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International Journal of Remote Sensing and Earth Sciences (IJReSES)
ISSN : 02166739     EISSN : 2549516X     DOI : -
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.
Articles 10 Documents
Search results for , issue " Vol 2(2005)" : 10 Documents clear
STUDY OF OCEAN PRIMARY PRODUCTIVITY USING OCEAN COLOR DATA AROUND JAPAN OSAWA, TAKAHIRO; FANG ZHAO, CHAO; Nuarsa, I WAYAN; Swardika, I Ketut; SUGIMORI, YASUHIRO
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (169.966 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1354

Abstract

Ocean primary production is an important factor for determining the ocean's role in global carbon cycle. In recent years, much more chlorophyll-a concentration data in the euphotic layer were derived from the satellite ocean color sensors. The primary productivity algorithms have been proposed based on satellite chlorophyll measurements (Piatt, 1988; Morel, 1991) and other environmental parameters such as sea surface temperature or mixed layer depth (Behrenfeld and Falkowski, 1997; Esaias, 1996; Asanuma, 2002). In order to estimate integrated primary productivity in the whole water column, the vertical distribution of chlorophyll concentration below the sea surface should be reconstructed based on satellite data. In this paper, the vertical profile data of chlorophyll-a (Chl-a) measured around Japan Islands from 1974 to 1994 were reanalyzed based on the shifted-Gaussian shape proposed by Piatt et al (1988). Using this statistical model (neural network) and the photosynthesis irradiance parameters from Asanuma (2002), the distribution of primary productivity and its seasonal variation around Japan islands were estimated from SeaWiFS data, and the results were compared with in situ data and the other two models estimated from VGPM and mixed layer depth model. Keywords: ocean color, primary productivity, chlorophyll profile, artificial neural network
STUDY OF MODIS-AQUA DATA FOR MAPPING TOTAL SUSPENDED MATTER (TSM) IN COASTAL WATERS TRISAKTI, BAMBANG; PARWATI, -; BUDIMAN, SYARIF
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (439.756 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1355

Abstract

The MODIS-Aqua data have been studied to map TSM distribution in coastal waters. TSM algorithm model for MODIS data with spatial resolution of 250 m, 500 m and 1000 m was developed by correlating the TSM derived from spectral values of MODIS and the TSM derived from Landsat-7 ETM data using the calibrated algorithm. Statistical test was conducted to see normality of data and level of influence from both parameters. Analysis was conducted to see the change of spectral value from bands of MODIS data with resolution of 1000 m towards the change of level of TSM concentration. The results shows that the TSM algorithm model is in the form of power (Xa) with the highest correlation coefficient is obtained from the correlation between the Landsat TSM value with the quantification of band 1 and band 2 of MODIS data for spatial resolution 250 m, ratio of band 4 and band 3 for spatial resolution 500 m, and ratio of band 13 and 11 for spatial resolution 1000 m. The pattern of TSM distribution in coastal waters can be identified in more accurate using MODIS data with resolution of 250 m and 500 m. The analysis result of the curve of MODIS spectral value data with resolution 1000 m shows that the change of TSM concentration influences significantly to the form of curve of spectral value, especially for band 11 - 16 ( visible green, red and NIR). Keywords : MODIS-Aqua, Landsat, TSM algorithm model, spatial resolution, curve of spectral value
NUMERICAL CALCULATION FOR THE RESIDUAL TIDAL CURRENT IN BENOA BAY-BALI ISLAND HENDRAWAN, GEDE; NUARSA, I WAYAN; SANDI, WAYAN; A.F. KOROPITAN, -; SUGIMORI, YASUHIRO
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (367.613 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1362

Abstract

Princeton Ocean Model (POM) was used to calculate the tidal current and M2-residual current in Benoa Bay using barotropic model (mode 2). The model was forced by tidal elevation, which was given along the open boundary condition using tide data prediction from Hydro-Oceanography Division-Indonesian Navy (DISHIDROS TNI-AL). The computed tidal current and residual current have been compared with both data in Benoa Bay, that are data of the open boundary of Benoa Bay and condition of Benoa Bay after developed a port and reclamation of Serangan Island. The maximum velocity of tidal current for open boundary conditions at flood tide is 0.71 m/sec, whereas at ebb tide is 0.65 m/sec and the maximum velocity after developed a port and reclamation of Serangan Island, at flood tide, is 0.69 m/sec. The simulation of residual current with particular emphasis on predominant constituent of M2 after developed a port and reclamation of Serangan Island shows a strong flow at the western part of Tanjung Benoa and Benoa Harbor and also at bay mouth between Serangan Island and Tanjung Benoa. Maximum velocity of M2-residual current is 0.0585 m/sec by the simulation and showed that the current which was produced forming two eddies in the bay of which one eddy is in the mouth of bay in southern part. The residual current for open boundary condition of bay shows four eddies circulation, one big eddies and the others small. The anticlockwise circulation occurs in the inner part of the bay. Key words: model, simulation, tidal current, residual current
VERTICAL DISTRIBUTION OF CHLOROPHYLL-A BASED ON NEURAL NETWORK OSAWA, TAKAHIRO; FANG ZHAO, CHAO; Nuarsa, I WAYAN; SWARDIKA, I KETUT; SUGIMORI, YASUHIRO
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (247.432 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1353

