cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
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
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 155 Documents
 12   13   14   15   16 
Bahasa Inggris Abdurrahman Afiq Yuda Hammaami; Nain Dhaniarti Raharjo; Lalu Muhamad Jaelani
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 20 No 1 (2026)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/inderaja.v20i1.9762

Abstract

The Suramadu Bridge is a vital infrastructure connecting Java and Madura Islands. Pylons, as key components of cable-stayed bridges, are susceptible to geometric changes due to sea wave exposure, wind loads, and increasing traffic volume. This study analyzes the geometric displacement of pylons by comparing two periods of UAV LiDAR point cloud data acquired on 5 January 2026 and 2 February 2026 against the Detailed Engineering Design (DED). Data acquisition was conducted using a DJI Matrice 350 UAV with a Geosun GS-260H LiDAR sensor. The geometric analysis encompasses six dimensional parameters and pylon tilt calculated from the combined centroid of both pylon legs. Accuracy validation using ICP points based on SNI 9135-2:2023 confirmed both periods achieved Class 2 accuracy at 1:2,500 scale. The upper width parameter (L1) recorded the largest deviation of 186 mm on the Madura pylon in Period 3, while the middle thickness (T2) was identified as the most critical parameter due to consistently negative deviation, reaching 134 mm on the Madura pylon in Period 5. The Mean Absolute Error indicated that the MDR pylon (51 mm) exhibited greater dimensional change intensity than the SBY pylon (36 mm). Tilt analysis showed both pylons inclined convergently toward the main span, attributed to cable tension.
Variabilitas Spasio-temporal Terrestrial Water Storage dan Groundwater Storage di Pulau Papua Menggunakan Satelit GRACE dan GRACE-FO Daniar Ihza Carundyatama; Krisna Dwi Oktabrian; Farrel Fitria Nathania Kuncara; Purwanti Lelly Sabrina; La Ode Ashamad Nusriah
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 20 No 1 (2026)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/inderaja.v20i1.9810

Abstract

Papua Island represents a region with complex hydrological characteristics influenced by mountainous topography and equatorial tropical climate conditions. This study aims to analyze the spatial, temporal, and seasonal variability of Total Water Storage (TWS) and Groundwater Storage (GWS) across Papua Island during the period 2005–2024 using GRACE and GRACE-FO satellite data integrated with Global Land Data Assimilation System (GLDAS) outputs. The analysis includes spatial mapping of TWS distribution for selected representative years, time-series evaluation across three sub-regions (West Papua, North Papua, and South Papua), and estimation of GWS using the residual approach. The results indicate strong spatial heterogeneity in TWS distribution, with higher storage consistently observed in West Papua and North Papua compared to South Papua. Temporally, TWS shows a positive increasing trend across all sub-regions, with the highest rate observed in West Papua at +0.43 cm/year. GWS variations exhibit a positive long-term trend of +0.38 cm/year and a clear seasonal recharge–depletion cycle, with recharge occurring during June–November and depletion during December–May. These findings demonstrate that GRACE and GRACE-FO observations provide an effective approach for monitoring regional terrestrial and groundwater storage changes, particularly in tropical regions with limited in-situ hydrological observations.
Mangrove Ecosystem Vulnerability through Integrated Remote Sensing: A Systematic Literature Review Rakhshanda Shaina Ahava Hidayat; Muhammad Iqbal Habibie; Ayang Armelita Rosalia
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 20 No 1 (2026)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/inderaja.v20i1.9866

Abstract

Mangrove ecosystems play a crucial role in maintaining the stability of coastal environments, but they face various pressures due to human activities and environmental changes that increase their vulnerability. This research aims to examine the development of remote sensing-based approaches in monitoring the condition, changes, and vulnerability of mangrove ecosystems, as well as to identify the main factors affecting their degradation. The method used is a Systematic Literature Review (SLR) with qualitative descriptive analysis of scientific publications related to mangrove monitoring using remote sensing technology. The study results show that remote sensing-based mangrove research has significantly increased, especially after 2010, along with the development of sensor technology, geographic information systems (GIS), and artificial intelligence methods. The main factors affecting the vulnerability of mangroves include anthropogenic pressures such as land conversion and pollution, environmental factors such as rising sea levels and hydrological changes, as well as biophysical factors related to the structure and condition of the vegetation. The integration of remote sensing, GIS, and spatial analysis has proven to enhance the effectiveness of monitoring and understanding the dynamics of mangrove ecosystem changes. Thus, an integrated geospatial approach becomes an important foundation in supporting the sustainable management and conservation of mangroves.
Bahasa Inggris Mohammad Rifqi Alfarizi; Lalu Muhamad Jaelani
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 20 No 2 (2026)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/inderaja.v20i2.9761

