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Contact Name
Lalu Muhamad Jaelani
Contact Email
lmjaelani@its.ac.id
Phone
+62819634394
Journal Mail Official
lmjaelani@its.ac.id
Editorial Address
Department of Geomatics Engineering, Faculty of Civil, Planning, and Geo-engineering; Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia. Phone 031-5929486, 031-5929487
Location
Kota surabaya,
Jawa timur
INDONESIA
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
ISSN : 14128098     EISSN : 2549726X     DOI : https://doi.org/10.12962/inderaja
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.
Articles 5 Documents
Search results for , issue "Vol. 14 No. 1 (2017)" : 5 Documents clear
PENGEMBANGAN LAYANAN WEB SPASIAL INFORMASI PEMANFAATAN PENGINDERAAN JAUH Sarno, Sarno
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2017.v14.a2546

Abstract

Dissemination implementation of remote sensing application information through the management of National Earth Observation System at the Remote Sensing Application Center of National Institute of Aeronautics and Space could be achieved by expanding and completing the dissemination mechanism, from the traditional way to spatial web services. The service is a standard defined by the Open Geospatial Consortium. These standards are widely used for the dissemination of spatial information through Web Map Services, Web Feature Services and Web Coverage Services - based standards and greatly assist in the implementation function of data application and remote sensing information dissemination. This research aims to analyze and provide development methods of spatial web services for remote sensing application information. The research methods include setting the initial requirements, programming a map file and spatial web services testing. The results showed that the spatial web services based on University of Minnesota Mapserver has been successfully implemented and tested using Google Map real web map service client and QGIS Desktop in case study forest cover change in Indonesia.
VALUASI JUMLAH AIR DI EKOSISTEM LAHAN GAMBUT DENGAN DATA LANDSAT 8 OLI/TIRS Risdiyanto, Idung; Wahid, Allan Nur
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2017.v14.a2592

Abstract

The water content of peatland ecosystems stored as gasses in the air and as liquid in the peat soil and vegetation. The presence of water was influential to the value of spectral radians received by satellite sensors. Objective of study were develop empirical model to be applied in the Landsat 8 satellite imagery interpretation to estimate water content of peatland ecosystem. Method consisted of field measurements and satellite data interpretation. Field activities aimed to obtain weather parameters such as radiation, air temperature, surface temperature, evapotranspiration (ET), relative humidity (RH), soil water content (KAT), and biomass for each land cover in peatland ecosystems. Field measurements results were used to validate the parameters derived from Landsat 8 satellite data. Water content in the air was assessed by the ET and RH, in the soil was assessed by soil heat flux (G) and in the vegetation by biomass. The results of the validation of the data field measurement with Landsat 8 showed only ET (r2 = 0.71), RH (r2 = 0.71), and biomass (r2 = 0.87) had a strong relationship, while between G and KAT had weak relationship. Conclusion of this study indicated Landsat 8 satellite data could be used to calculate the water content in the air and vegetation. Thus, estimating water content in the peatland ecosystem with satellite data can only be done on the surface.
ESTIMASI PRODUKTIVITAS PRIMER PERAIRAN BERDASARKAN KONSENTRASI KLOROFIL-A YANG DIEKSTRAK DARI CITRA SATELIT LANDSAT-8 DI PERAIRAN KEPULAUAN KARIMUN JAWA Nuzapril, Mulkan; Susilo, Setyo Budi; Panjaitan, James P.
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2017.v14.a2548

