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The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Published by Badan Riset dan Inovasi Nasional
ISSN : 02166739     EISSN : 2549516X     DOI : https://doi.org/10.55981/ijreses
Core Subject : Science,
Earth & Planetary Sciences
The International Journal of Remote Sensing and Earth Sciences (IJReSES), published by Badan Riset dan Inovasi Nasional (BRIN) in collaboration with the Ikatan Geografi Indonesia (IGI) and managed by the Department of Geography Universitas Indonesia, is a pivotal platform in the global dissemination of research in earth sciences and remote sensing. It aims to enrich the literature in these fields and serves as a key resource, particularly in Indonesia and Asian countries, while extending its reach worldwide. The journal is instrumental in complementing the body of knowledge in Remote Sensing and Earth Sciences and is committed to fostering the participation of young scientists, especially from Indonesia and Asian countries. Scope and Focus: IJReSES encompasses a wide spectrum of topics related to remote sensing and earth sciences, including but not limited to: - Remote sensing technologies and methodologies - Geospatial data acquisition, processing, and analysis - Earth observation and satellite imagery - Geographic Information Systems (GIS) - Environmental monitoring and management - Climate change and its impacts - Natural resource management - Land use and land cover change - Urban and rural development - Disaster risk reduction and response - Geology and geomorphology - Soil and water sciences - Biodiversity and ecosystem studies
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Ilmu Bumi dan Planet (Lain-Lain)
Articles 327 Documents
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VARIABILITY OF SEA SURFACE TEMPERATURE (SST) AND CHLOROPHYLL-A (CHL-A) CONCENTRATIONS IN THE EASTERN INDIAN OCEAN DURING THE PERIOD 2002–2017 Michelia Mashita; Jonson Lumban-Gaol
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/ijreses.v16i1.13842

Abstract

We analysed the variability of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) in the eastern Indian Ocean (EIO). We used monthly mean Chl-a and SST data with a 4-km spatial resolution derived from Level-3 Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) distributed by the Asia-Pacific Data-Research Center (APDRC) for the period 2002–2017. Wavelet analysis shows the annual and interannual variability of SST and Chl-a concentration in the EIO. The annual variability of SST and Chl-a is influenced by monsoon systems. During a southeast monsoon, SST falls while Chl-a increases due to upwelling. The annual variability of SST and Chl-a is also influenced by the Indian Ocean Dipole (IOD). During positive phases of the IOD (2006, 2012 and 2015), there was more intense upwelling in the EIO caused by the negative anomaly of SST and the positive anomaly of Chl-a concentration.
STUDY ON POTENTIAL FISHING ZONES (PFZ) INFORMATION BASED ON S-NPP VIIRS AND HIMAWARI-8 SATELLITES DATA Sartono Marpaung; Teguh Prayogo; Ety Parwati; Kuncoro Teguh Setiawan; Orbita Roswintiarti
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 1 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a2817

Abstract

Sea surface temperature (SST) data from S-NPP VIIRS satellite has different spatial resolution with SST data from Himawari-8 satellite. In this study comparative analysis of potential fishing zones information from both satellites has been conducted. The analysis was conducted on three project areas (PA 7, PA 13, PA 19) as a representation Indonesian territorial waters. The data used were daily for both satellites with a period  time from August 2016 to December 2016. The method used was Single Image Detection (SIED) to detect thermal fronts. Method of mass center point for determining potential fishing zones coordinate point from result thermal front detection. Furthermore, an analysis of overlapping was done to compare the coordinate point information from both satellites. Based on data analysis that had been done, the result showed that potential fishing zones coordinate points of Himawari-8 satellite was mostly far from potential fishing zones coordinate point of S-NPP VIIRS. The coordinate points whose positionswere close together or nearly same from both satellites was only about 20 %. Differences in potential fishing zones coordinate positions occur due to the effect of different spatial resolutions of both satellite data and the size of the front thermal events that had high variability. The ideal potential fishing zones coordinate points information was probably a combination of the potential fishing zones coordinate points of S-NPP VIIRS and Himawari-8 by making two adjacent coordinate points to be a single coordinate point. Field validation testing was required to prove the accuracy of the coordinate point.
IDENTIFICATION OF MANGROVE FORESTS USING MULTISPECTRAL SATELLITE IMAGERIES Anang Dwi Purwanto; Wikanti Asriningrum
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/ijreses.v16i1.13844

Abstract

The visual identification of mangrove forests is greatly constrained by combinations of RGB composite. This research aims to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using the Optimum Index Factor (OIF) method. The OIF method uses the standard deviation value and correlation coefficient from a combination of three image bands. The image data comprise Landsat 8 imagery acquired on 30 May 2013, Sentinel 2A imagery acquired on 18 March 2018 and images from SPOT 6 acquired on 10 January 2015. The results show that the band composites of 564 (NIR+SWIR+Red) from Landsat 8 and 8a114 (Vegetation Red Edge+SWIR+Red) from Sentinel 2A are the best RGB composites for identifying mangrove forest, in addition to those of 341 (Red+NIR+Blue) from SPOT 6. The near-infrared (NIR) and short-wave infrared (SWIR) bands play an important role in determining mangrove forests. The properties of vegetation are reflected strongly at the NIR wavelength and the SWIR band is very sensitive to evaporation and the identification of wetlands.
ACCURACY EVALUATION OF STRUCTURE FROM MOTION THERMAL MOSAICING IN THE CENTER OF TOKYO Atik Nurwanda; Nobumitsu Tsunematsu; Hitoshi Yokoyama
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 2 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a2856