Abstract

An algorithm of estimating Vertical distribution of Chlorophyll-a (Chl-a) was evaluated based on Artificial Neural Networks (ANN) method in Hokkaido field in the northwest of Pacific Ocean. The algorithm applied to the data of SeaWiFS on OrbView-2 and AVHRR on NOAA off Hokkaido, has been applied on September 24, 1998 and September 28, 2001. Ocean color sensor provides the information of the photosynthetic pigment concentration for the upper 22% of the euphotic zone. In order to model a primary production in the water column derived from satellite, it is important to obtain the vertical profile of Chl-a distribution, because the maximum value of Chl-a concentration used to lie in the subsurface region. A shifted Gaussian model has been proposed to describe the variation of the chlorophyll-a (Chl-a) profile which consists of four parameters, i.e. background biomass (B0), maximum depth of Chl-a (zm), total biomass in the peak (h), and a measurement of the thickness or vertical scale of the peak (cr). However, these parameters are not easy to be determined directly from satellite data. Therefore, in the present study, an ANN methodology is used. Using in-situ data from 1974 to 1994 around Japan Islands, the above four parameters are calculated to derive the Chl-a concentration, sea surface temperature, mixed layer depth, latitude, longitude, and Julian days. The total of 6983 profiles of Chl-a and temperature are used for ANN. The correlation coefficients of these parameters are 0.79 (B0), 0.73 (h), 0.76 (cr) and 0.79 (zm) respectively. A site called A-linc off Hokkaido is used to evaluate Chl-a concentration in each depth. After comparing with in-situ data and ANN model, the results show good agreement relatively. Therefore, the ANN method is applicable and available tool to estimate primary production and fish resources from the space. Keywords : Ocean color, Chlorophyll-a (Chl-a), Vertical structure, Artificial Neural Networks (ANN).
SPECTRAL CHARACTERISTIZATION OF RICE FIELD USING MULTITEMPORAL LANDSAT ETM+ DATA NUARSA, I WAYAN; KANNO, SUSUMU; SUGIMORI, YASUHIRO; NlSHIO, FUMIHIKO
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (149.215 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1359

Abstract

The preliminary study using Landsat ETM+ to estimate the rice production in Regency of Tabanan, Bali Province was conducted. The objectives of this study were to know spectral characteristic of rice plant in three importance growth periods of rice, and to develop a model to identify the distribution of rice. Landsat ETM+ in two acquisition dates (March 21st, 2003 and May 24*, 2003) were used in this study. Characteristics of rice were analyzed using radiance value of Landsat ETM+ obtained from converting digital number of Landsat data. Multi-variable linear regression analysis was developed to classify the rice in its growth period. The result showed that the rice plant has different reflectance in seedling-development period, ear differentiation period and maturation period. It is expressed by the radiance value of Landsat ETM+. However, spectral characteristic of rice in each band of Landsat ETM+ is similar to the green vegetations in general, except in blue band (Bl). Based on statistical analysis, the classification of rice in each its growth period can be classified. Key words: Rice field, Landsat ETM+, Spectral Characteristic, Multi-temporal.
CORAL REEF HABITAT CHANGING ASSESSMENT OF DERAWAN ISLANDS, EAST KALIMANTAN, USING REMOTE SENSING DATA NURLIDIASARI, MARLINA; BUDIMAN, SYARIF
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (375.511 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1356

Abstract

Coral reefs in Dcrawan Islands are astonishingly rich in the marine diversity. However, these reefs are threatened by humans. Destructive fishing methods, such as trawl, blasting and cyanide fishing practise, are found to be the main cause of this degradation. The coral reefs habitat reduction is also caused by tourism activities due to trampling over the reef and charging organic and anorganic wastes. The capabilities of satellite remote sensing techniques combined with field data collection have been assessed for the coral reef mapping and the change detection of Derawan Island. Multi-temporal Landsat TM and ETM images (1991 and 2002) have been used. Comparison of the classified images of 1991 and 2002 shows spatial changes of the habitat. The changes were in accordance with the known changes in the reef conditions. The analysis shows the decrease of the coral reef and patchy seagrass percentage, while the increase of the algae composite and patchy reef percentage. Keywords : Coral Reef, Change Detection, Landsat-TM, Derawan
THE APPLICATION OF WAVELET ANALYSIS FOR INTERNAL WAVE DETECTION IN SAR AND OPTICAL IMAGES DATA OVER TSUSHIMA STRAIT ARVELYNA, YESSY
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (154.581 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1360