Abstract

Sea primary productivity is an important factor in monitoring the quality of sea waters due to his role in the carbon cycle and the food chain for heterotrophic organisms. Estimation of sea primary productivity may be suspected through the values of chlorophyll-a concentration, but surface chlorophyll-a concentration was only able to explain 30% of the primary productivity of the sea. This research aims to build primary productivity estimation model based on chlorophyll-a concentration value of a surface layer of depth until depth compensation. Primary productivity model of relationships with chlorophyll concentration were extracted from Landsat-8 imagery then it could be used to calculated of sea primary productivity. The determination of the depth classification were done by measuring the attenuation coefficient values using the luxmeter underwater datalogger 2000 and secchi disk. The attenuation coefficient values by the luxmeter underwater, ranges between of 0.13-0.21 m-1 and secchi disk ranged, of 0.12 – 0.21 m-1. The penetration of light that through into the water column where primary productivity is still in progress or where the depth of compensation ranged from 28.75 – 30.67 m. The simple linier regression model between average value of chlorophyll concentration in all euphotic zone with sea primary productivity has high correlation, it greater than of surface chlorophyll-a concentration (R2 = 0.65). Model validation of sea primary productivity has high accuracy with the RMSD value of 0.09 and satellite-derived sea primary productivity were not significantly different. The satellite derived of chlorophyll-a could be calculated into sea primary productivity
METODE DUAL KANAL UNTUK ESTIMASI KEDALAMAN DI PERAIRAN DANGKAL MENGGUNAKAN DATA SPOT 6 STUDI KASUS : TELUK LAMPUNG Arief, Muchlisin; Adawiah, Syifa Wismayati; Parwati, Ety; Marpaung, Sartono
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2017.v14.a2618

Abstract

Depth data can be used to produce seabed profile, oceanography, biology, and sea level rise. Remote sensing technology can be used to estimate the depth of shallow marine waters characterized by the ability of light to penetrate water bodies. One image that can estimate the depth is SPOT 6 which has three visible canals and one NIR channel with 6 meter spatial resolution. This study used SPOT 6 image on March 22, 2015. The image was first being dark pixel atmospheric corrected by making 30 polygons. The originality of this method was to build a correlation between the dark pixel value of red and green channels with the depth of the field measurement results, made on June 3 to 9, 2015. The algorithm derived experimentally consisted of: thresholding which served to separate the land by the sea and the correlation function. The correlation function was obtained: first correlating the observation value with each band, then calculating the difference of minimum pixel darkness value and minimum for red and green channel was 0.056 and 0.0692. The model was then constructed by using the comparison proportions, so that the linear equations were obtained in two channels: Z (X1, X2) = 406.26 X1 + 327.21 X2 - 28.48. Depth estimation results were for a 5-meter scale, the most efficient estimation with the smallest error relative mean occurred in shallow water depth from 20 to 25 meters, while the result of 10 meters scale from 20 to 30 meters and the estimated depth had similar patterns or could be said close to reality. This method was able to detect sea depths up to 25 meters and had a small RMS error of 0.653246 meters. Thus the two-channel method could offer a fast, flexible, efficient, and economical solution to map topography of the ocean floor.
UJI MODEL FASE PERTUMBUHAN PADI BERBASIS CITRA MODIS MULTIWAKTU DI PULAU LOMBOK Parsa, I Made; Dirgahayu, Dede; Manalu, Johannes; Carolita, Ita; KH, Wawan
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2017.v14.a2621

Abstract

Model testing is a step that must be done before operational activities. This testing aimed to test rice growth phase models based on MODIS in Lombok using multitemporal LANDSAT imagery and field data. This study was carried out by the method of analysis and evaluation in several stages, these are: evaluation of accuracy by multitemporal Landsat 8 image analysis, then evaluation by using field data, and analysis of growth phase information to calculate model consistency. The accuracy of growth phase model was calculated using Confusion Matrix. The results of stage I analysis for phase of April 30 and July 19 showed the accuracy of the model is 58-59%, while the evaluation of stage II for phase of period July 19 with survey data indicated that the overall accuracy is 53%. However, the results of model consistency analysis show that the resulting phase of the smoothed MODIS imagery shows a consistent pattern as well as the EVI pattern of rice plants with an 86% accuracy, but not for pattern data without smoothing. This testing give conclusion is the model is good, but for operational MODIS input data must be smoothed first before index value extraction.

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