![CDATA[Nugroho, Gagat]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 1 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i1.3257
<![CDATA[Remote sensing satellite data has been widely used to support watershed and lake managements. However researches conducted in Indonesia are facing common problems related with standardization of data pre-processing, particularly that are related to orthorectification and radiometric correction. The objective of this research is to standardize the satellite data correction to monitor Total Suspended Material (TSM) in Limboto lake along 1990-2010 period using Landsat TM/ETM+ and SPOT-4. The data correction process was performed included orthorectification, sun correction, terrain correction and normalization of data with different time and different sensor. The result of each correction process was examined to evaluate the quality improvement before and after correction. The corrected data was then used to monitor the degree of turbidity of Limboto Lake during 1990-2010 periods. The study results show that data correction reduces position error and object spectral difference due to differences in acquisition time and sensor. The examined correction provides more accurate and consistent results. The quality of Limboto Lake was monitored decreases gradually, where the higher TSM concentration was found during the period of 1990-2010.]]>
<![CDATA[ANALISIS POTENSI BANJIR DI SAWAH MENGGUNAKAN DATA MODIS DAN TRMM (STUDI KASUS KABUPATEN INDRAMAYU) ]]>
<![CDATA[Febrianti, Nur]]>;
<![CDATA[Domiri, Dede Dirgahayu]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 1 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i1.3258
<![CDATA[The occurrence of flooding in paddy field may cause the decrease of total production. To increase the food sufficiency within the country, the monitoring of flood affected paddy field is very important to be implemented. The satellite imagery is one of tools for monitoring the flooding area. In this study; we used remotely sensed data from MODIS (Moderate Resolution Imaging Spectroradiometer) and TRMM (Tropical Rainfall Measuring Mission) for January 2011 and January 2012, respectively. The district of Indramayu was selected as the study site due to one of the center of the rice production. The flood frequency method was utilized to estimate the flood duration. Some assumption used in this study, i.e.: (i) the assumed to be wetland rained rice. (ii) Rice fields are assumed in the flat. (iii) The rainfall exceeds the crop water demand will be potentially because the floods, (iv) The rainfall have large impact causing flooding when compare to index vegetation greenness. The calculation of the flood potential did known that the equation used compelling enough because it has been in accordance with actual flood events. The class of potential flooding were identifying as a class of height severe flooding. The calculation of flood frequency in January 2011 showed that there had been flooding up to 4 times a month. Besides, there is 18,400 ha that has four times frequency of flooding, respectively and requires to be aware crop failures occurred in both conditions. The condition on January 2012 was in a safe because floods occurred only one time. The extensive flooding of rice fields in Indramayu district January 2012.]]>
<![CDATA[MODEL BAHAYA BANJIR MENGGUNAKAN DATA PENGINDERAAN JAUH DI KABUPATEN SAMPANG ]]>
<![CDATA[Haryani, Nanik Suryo]]>;
<![CDATA[Zubaidah, Any]]>;
<![CDATA[Dirgahayu, Dede]]>;
<![CDATA[Yulianto, Hidayat Fajar]]>;
<![CDATA[Pasaribu, Junita]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 1 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i1.3259
<![CDATA[Flood is the first biggest disaster in Indonesia, as stated by the National Disaster Management Agency (BNPB) in the BNPB’s natural disaster data of year 2000 to 2009. Considering the flood has the significant impact of causing the casualties and material losses, it is necessary to study on it. One of useful data for studying the flood is remote sensing data. The advantage of good historical data makes it possible to see the changes of cover/land use from year to year in a region. The extensive area coverage of remote sensing data allows it to view and analyze in a comprehensive manner. The method of the study of flood hazard models is using multiple variables, where each variable has a class of criteria. Determination of the weight of each flood variable by using the Composite Mapping Analysis. The results of this study shows the main cause of flooding in the District of Sampang is that most of the land system in the cities are the combined estuary and swamp plain, forming a low land and is triggered by the torrential rain. The model of flood hazard maps produced by variable weighting floods with a multi criteria analysis method which is function of rainfall, landuse, slope, land system and elevation.]]>