Abstract

On this paper, wavelet analysis has been used for internal wave detection in ERS SAR and ASTER images data over Tsushima strait, southwest of Japan, during 1993-2004 period. Various wavelet transforms, such as Haar wavelet, Symlet wavelet, Coif wavelet, Daubechies wavelet, and Discreet Meyer wavelet, are tested comparably with different level of synthesize image on horizontal, diagonal, and vertical detail, and approximation to study the internal wave characteristic in image. Internal wave features were detected as elongated pattern in image with higher wavelet coefficient (>36) than sea surface (litlle than 10) on horizontal and vertical detail coefficient of image transforms at level 2-5. The decomposition image shows the tendency that the decomposition of internal wave feature using wavelet transform tends to follow the wavelet function. This may reduced the height of leading wave. Smoother result of internal wave shape can be formed using higher scale resolution of image and higher number of vanishing moments such as Daubechies waveletdb5, Symlet wavelet-sym5, and Discrete Meyer wavelet. The compactly supported wavelet function with orthogonal basis with scale function and FIR filter, such as discrete Meyer function is proposed for smoothness of feature, space save coding, and to avoid depashing in image. So far, the detection processes were performed well on the internal waves data that occurred at north coast off Kitakyushu and NW/W/SW/E coast off Tsushima Island on June to September period whose lengths were detected between 6-28 km and wavelength between 120m-1.28km. The directions of internal wave propagation were varied between NW-SW at eastern channel and N-SW at western channel of Tsushima Strait. Keywords: wavelet analysis, SAR image, optical image, internal wave.
THE ASSESSMENT OF PELAGIC FISH STOCK AND ITS DISTRIBUTIONS IN INDIAN OCEAN BY SPLIT BEAM ACOUSTIC SYSTEM ARNAYA, I NYOMAN
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (150.663 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1361

Abstract

The assessment of pelagic fish stock and its distribution in Indian Ocean, especially southern part of Java-Bali-Lombok, was conducted by SIMRAD EK-500 Split-beam Acoustic System, in October-November 2001. The research was carried out by R/V Baruna Jaya VII of Indonesia Institute of Science (LIPI), under the Fish Stock Assessment Project in Indonesian Waters of fiscal year 2001. As a result, it can be reported that (I) the dominant species of pelagic fish distributed in this area is small pelagic fish with target strength (TS) values between -54.00 dB to - 37.60 dB, absolute density of between 0.07 to 218 fish/1000 m\ and total fish stock of 526.570 ton/year; (2) the large pelagic fish (some species of tuna) also distributed in the area with average TS of -27 dB, absolute density between 0.00 to 0.07 fish/100 m\ and total fish stock of 386,260 ton/year. This result still needs more accurate verification, especially on the species composition and individual size of fish by a more appropriate biological sampling method (mid-water trawl). Consequently, more acoustical surveys combined with oceanographic sampling and exploratory fishing are needed to evaluate the existing condition of marine fish resources in the area, in order to optimize and set up the relevant and accurate fisheries management plan for suitable and responsible utilization offish resources. Keywords: Split-beam Acoustic System, Fish Stock Assessment, Target Strength, Density, Distribution, Indian Ocean (southern part of Java-Bali-Lombok).
MAPPING CORAL REEF HABITAT WITH AND WITHOUT WATER COLUMN CORRECTION USING QUICKBIRD IMAGE NURLIDIASARI, MARLINA; BUDIMAN, SYARIF
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (460.55 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1357

Abstract

Remote sensing from space offers an effective approach to solve the limitation of field sampling, in particular to monitor the reefs in remote sites. Moreover, using the achieved remotely sensed data, it is even possible to monitor the historic status of the coral reef environment. The capabilities of satellite remote sensing techniques combined with the field data collection have been assessed for generating coral reef habitat mapping of the Derawan Island. A very high spatial resolution multi-spectral QuickBird image (October 2003) has been used. The capability of QuickBird image to generate a coral reef habitat map with the water column correction by applying the Lyzenga method, and also without the water column correction by the applying maximum likelihood method, have been assessed. The classification accuracy of the coral reef habitat map increased after the improvement of the water column effects. The classification of QuickBird image for coral reef habitat mapping increased up to 22% by applying a water column correction. Keywords : Coral Reef, Quickbird, Water Column Correction
DEVELOPMENT OF THE NEW ALGORITHM FOR MANGROVE CLASSIFICATION NUARSA, I WAYAN; SANDI ADNYANA, I WAYAN; SUGIMORI, YASUHIRO; KANNO, SUSUMU; NISHIO, FUMIHIKO
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (253.121 KB) | DOI: 10.30536/j.ijreses.2005.v2.a1358

Abstract

The objective of the study is to develop the algorithm for mangrove classification and density. Regression and correlation analysis was used to perform the equation. CE1 = (0.663*Band 3) + (0.l55 *Band 4) - (l.4*Band 5) + 0.995 And CE2 = 36 * Band 4 + 6*Band 5 + Band 3 were two formula that have been used to classify the mangrove. The object will be classified as mangrove when the value of CE1 is between -31.439 and 0.888, and value of CE2 is greater than or equal to 2000. On the other hand, density of the mangrove was expressed as DE = (2 * Band 4)/(Band 1+Band 3). Mangrove classification result in this study was similar to those of the existing methods. Statistical approach in this study generally gives the higher result tendency than other methods. Key words: Mangrove, Landsat ETM+, Empirical Model, Image Classification

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