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International Journal of Remote Sensing and Earth Sciences (IJReSES)

ijreses
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Published by Lembaga Penerbangan dan Antariksa Nasional

ISSN : 02166739 EISSN : 2549516X DOI : -

Core Subject : Science,

Earth & Planetary Sciences

International Journal of Remote Sensing and Earth Sciences (IJReSES) is expected to enrich the serial publications on earth sciences, in general, and remote sensing in particular, not only in Indonesia and Asian countries, but also worldwide. This journal is intended, among others, to complement information on Remote Sensing and Earth Sciences, and also encourage young scientists in Indonesia and Asian countries to contribute their research results. This journal published by LAPAN.

Arjuna Subject : -

Articles 320 Documents

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CAN THE PEAT THICKNESS CLASSES BE ESTIMATED FROM LAND COVER TYPE APPROACH? Bambang Trisakti; Atriyon Julzarika; Udhi C. Nugroho; Dipo Yudhatama; Yudi Lasmana
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 2 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Indonesia has been known as a home of the tropical peatlands. The peatlands are mainly in Sumatera, Kalimantan and Papua Islands. Spatial information on peatland depth is needed for the planning of agricultural land extensification. The research objective was to develop a preliminary estimation model of peat thickness classes based on land cover approach and analyse its applicability using Landsat 8 image. Ground data, including land cover, location and thickness of peat, were obtained from various surveys and peatlands potential map (Geology Map and Wetlands Peat Map). The land cover types were derived from Landsat 8 image. All data were used to build an initial model for estimating peat thickness classes in Merauke Regency. A table of relationships among land cover types, peat potential areas and peat thickness classes were made using ground survey data and peatlands potential maps of that were best suited to ground survey data. Furthermore, the table was used to determine peat thickness classes using land cover information produced from Landsat 8 image. The results showed that the estimated peat thickness classes in Merauke Regency consist of two classes, i.e., very shallow peatlands and shallow peatlands. Shallow peatlands were distributed at the upper part of Merauke Regency with mainly covered by forest. In comparison with Indonesia Peatlands Map, the number of classes was the two classes. The spatial distribution of shallow peatlands was relatively similar for its precision and accuracy, but the estimated area of shallow peatlands was greater than the area of shallow peatlands from Indonesia Peatlands Map. This research answered the question that peat thickness classes could be estimated by the land cover approach qualitatively. The precise estimation of peat thickness could not be done due to the limitation of insitu data.

GROWTH RATE AND PRODUCTIVITY DYNAMICS OF ENHALUS ACOROIDES LEAVES AT THE SEAGRASS ECOSYSTEM IN PARI ISLANDS BASED ON IN SITU AND ALOS SATELLITE DATA Agustin Rustam; Dietriech Geoffrey Bengen; Zainal Arifin; Jonson Lumban Gaol; Risti Endriani Arhatin
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 10, No 1 (2013)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Enhalus acoroides is the largest population of seagrasses in Indonesia. However, growth rate and productivity analyses of Enhalus acoroides and the use of satellite data to estimate its the productivity are still rare. The goal of the research was to analyze the growth rate, productivity rate,seasonal productivity of Enhalus acoroides in Pari island and its surroundings. The study was divided into two phases i.e., in situ measurments and satellite image processing. The field study was conducted to obtain the coverage percentage, density, growth rate, and productivity rate, while the satellite image processing was used to estimate the extent of seagrass. The study was conducted in August 2011 toJuly 2012 to accommodate all four seasons. Results showed that the highest growth rate andproductivity occurred during the transitional season from west Monsoon to the east Monsoon of 5.6cm/day and 15.75 mgC/day, respectively. While, the lowest growth rate and productivity occurred during the transition from east Monsoon to the west Monsoon of 3.93 cm/day and 11.4 mgC/day, respectively. Enhalus acoroides productivity reached its maximum during the west Monsoon at 1081.71 mgC/day/m2 and minimum during east Monsoon with 774.85 mgC/day/m2 . Based on ALOS data in 2008 and 2009, total production of Enhalus acoroides in the proximity of Pari islands reached its maximum occur during the west Monsoon (48.73 – 49.59 Ton C) and minimum during transitional season (16.4-16.69 Ton C). Potential atmospheric CO2 absorption by Enhalus acoroides in Pari island was estimated at the number 60.14 – 181.82 Ton C.

