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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 8 Documents
 1 
Search results for , issue "Vol. 9 No. 2 (2012)" : 8 Documents clear
THE USE OF MODIS DATA TO EXTRACT A DUST STORM PRODUCT Faten G. Abed; Abed Alkareem Abed Ali; Eshtar H. Nasser
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1828

Abstract

Iraq in the summer is affected by low pressure centered in the area of Arabian Sea and the Indian Ocean, and the high pressure region in the plateau of Anatolia. This climate system causes that the Shamal wind blows from the plateau of Anatolia in the north and northwest with relatively cold temperature. From mid-June to mid-September, the wind is accompanied with intensive heating of the earth surface causing dust storms rising up to thousand meters in the atmosphere above Iraq region. In recent years, the frequency of dust storm events was increased in Iraq and its surrounding regions due to the long drought seasons. Unsupervised classification method was used to determine the intensity of the dust storm and to identify the area of dust cloud. In this study, we were able to map dust storm over Iraq region using MODIS Terra and Aqua satellite data within thermal bands (band 31 and 32), and visible band VIS (band 1). Other thermal band (band 21) was used to produce RGB composite image specifying the dust storm. A spectral subtraction between two bands was also used to produce another RGB composite image to obtain better detection for the dust storm over Iraq region.
COMPARISON ANALYSIS OF INTERPOLATION TECHNIQUES FOR DEM GENERATION USING CARTOSAT-1 STEREO DATA Andie Setiyoko; Anil Kumar
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1829

Abstract

Digital Elevation Model (DEM) can be generated using several techniques such as photogrammetric technique, interferometry, Lidar, etc. In photogrammetric technique, a DEM generation using stereo images, accuracy of generated DEM is also dependent on interpolation techniques. The process of interpolation is conducted to generate DEM as a continuous data from the point map that contained height information as a discrete data. In this research, point map was extracted from Cartosat-1 stereo image and from geodetic single frequency GPS in differential mode. Different interpolation techniques were applied on these data sets with different combination within these data sets. In this study, analysis of DEM interpolation was conducted with deterministic interpolators such as inverse distance weighted (IDW), global polynomial, local polynomial, and radial basis functions (RBF); and probabilistic interpolators such as simple kriging, ordinary kriging, universal kriging, indicator kriging, probabilistic kriging, disjunctive kriging, and cokriging. The accuracy of generated DEMs through different interpolation techniques were evaluated with ground point data collected from geodetic single frequency GPS in differential mode. Based on the analysis, the range error of DEMs generated was between 1.29 m to 2.96 m. Interpolation method with the least error was ordinary kriging using point map data and GPS points, while the highest error was obtained from global polynomial method.
THE EFFECT OF THE EXTENT OF CORAL REEF AREA ON UNIFORM BOTTOM REFLECTANCE DETERMINATION FOR WATER COLUMN CORRECTION USING LANDSAT ETM Syarif Budhiman; Ety Parwati; Emiyati
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1830

Abstract

In one pixel of 30 meter spatial resolution of Landsat ETM multispectral sensor might consist of mixed bottom substrate types. The influence of a mixture of bottom substrate on the Landsat data can be a source of errors and together with the extent of coral reef area might contribute to affect the determination of uniform bottom reflectance. This study aimed to assess the effect of the extent of coral reef area on uniform bottom reflectance determination for water column correction. Lyzenga method was used for water column correction. This study carried out in two case studies using two sites with different size of coral reef ecosystems area i.e., Tidung island, in the Province of Jakarta and Maratua island, in the Province of East Kalimantan. Tidung island was selected to represent small area of coral reef ecosystem, while Maratua island was selected to represent relatively larger area of coral reef ecosystem. The results showed that the extent of coral reef influenced the determination of training sample areas for uniform bottom reflectance using Landsat ETM. The combination of moderate spatial resolution and the small area of coral reef ecosystem lead to the difficulties for uniform bottom substrate type determination at different depths.
NEW AUTOMATED CLOUD AND CLOUD-SHADOW DETECTION USING LANDSAT IMAGERY Kustiyo; Dianovita; Hedi Ismaya; Mulia Inda Rahayu; Erna Sri Adiningsih
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1831

Abstract

Cloud cover has become a major problem in the use of optical satellite imageries, particularly in Indonesian region located along equator or tropical region with high cloud cover almost all year round. In this study, a new method for cloud and cloud shadow detection using Landsat imagery for specific Indonesian region was developed to provide a more efficient and effective way to detect clouds and cloud shadows. Landsat Top of Atmosphere (TOA) reflectance and Brightness Temperature (BT) were used as inputs into the model. The first step was to detect cloud based on cloud physical properties using albedo and thermal bands, the second step was to detect cloud shadows using the Near Infrared (NIR), and Short Wave Infrared (SWIR) bands, and finally, the geometric relationships were used to match the cloud and cloud shadow layer, before proceeding to the production of the final cloud and cloud shadow mask. The results were then compared with other method such as tree base cloud separation. It showed that method we proposed could provide better result than tree base method, the accuracy result of this method was 98.75%.
SEMI-AUTOMATIC SHIP DETECTION USING PI-SAR-L2 DATA BASED ON RAPID FEATURE DETECTION APPROACH Katmoko Ari Sambodo
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1832