<![CDATA[PEMETAAN MUATAN PADATAN TERSUSPENSI MENGGUNAKAN DATA SATELIT LANDSAT (STUDI KASUS: TELUK SEMANGKA) ]]>
<![CDATA[Arief, Muchlisin]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 1 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i1.3260
<![CDATA[Total Suspended Matters (TSM) defined all solids or particles with a larger size 1 µm that are suspended in water resulting in decreased quality of water until the water can not be used as intended. There are various methods that have been made in mapping the TSM based on remote sensing satellite data both low and high resolution. This paper describes TSM mapping which TSM algorithm was directly applied to the digital number value of Landsat image. The mapping process was preceded by a thresholding method to separate the water with other objects (clouds, cloud shadows and the mainland), then the TSM concentration was calculated through the algebraic sum of band 1, 2, 3, and 4 and ended with density slice range process. Based on the TSM analysis, the TSM concentration in the Semangka Gulf was caused by human waste and also the material carried by streams of water from ponds and sewage waste soil erosion. TSM concentration areas was spread out in water of the Wonosobo District until 640 meters of spreading length and Kota Agung Timur districts until 3240 meters of spreading length.]]>
<![CDATA[PERBANDINGAN KARAKTERISTIK SPEKTRAL (SPECTRAL SIGNATURE) PARAMETER KUALITAS PERAIRAN PADA KANAL LANDSAT ETM+ DAN ENVISAT MERIS ]]>
<![CDATA[Budhiman, Syarif]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i2.3261
<![CDATA[This study analyzed 3 optically active water constituents (Total Suspended Matter (TSM), Chlorophyll a (Chl a) and Color Dissolved Organic Matter (CDOM)) measured by in situ spectroradiometer (350-950 nm, interval 3.3 nm) and laboratory analysis for respective concentration measurements. Remote sensing reflectances ($R_s$) were derived from radiance and irradiance measurements and estimated using bio-optical model approach. The spectral signatures of derived $R_s$ were converted to ETM+ and MERIS bands using respective spectral response sensitivity. The converted $R_s$ were used to estimate the concentrations of 3 optically active water constituents using optimization method. The derived concentrations were validated with measured concentrations from laboratory analysis. ETM+ sensor with 4 bands provided better estimation for TSM ($R^2=0.70$) and CDOM ($R^2=0.64$) while the coefficient determination ($R^2$) for Chl a is only 0.46. However, MERIS sensor with 10 bands provided better estimation than ETM+, with coefficient determinations were higher than 0.70 for all water constituents. RMSE values for MERIS sensor showed smaller error estimation (16.84 gm-3 (TSM), 2.66 mg m-3 (Chl a) and 0.26 m-1 (CDOM)) compare with ETM+ sensor (19.89 gm-3 (TSM), 4.96 mg m-3 (Chl a) and 0.29 m-1 (CDOM)).]]>
<![CDATA[MODEL SIMULASI BANJIR MENGGUNAKAN DATA PENGINDERAAN JAUH, STUDI KASUS KABUPATEN SAMPANG DENGAN MENGGUNAKAN METODE GRIDDED SURFACE SUBSURFACE HYDROLOGIC ANALYSIS ]]>
<![CDATA[Haryani, Nanik Suryo]]>;
<![CDATA[Pasaribu, Junita Monika]]>;
<![CDATA[Ambarwati, Dini Oktavia]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i2.3262
<![CDATA[The problem of flood that yearly occurred in Sampang district was due to the very large amount of runoff flow to the Sampang Cit, very high sedimentation in the river that crosses the city, as well as the lack of good drainage system especially in urban residential areas. Some of that problems eventually can lead to flooding in the City of Sampang. The method used for flood simulation model was GSSHA (Gridded Surface Subsurface Hydrologic Analysis), which is able to produce a good hydrological components. The data used data in this research among others are: Qmorph, DEM-SRTM (Digital Elevation Model-Shuttle Radar Topography Mission), SPOT-5 of 2010, land map, river cross sections and field data. This flood simulation model research resulting flood discharge, which is described in the hydrograph and flood depth calculations. The peak discharge resulted in several catchment areas (CA): Klampis CA is 5.40 m³/s, Jelgung CA is 364788.9 m³/s, Kamoning CA is 32.40 M³/s, and 3 CAs which are associated with the above CAs is 174059 m³/s.]]>
<![CDATA[EVALUASI PRODUK MODIS GROSS PRIMARY PRODUCTION PADA HUTAN RAWA GAMBUT TROPIS INDONESIA ]]>
<![CDATA[Vetrita, Yenni]]>;
<![CDATA[Hirano, Takashi]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i2.3264