DEVELOPING TROPICAL LANDSLIDE SUSCEPTIBILITY MAP USING DINSAR TECHNIQUE OF JERS-1 SAR DATA Ilham Alimuddin; Luhur Bayuaji; Haeruddin C. Maddi; Josaphat Tetuko Sri Sumantyo; Hiroaki Kuzei
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 8, (2011)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Comprehensive information in natural disaster area is essential to prevent and mitigate people from further damage that might occur before and after such event. Mapping this area is one way to comprehend the situation when disaster strikes. Remote sensing data have been widely used along with GIS to create a susceptibility map. The objective of this study was to develop existing landslides susceptibility map by integrating optical satellite images of Landsat ETM and ASTER with Japanese Earth Resource Satellites (JERS-1) Synthetic Aperture Radar (SAR) data complemented by ground GPS and feature measurement into a Geographical Information Systems (GIS) platform. The study area was focused on a landslide event occurred on 26 March 2004 in Jeneberang Watershed of South Sulawesi, Indonesia. Change detection analysis was used to extract thematic information and the technique of Differential SAR Interferometry (DInSAR) was employed to detect slight surface displacement before the landslide event. The DInSAR processed images would be used to add as one weighted analysis factor in creating landslide susceptibility map. The result indicated that there was a slight movement of the slope prior to the event of landslide during the JERS-1 SAR data acquisition period of 1993-1998. Keywords: Optical Images, JERS-1 SAR, DInSAR, Tropical Landslide, GIS, Susceptibility Map 1. Introduction Recently, natural disasters increased in terms of frequency, complexity, scope, and destructive capacity. They have been particularly severe during the last few years when the world has experienced several large-scale natural disasters such as the Indian Ocean earthquake and tsunami; floods and forest fires in Europe, India and China, and drought in Africa (Sassa, 2005). Mapping such natural disaster areas is essential to prevent and mitigate people from further damage that might occur before and after such event. In Indonesia in particular, in these recent years natural disasters occurred more frequently compared to the last decade (BNPB, 2008). Once within a month in 2011, in three different islands, Indonesia was stricken by earthquake, tsunami, flash floods, and volcanic eruptions with severe fatalities to the people and environment. It was obvious that Indonesia was prone to natural disaster due to its position of being squeezed geologically by three major world plates and this fact makes Indonesia one of the most dangerous

Front Pages IJReSES Vol. 13, No. 1(2016) Editorial Journal
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 13, No 1 (2016)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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Front Pages IJReSES Vol. 13, No. 1(2016) *Note: This cover is a revision version of the Editorial Committee Preface section cover that was uploaded on May 26, 2017

THE DEVELOPMENT RESEARCH OF THE FISHING BOAT DISTINCTION TECHNIQUE BY SATELLITE-ONBOARD HIGH RESOLUTION OPTICAL SENSOR — DISTINCTION TECHNIQUE USING IKONOS DATA - T. MORIYAMA; - H. TAMEISHI; - J. SUWA; - S. KANNO; - Y. SUGIMORI; - T. OSAWA; - M. KOIWA
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 1,No. 1(2004)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

This paper describes the vessel distinction algorithm by using radiance silhoutte algorithm for IKONOS data. Although original TKONOS image has high spatial resolution about 1 m, it is difficult to identify whole feature of the vessel. The newly developed algorithm named "Radiance Silhoutte Analysis Algorithm" can estimate entire length, full width and bridge location of the vessel in high accuracy. By using targeted vessels, it is evaluated the algorithm has sufficient accuracy for vessel distinction. The research also covers synthetic collation decision by using vessel type axtraction algorithm. Keyword: IKONOS image, SPOT, ALOS image, high resolution image alogarithm, nearest neighbor interpolation, cubic convolution interpolation

ACCURACY EVALUATION OF STRUCTURE FROM MOTION THERMAL MOSAICING IN THE CENTER OF TOKYO Atik Nurwanda; Tsuyoshi Honjo; Nobumitsu Tsunematsu; Hitoshi Yokoyama
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 2 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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 Mosaicing”. 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.