Abstract

Synthetic Aperture Radar (SAR) satellite an active sensor offering unique high spatial resolution regardless of weather conditions can operate both day and night time with wide area coverage. Therefore, SAR satellite can be used for monitoring ship on sea surface. This study showed on an alternative method for ship detection of SAR data using Pi-SAR-L2 (L-band, JAXA-Airborne SAR) data. The ship detection method is this study was consisted of eight main stages. After the Pi-SAR data was registered and speckle was filtered, then the land was masked using SRTM-DEM (Shuttle Radar Topography Mission-Digital Elevation Model) data since most ship detectors produced false detections when it applied to land areas. A ship sample image was then selected (cropped). The next step was to detect some unique keypoints of ship sample image using Speeded Up Robust Features (SURF) detector. The maximum distance (‘MaxDist’) of keypoints was also calculated. The same detector was then applied to whole Pi-SAR imagery to detect all possible keypoints. Then, for each detected keypoint, we calculated distance to other keypoint (‘Dist’). If ‘Dist’ was smaller than ‘MaxDist’, then we marked these two (or more) keypoints as neighboring keypoints. If the number of neighbor keypoints was equal or greater than two, finally we marked these keypoints as ‘Detected Ship’ (draw rectangle and show its geographic position). Results showed that our method can detect successfully 32 ‘possible ships’ from Pi-SAR-L2 data acquired on the area of North Sulawesi, Indonesia (August 8, 2012).
SITE SELECTION OF SEAWEED CULTURE USING SPOT AND LANDSAT SATELLITE DATA IN PARI ISLAND Bidawi Hasyim; Wawan K. Harsanugraha; Yennie Marini; Anneke K.S. Manoppo
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1833

Abstract

One of several factors for seaweed culture success is to determine the suitable location for seaweed culture based on oceanographic parameters. The best location for seaweed culture is coastal waters with suitable requirements for total suspended solid (TSS), sea surface temperature (SST), and area with calm water that is sheltered from waves, strong current and predator, such as lagoon in the middle of an atoll. The purpose of this study was to locate the suitable area for seaweed culture in Pari island, Seribu island using SPOT and LANDSAT-TM data. The results showed that TSS in Pari island waters were in the range of 150 mg/l - 200 mg/l, SST in the range of 22-29°C, while coral reefs and lagoon was only available in some coastal locations. The analysis showed that most of Pari island waters were suitable for seaweed culture.
COASTAL UPWELLING UNDER THE INFLUENCE OF WESTERLY WIND BURST IN THE NORTH OF PAPUA CONTINENT, WESTERN PACIFIC Harold J.D.Waas; Vincentius P. Siregar; Indra Jaya; Jonson Lumban Gaol
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1837

Abstract

Coastal upwelling play an important role in biological productivity and the carbon cycle in the ocean. This research aimed to examine the phenomenon of coastal upwelling that occur in the coastal waters north of Papua continent under the influence of Westerly Wind Burst(WWB) prior to the development of El Nino in the Pacific. Data consisted of sea surface temperature, vertical oceanic temperature, ocean color satellite image, wind stress and vector wind speed image, sea surface high, and Nino 3.4 index. Coastal upwelling events in the northern coastal waters of Papua continent occurred in response to westerly winds and westerly wind burst (WWBs) during December to March characterizing by low sea surface temperature (SST) (25 - 28ï‚°C), negative sea surface high deviation and phytoplankton blooming, except during pre-development of the El Nino 2006/2007 where weak upwelling followed by positive sea surface high deviation. Strong coastal upwelling occurred during two WWBs in December and March1996/1997 with maximum wind speed in March produced a strong El Nino 1997/1998. Upwelling generally occurred along coastal waters of Jayapura to Papua New Guinea with more intensive in coastal waters north of Papua New Guinea indicated by Ekman transport and Ekman layer depth maximum.
DROUGHT AND FINE FUEL MOISTURE CODE EVALUATION: AN EARLY WARNING SYSTEM FOR FOREST/LAND FIRE USING REMOTE SENSING APPROACH Yenni Vetrita; Indah Prasasti; Nanik Suryo. Haryani; M. Priyatna; M. Rokhis Khomarudin
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1841

Abstract

This study evaluated two parameters of fire danger rating system (FDRS) using remote sensing data i.e. drought code (DC) and fine fuel moisture code (FFMC) as an early warning program for forest/land fire in Indonesia. Using the reference DC and FFMC from observation data, we calculated the accuracy, bias, and error. The results showed that FFMC from satellite data had a fairly good correlation with FFMC observations (r=0.68, bias=7.6, and RMSE=15.7), while DC from satellite data had a better correlation with FFMC observations (r=0.88, bias=49.91, and RMSE=80.22). Both FFMC and DC from satellite and observation were comparable. Nevertheless, FFMC and DC satellite data showed an overestimation values than that observation data, particularly during dry season. This study also indicated that DC and FFMC could describe fire occurrence within a period of 3 months before fire occur, particularly for DC. These results demonstrated that remote sensing data can be used for monitoring and early warning fire in Indonesia.

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