Abstract

In the airborne and high-resolution measurement of Land Surface Temperature (LST) over large area, capturing and synthesizing of many images are necessary. In the conventional method, the process of georeferencing a large number of LST images is necessary to make one large image. Structure from Motion (SfM) technique was applied to automized the georeferencing process. We called it “SfM Thermal Mosaicingâ€. The objective of this study is to evaluate the accuracy of SfM thermal mosaicing in making an orthogonal LST image. By using airborne thermal images in the center of Tokyo, the LST image with the 2m resolution was created by using SfM thermal mosaicing. Its accuracy was then analyzed. The result showed that in the whole examined area, the mean error distance was 4.22m and in the small parts of the examined area, the mean the error distance was about 2m. Considering the image resolution, the error was minimal indicating good performance of the SfM thermal mosaicing. Another advantage of SfM thermal mosaicing is that it can make precise orthogonal LST image. With the progress of UAV and thermal cameras, the proposed method will be a powerful tool for the environmental researches on the LST.
WATERMARKING METHOD OF REMOTE SENSING DATA USING STEGANOGRAPHY TECHNIQUE BASED ON LEAST SIGNIFICANT BIT HIDING Destri Yanti Hutapea; Octaviani Hutapea
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 1 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a282

Abstract

Remote sensing satellite imagery is currently needed to support the needs of information in various fields. Distribution of remote sensing data to users is done through electronic media. Therefore, it is necessary to make security and identity on remote sensing satellite images so that its function is not misused. This paper describes a method of adding confidential information to medium resolution remote sensing satellite images to identify the image using steganography technique. Steganography with the Least Significant Bit (LSB) method is chosen because the insertion of confidential information on the image is performed on the rightmost bits in each byte of data, where the rightmost bit has the smallest value. The experiment was performed on three Landsat 8 images with different area on each composite band 4,3,2 (true color) and 6,5,3 (false color). Visually the data that has been inserted information does not change with the original data. Visually, the image that has been inserted with confidential information (or stego image) is the same as the original image. Both images cannot be distinguished on histogram analysis.  The Mean Squared Error value of stego images of  all three data less than 0.053 compared with the original image.  This means that information security with steganographic techniques using the ideal LSB method is used on remote sensing satellite imagery.
DETECTING AND COUNTING COCONUT TREES IN PLEIADES SATELLITE IMAGERY USING HISTOGRAM OF ORIENTED GRADIENTS AND SUPPORT VECTOR MACHINE Yudhi Prabowo; Kenlo Nishida Nasahara
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/ijreses.v16i1.13848

Abstract

This paper describes the detection of coconut trees using very-high-resolution optical satelliteimagery. The satellite imagery used in this study was a panchromatic band of Pleiades imagery with aspatial resolution of 0.5 metres. The authors proposed the use of a histogram of oriented gradients(HOG) algorithm as the feature extractor and a support vector machine (SVM) as the classifier for thisdetection. The main objective of this study is to find out the parameter combination for the HOGalgorithm that could provide the best performance for coconut-tree detection. The study shows that thebest parameter combination for the HOG algorithm is a configuration of 3 x 3 blocks, 9 orientation bins,and L2-norm block normalization. These parameters provide overall accuracy, precision and recall ofapproximately 80%, 73% and 87%, respectively.
ANALYSIS OF ANTENNA SPECIFICATION FOR VERY HIGH RESOLUTION SATELLITE DATA ACQUISITION THROUGH DIRECT RECEIVING SYSTEM (DRS) Muchammad Soleh; Ali Syahputra Nasution; Arif Hidayat; Hidayat Gunawan; Ayom Widipaminto
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 2 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a2799