INTERPOLATION METHODS FOR SEA SURFACE HEIGHT MAPPING FROM ALTIMETRY SATELLITES IN INDONESIAN SEAS Rossi Hamzah; Teguh Prayogo
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 1 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Altimetry satellite data, has a very low spatial resolution for using in determine fishing ground area. With very low spatial resolution is required interpolation method that can mapped Sea Surface Height (SSH) with a good result. SSH data from Global Near Real Time from AVISO, mapped in geographic projection and interpolated with Inverse Distance Weighting (IDW) and Ordinary Krigging method. This interpolation method are expected to know which the good method for mapped SSH data in resulting better information. The results of statistical calculation shows that RMSE value and standar deviations from kriging method is smaller than IDW method.

CLASSIFICATION OF POLARIMETRIC-SAR DATA WITH NEURAL NETWORK USING COMBINED FEATURES EXTRACTED FROM SCATTERING MODELS AND TEXTURE ANALYSIS Katmoko Ari Sambodo; Aniati Murni; Mahdi Kartasasmita
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 4,(2007)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

This paper shows a study on an alternative method for classification of polarimetric-SAR data. The method is designed by integrating the comined features extracted from two scattering models(i.e., freeman decomposition model and cloud decomposition model) and textural analysis with distribution-free neural network classifier. The neural network classifier (wich is based on a feedforward back-propagation neural network architecture) properly exploits the information in the combined features for providing high accuracy classification result. The effectiveness of the proposed method is demonstrated using E-SAR polarimetric data acquired on the area of Penajam, East Kalimantan, Indonesia. Keywords: Polarimetric-SAR, scattering model, freeman decomposition, Cloude decomposition, texture analysis, feature extraction, classification, neural networks.

DETECTION OF FOREST FIRE, SMOKE SOURCE LOCATIONS IN KALIMANTAN DURING THE DRY SEASON FOR THE YEAR 2015 USING LANDSAT 8 FROM THE THRESHOLD OF BRIGHTNESS TEMPERATURE ALGORITHM . Kustiyo; Ratih Dewanti; Inggit Lolitasari
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 12, No 2 (2015)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Almost every dry season, there are large forest/land fires in several regions in Indonesia, especially in Kalimantan and Sumatra in the dry season of August to September 2015 a forest fire in 6 provinces namely West Kalimantan, Central Kalimantan, South Kalimantan, Riau, Jambi, and South Sumatra. Even some parties proposed that the Government of Indonesia declares them as a national disaster. The low-resolution remote sensing data have been widely used for monitoring the occurrence of forest/land fires (hotspots), and mapping of burnt scars. The hotspot detection was done by utilizing the data of NOAA-AVHRR and MODIS data which have a lower spatial resolution (1 km). In order to increase the level of detail and accuracy of product information, this research is done by using Landsat 8 TIRS (Thermal Infrared Sensor) band which has a greater spatial resolution of 100 m. The purpose of this research is to find and to determine the threshold value of the brightness temperature of the TIRS data to identify the source of fire smoke. The data used is the Landsat 8 of several parts of Borneo during the period of 24 August to 18 September 2015 recorded by the LAPAN's receiving station. Landsat - 8 TIRS band was converted into brightness temperature in degrees Celsius, then dots in a region that is considered the source of the smoke if the temperature of each pixel in the region > 43oC, and given the attributes with the highest temperatures of the pixels in the region. The source of the smoke was obtained through visual interpretation of the objects in the multispectral Natural Color Composite (NCC) and True Color Composite (TCC) images. Analysis of errors (commission error) is obtained by comparing the temperature detected by TIRS band with a visual appearance of the source of the smoke. The result of the experiment showed that there were detected 9 scenes with high temperatures over 43oC from the 27 scenes Kalimantan Landsat 8 data, which include 153 sites. The accuracy (commission error) of identification results using temperature ≥ 51°C is 0%, temperature ≥ 47°C is 10%, and temperature ≥ 43°C is 30.5%.

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 (IJReSES) Vol 9, No 2 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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 - 28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.

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