<![CDATA[Gross Primary Production (GPP) estimation method was developed as one approach for calculating the amount of carbon stored in vegetation. One of the GPP products which can be operationally downloaded free of charge from Terra/Aqua MODIS (NASA satellite) is MODIS GPP product (MOD17). The examination of this product needs to be performed in several ecosystem types due to its global properties. Recently, a new version of the product has been launched, however its examination on tropical forests particularly over Indonesia has not been implemented yet. In this study, new version of MODIS GPP (MOD17A2-51) was evaluated in tropical peat swamp forest, in Central Kalimantan Province using time series and statistical analysis of field data (GPP EC). The study results show that the time series of 8-daily MODIS GPP provide a similar pattern although it has low correlation. In general, MODIS GPP tend to be underestimate either on rainy or dry season. However, an overestimate result was found during the ENSO-caused long dry season in 2002. Nevertheless, the accumulated value of GPP with seasonal consideration (dry and rainy) shows good relationship (r=0.94, RMS= 17.47, and Efficiency score= 0.68). The 2nd dry season period (August-October) shows better distribution than other periods. This study concludes that the MODIS GPP product version 51 can be used for biomass seasonal monitoring of tropical peat swamp forests in Indonesia.]]>
<![CDATA[PERBANDINGAN TEKNIK INTERPOLASI DEM SRTM DENGAN METODE INVERSE DISTANCE WEIGHTED (IDW), NATURAL NEIGHBOR DAN SPLINE ]]>
<![CDATA[Pasaribu, Junita Monika]]>;
<![CDATA[Haryani, Nanik Suryo]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i2.3265
<![CDATA[Flood simulation model requires input data, such as 10 meters spatial resolution of DEM (Digital Elevation Model) which is higher than the available data DEM SRTM (Shuttle Radar Topography Mission). Detail DEM can be made using interpolation method of height points. The research has two purposes, first is to generate DEM with 10 meters spatial resolution and the second is to study the differences of the DEM interpolation result by using Inverse Distance Weighted, Natural Neighbor and Spline. Height points of DEM SRTM were extracted and converted into point format data, and then it was used as the input data in interpolation process. The quality of DEM from the interpolation result was influenced by weighting model used in the process, therefore the effects of weighting model on height value obtained by the interpolation result was also observed. The result indicates that the best DEM with 10 meters spatial resolution can be produced using Natural Neighbor and Regularized Spline type method. The DEMs have low error value, smooth surface and closer appearance to the earth's surface observed visually from Google Earth. Another influential factor to improve the quality of DEM in interpolation process, is the height points of the input data should be evenly distributed over the study area.]]>
<![CDATA[PEMANFAATAN DATA SATELIT UNTUK ANALISIS POTENSI GENANGAN DAN DAMPAK KERUSAKAN AKIBAT KENAIKAN MUKA AIR LAUT ]]>
<![CDATA[Anggraini, Nanin]]>;
<![CDATA[Trisakti, Bambang]]>;
<![CDATA[Soesilo, Tri Edhi Budhi]]>
<![CDATA[ Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012) ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.30536/inderaja.v9i2.3266
<![CDATA[Increasing of ocean water volume caused sea level rise (SLR) that threatens the existence of small islands and coastal areas, such as North Jakarta. Besides the SLR, North Jakarta is also threatened by land subsidence. This study aims to predict the height of SLR in 2030 and to analyze the impact of SLR on the coastal areas of North Jakarta. The total height of SLR in 2030 was predicted using tidal data, land subsidence data, and SLR prediction by B2 scenario from the Intergovernmental Panel on Climate Change (IPCC). Potential inundation area due to SLR was estimated using Digital Elevation Model Shuttle Radar Topography Mission (DEM SRTM) X-C band with spatial resolution 30 m. The damage was analyzed by doing the overlay between the inundation areas with the land use information extracted from QuickBird data. The result shows that the SLR predictions in 2030 are 2.88 m caused by the tide, 2.28 m caused by the land subsidence, and 1.29 m caused by the B2 scenario IPCC. The total height of SLR prediction is 6.45 m. The potential damages of land use are dominated by urban area (1045 ha) and industrial area (563 ha). The most inundated areas are located in Penjaringan sub-district for urban (523 ha) and in Cilincing sub-district for industrial area (311 ha).]]>
