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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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THREE-WAY ERROR ANALYSIS OF SEA SURFACE TEMPERATURE (SST) BETWEEN HIMAWARI-8, BUOY, AND MUR SST IN SAVU SEA Bambang Sukresno; Rizki Hanintyo; Denny Wijaya Kusuma; Dinarika Jatisworo; Ari Murdimanto
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 1 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Variance errors of Himawari-8, buoy, and Multi-scale Ultra-high Resolution (MUR) SST in Savu Sea have been investigated. This research used level 3 Himawari-8 hourly SST, in situ measurement of buoy, and daily MUR SST in the period of December 2016 to July 2017. The data were separated into day time data and night time. Skin temperature of Himawari-8 and subskin tempertaure of MUR SST were corrected with the value of 15âˆ†Tdept"> before compared with buoy data. Hourly SST of Himawari-8 and buoy data were converted to daily format by averaging process before collocated with MUR SST data. The number of 2,264 matchup data are obtained. Differences average between Himawari-8, buoy and MUR SST were calculated to get the value of variance (Vij). Using three-way error analysis, variance errors of each observation type can be known. From the analysis results can be seen that the variance error of Himawari-8, buoy and MUR SST are 2.5 oC, 0.28oC and 1.21oC respectively. The accuracy of buoy data was better than the other. With a small variance errors, thus buoy data can be used as a reference data for validation of SST from different observation type.

BATHYMETRY DATA EXTRACTION ANALYSIS USING LANDSAT 8 DATA Kuncoro Teguh Setiawan; Syifa Wismayati Adawiah; Yennie Marini; Gathot Winarso
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 13, No 2 (2016)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

The remote sensing technique can be used to produce bathymetric map. Bathymetric mapping is important for the coastal zone and watershed management. In the previous study conducted in Menjangan Island of Bali, bathymetric extractin information from the top of the atmosphere (TOA) reflectance image of Landsat ETM+ data has R2 = 0.620. Not optimal correlation value produced is highly influenced by the reflectance image of Landsat ETM+ data, were used, hence the lack of the research which became the basis of the present study. The study was on the Karang Lebar water of Thousand Islands, Jakarta. And the aim was to determine whether there was an increased correlation coefficient value of bathymetry extraction information generated from Surface reflectance and TOA reflectance imager of Landsat 8 data acquired on August 12, 2014. The method of extraction was done using algorithms Van Hengel and Spitzer (1991). Extraction absolute depth information obtained from the model logarithm of Landsat 8 surface reflectance images and pictures TOA produce a correlation value of R2 = 0.663 and R2 = 0.712.

MAPPING CORAL REEF HABITAT WITH AND WITHOUT WATER COLUMN CORRECTION USING QUICKBIRD IMAGE MARLINA NURLIDIASARI; SYARIF BUDIMAN
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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

ANALYSIS OF SEA SURFACE HEIGHT ANOMALY CHARACTERISTICS BASED ON SATELLITE ALTIMETRY DATA (CASE STUDY: SEAS SURROUNDING JAVA ISLAND) Sartono Marpaung; Wawan K. Harsanugraha
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 2 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Sea surface height anomaly is a oceanographic parameter that has spatial and temporal variability. This paper aims to determine the characters of sea surface height anomaly in the south and north seas of Java Island. To find these characters, a descriptive analysis of monthly anomaly data is performed spatially, zonally and temporally. Based on satellite altimetry data from 1993 to 2010, the analysis shows that the average of sea surface height anomaly varies, ranging from -15 cm to 15 cm. Spatially and zonally, there are three patterns that can be concidered as sea surface height anomaly characteristics: anomaly is higher in coastal areas than in open seas, anomaly is lower in coastal areas than in open seas and anomaly in coastal area is almost the same as in open seas. The first and second patterns occur in the south and north seas of Java Island. The third pattern occurs simultaneously in south and north seas of Java Island. Characteristics of temporal anomaly have a sinusoidal pattern in south and north seas of Java Island.