Abstract

Very High Resolution Satellite Image (VHRSI) data for Indonesian Government license is required by ministries/agencies, TNI, police, and local government to support national programs. But Indonesia did not have a VHRSI data recipient facility to directly acquire this data. In accordance with Law 21/2013 on Space, LAPAN is mandate to provide high resolution satellite data, and based on a roadmap for provision of satellite data in 2017, LAPAN will provide a VHRSI data reception facility through direct receiving system (DRS). This will be more efficient than other methods in providing the data. Priority provision of satellite data is for acquiring Pleiades and TerraSAR-X operating in the frequency range 8 GHz (X-Band). Therefore, to receive both data, it requires antenna subsystem with optimum coverage throughout Indonesia. Parameters to obtain the minimum antenna specifications include Free Space Loss (FSL), Carrier to Noise Ratio (C/No) and Antenna Gain to Noise Temperature (G/T). The calculation of G/T antenna is done for both satellites based on satellite parameters and analysis of antenna product availability in the market. Based on the calculation of satellite parameters shows that the minimum G/T value with the elevation of 5 degrees is 27.71 dB/K for Pleiades data reception and the minimum G/T value of 26.10 dB/K for the TerraSAR-X data reception. In general, the minimum G/T value for receiving the Pleiades and TerraSAR-X data is at 28 dB/K. While based on the calculation of antenna products availability in the market is require G/T value of 33.45 dB /K for the elevation of 5 degrees with a diameter of 7.5 mm antenna. This can be conclude that the antenna products meets the minimum requirements specification and to receive both satellite data. Â However, both calculation for the antenna subsystem still will be evaluated further in order to be directly installed at Parepare Remote Earth Station (SPBJ), South Sulawesi.
INTEGRATION OF GIS AND REMOTE SENSING FOR HOTSPOT DISTRIBUTION ANALYSIS IN BERBAK SEMBILANG NATIONAL PARK Andita Minda Mora; Bambang Hero Saharjo; Lilik Budi Prasetyo
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/ijreses.v16i1.13851

Abstract

Abstract. Remote sensing is composed of many interrelated processes to be able to consider physical objects such as buildings, land, and plants which are objects that can be discussed by applications discussed in various disciplines that discuss geology, forestry, soil science, and geography. The use of GIS and remote sensing for fire monitoring has been widely used. However, this study is the first study conducted in the TNBS area after the Berbak National Park (TNB) in Jambi to join the Sembilang National Park (TNS) in South Sumatra. Hotspot distribution in this study was obtained using Getis-Ord-Gi * statistics, hotspot data collected from 2000-2018 in the TNBS area. The results of the hotspot distribution during the 2000-2018 recorded by MODIS satellites with time acquisition and statistical analysis using Gi* show the results that the hotspots gathered (80% confidence level) outside the TNBS area, which is a mixed fields area. Further studies on causes of fire in terms of socio-economic and cultural needs to be done to get the right advice in reducing the risk of loss of forest cover and diversity in TNBS. Keywords: mitigation, hydrology, DAS
OBSERVING THE INUNDATED AREA USING LANDSAT-8 MULTITEMPORAL IMAGES AND DETERMINATION OF FLOOD-PRONE AREA IN BANDUNG BASIN Fajar Yulianto; Suwarsono; Sayidah Sulma; Muhammad Rokhis Khomarudin
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 2 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a3074

Abstract

Flood is the most frequent hydro-meteorological disaster in Indonesia. Flood disasters in the Bandung basin result from increasing population density, especially in the Citarum riverbank area, accompanied by land use changes in upstream of the Citarum catchment area which has disrupted the river’s function. One of the basic issues that need to be investigated is which areas of the Bandung basin are prone to flooding. This study offers an effective and efficient method of mapping flood-prone areas based on flood events that have occurred in the past through the use of historical remote sensing image data. In this research, Landsat-8 imagery was used to observe the inundated area in the Bandung basin in the past (2014–2018) using an improved algorithm, the modified normalized water index (MNDWI). The results of the study show that MNDWI is the appropriate parameter to be used to detect flooded areas in the Bandung basin area that have heterogeneous land surface conditions. The flood-prone area was determined based on flood events for 2014 to 2018, identified as inundated areas in the images. The estimation of the flood-prone area in the Bandung basin is 11,886.87 ha. Most of the flood-prone areas are in the subdistricts of Rancaekek, Bojongsoang, Solokan Jeruk, Ciparay, Cileunyi, Bale Endah and Cikancung. This area geographically or naturally is a water habitat area. Therefore, if the area will be used for residential, this will have consequences that flood will always be a threat to the area.Â
MANGROVE FOREST CHANGE IN NUSA PENIDA MARINE PROTECTED AREA, BALI - INDONESIA USING LANDSAT SATELLITE IMAGERY August Daulat; Widodo Setiyo Pranowo; Syahrial Nur Amri
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 2 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a2955

Abstract

Nusa Penida, Bali was designated as a Marine Protected Area (MPA) by the Klungkung Local Government in 2010 with support from the Ministry of Marine Affairs and Fisheries, Republic of Indonesia. Mangrove forests located in Nusa Lembongan Island inside the Nusa Penida MPA jurisdiction have decreased in biomass quality and vegetation cover. It’s over the last decades due to influences from natural phenomena and human activities, which obstruct mangrove growth. Study the mangrove forest changes related to the marine protected areas implementation are important to explain the impact of the regulation and its influence on future conservation management in the region. Mangrove forest in Nusa Penida MPA can be monitored using remote sensing technology, specifically Normalized Difference Vegetation Index (NDVI) from Landsat satellite imagery combined with visual and statistical analysis. The NDVI helps in identifying the health of vegetation cover in the region across three different time frames 2003, 2010, and 2017. The results showed that the NDVI decreased slightly between 2003 and 2010. It’s also increased significantly by 2017, where a mostly positive change occurred landwards and adverse change happened in the middle of the mangrove forest towards the sea.

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