Abstract

Urban air quality monitoring requires methods that are both comprehensive and cost-effective. Sentinel-5P TROPOMI satellite data are freely available; however, their units (mol/m²) cannot directly represent surface pollutant concentrations (μg/m³) without the Vertical Column Height (VCH) parameter, which is commonly assumed to be constant. This assumption contradicts the dynamic nature of the atmosphere. This study demonstrates that VCH is inherently dynamic through the integration of Sentinel-5P data with in-situ air quality sensor observations in Surabaya City. Daily VCH values were calculated for SO₂, CO, and NO₂ at the Kebonsari and Wonorejo monitoring stations throughout 2024 by pairing Vertical Column Density (VCD) data (retrieved via Google Earth Engine) with surface pollutant concentrations (obtained from the Surabaya Environmental Agency) based on matching dates and coordinates. The results show that VCH varies significantly on both daily and monthly scales, indicating that a static VCH assumption is not representative. The correlation between VCH and in-situ concentrations is negative, with the following order of strength: CO (r = −0.7989; R² = 0.6383) > NO₂ (r = −0.5913; R² = 0.3496) > SO₂ (r = −0.3818; R² = 0.1457), consistent with the atmospheric lifetime of each pollutant. Additional analysis shows that MODIS surface temperature shows weak positive correlations with VCH for all pollutants: SO₂ (r = 0.2903; R² = 0.0843) > CO (r = 0.2464; R² = 0.0607) > NO₂ (r = 0.0033; R² ≈ 0.0000), indicating that surface temperature alone is insufficient to explain vertical pollutant distribution. A dynamic VCH approach is therefore necessary for more accurate satellite-to-surface pollutant conversion, and future models require integration of more comprehensive meteorological parameters
Deep Learning-Based Spatio-Temporal LULC Mapping and Urban Growth Analysis of Gading Serpong, Tangerang (2017–2026) Kurnia Muludi; Ary Budi Warsito; Prya Artha Widjaja
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 20 No 1 (2026)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/inderaja.v20i1.10126

Abstract

Land-use/land-cover (LULC) changes in new satellite towns such as Gading Serpong, Tangerang, Indonesia, represent a major driving force of spatial transformation and landscape fragmentation in metropolitan outskirts. Rapid urban development has converted agricultural lands, open spaces, and local water bodies into massive residential and commercial built-up areas. The objective of this study is to analyze a 10-year period of spatio-temporal LULC dynamics (2017–2026) using multispectral Sentinel-2 satellite imagery. For classification, the performance of a traditional pixel-based Random Forest (RF) classifier is compared against two state-of-the-art Deep Learning semantic segmentation models (U-Net and DeepLabv3+). The models successfully mapped the study area into four classes: Water Body, Vegetation, Built-Up Area, and Bare Land. Quantitative results indicate an expansion of the Built-Up Area from 212.0 Ha in 2017 to 2583.4 Ha by 2026. The primary converted land covers were Vegetation, which declined from 1759.2 Ha to 818.8 Ha, and Bare Land, which decreased from 1568.7 Ha to 193.8 Ha. The highest performance was achieved by the DeepLabv3+ algorithm, yielding an Overall Accuracy of 88.40% and a mean IoU of 76.24%. These results significantly outperform U-Net (63.69% mIoU) and the Random Forest baseline (44.52% mIoU) under complex urban spectral mixing conditions.

Page 16 of 16 | Total Record : 155

 12   13   14   15   16 

Filter by Year

2004 2026


Reset
Filter By Issues
All Issue Vol 20 No 2 (2026) Vol 20 No 1 (2026) Vol 19 No 2 (2025) Vol 19 No 1 (2025) Vol. 18 No. 1 (2021) Vol. 17 No. 1 (2020) Vol. 16 No. 2 (2019) Vol. 16 No. 1 (2019) Vol. 15 No. 2 (2018) Vol. 15 No. 1 (2018) Vol. 14 No. 2 (2017) Vol. 14 No. 1 (2017) Vol. 13 No. 2 (2016) Vol. 13 No. 1 (2016) Vol. 12 No. 2 (2015) Vol. 12 No. 1 (2015) Vol. 11 No. 2 (2014) Vol. 11 No. 1 (2014) Vol. 10 No. 2 (2013) Vol. 10 No. 1 (2013) Vol. 9 No. 2 (2012) Vol. 9 No. 1 (2012) Vol. 8 No. 1 (2011) Vol. 6 No. 1 (2009) Vol. 5 No. 1 (2008) Vol. 4 No. 1 (2007) Vol. 3 No. 1 (2006) Vol. 1 No. 1 (2004) More Issue