DETERMINATION OF THE BEST METHODOLOGY FOR BATHYMETRY MAPPING USING SPOT 6 IMAGERY: A STUDY OF 12 EMPIRICAL ALGORITHMS Masita Dwi Mandini Manessa; Muhammad Haidar; Maryani Hartuti; Diah Kirana Kresnawati
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 2 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

For the past four decades, many researchers have published a novel empirical methodology for bathymetry extraction using remote sensing data. However, a comparative analysis of each method has not yet been done. Which is important to determine the best method that gives a good accuracy prediction. This study focuses on empirical bathymetry extraction methodology for multispectral data with three visible band, specifically SPOT 6 Image. Twelve algorithms have been chosen intentionally, namely, 1) Ratio transform (RT); 2) Multiple linear regression (MLR); 3) Multiple nonlinear regression (RF); 4) Second-order polynomial of ratio transform (SPR); 5) Principle component (PC); 6) Multiple linear regression using relaxing uniformity assumption on water and atmosphere (KNW); 7) Semiparametric regression using depth-independent variables (SMP); 8) Semiparametric regression using spatial coordinates (STR); 9) Semiparametric regression using depth-independent variables and spatial coordinates (TNP), 10) bagging fitting ensemble (BAG); 11) least squares boosting fitting ensemble (LSB); and 12) support vector regression (SVR). This study assesses the performance of 12 empirical models for bathymetry calculations in two different areas: Gili Mantra Islands, West Nusa Tenggara and Menjangan Island, Bali. The estimated depth from each method was compared with echosounder data; RF, STR, and TNP results demonstrate higher accuracy ranges from 0.02 to 0.63 m more than other nine methods. The TNP algorithm, producing the most accurate results (Gili Mantra Island RMSE = 1.01 m and R2=0.82, Menjangan Island RMSE = 1.09 m and R2=0.45), proved to be the preferred algorithm for bathymetry mapping.

IDENTIFICATION OF INUNDATED AREA USING NORMALIZED DIFFERENCE WATER INDEX (NDWI) ON LOWLAND REGION OF JAVA ISLAND - Suwarsono; Jalu Tejo Nugroho; - Wiweka
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 10, No 2 (2013)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Flood disaster is a major issues due to its frequently events on several areas in Indonesia. Delineation of inundated area caused by flood is needed to support disaster emergency response. The objective of this research was to identify inundated areas using NDWI methos from Landsat TM/ETM+ data on lowland regions of Java island. A pair of the data (before and during the flood) were in each observation areas. Observation areas were selected in several location of lowland regions of Java island where great event of flood occurred during the last decades. The thresholds values of NDWI change were used to separate the flood and non flood areas. The results showed that the extent of inundated area caused by flood on lowland regions can be identifyed and separated based on NDWI variables extracted from Landsat TM/ETM+.

COMBINATION OF SPECKLE DIVERGENCE AND NEIGHBORHOOD ANALYSIS TO CLASSIFY SETTLEMENT FROM TERASAR-X DATA Rokhis Komarudin; Agung Indrajit
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Abstract. The objectives of this research were to develop and improve methods for determination of settlements area with focus on synthetic aperture radar (SAR) data. Remote sensing settlement classification has made great progress, both for optical and radar data as well for their fusion. Yet, in radar imagery, settlement classification still contains some problems. Several studies on application of radar imagery have been conducted using techniques such as textural analysis, multi-temporal analysis, statistical model, spatial indexes, and object-based classification. Most of the development methods have several problems in the specific area especially in the tropical country. Several studies also showed that settlement classification accuracies were just below 60%. This was not sufficient enough to classify settlement areas using SAR imagery. Therefore, in this research, we proposed a new method i.e., the combination of the speckle divergence and the neighborhood analysis. The proposed method was applied to classify settlement area in Cilacap and Padang Districts of Indonesia. The results showed that the proposed method produced a good accuracy i.e., 85.5% for Cilacap Districts and 78.1% for Padang Districts.

FISH SCHOOL IDENTIFICATION IN THE BALI STRAIT USING ACOUSTIC DESCRIPTOR AND ARTIFICIAL NEURAL NETWORKS TECHNIQUES INDRA JAYA; WAYAN SRIYASA
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 1,No. 1(2004)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Accurate fish school identification is one of the crucial pieces of information for fish stock assessment. The fish stock assessment, in turn, is used as a basis for fisheries management action plan. In this paper, we discuss the development and application of acoustic descriptor (AD) and artificial neural networks (ANN) technique for fish school identification. Data (echogram) was obtained from the acoustic survey conducted in November 2000 in the Bali Strait, using SIMRAD EK500 split-beam acoustic system. In this preliminary study, the usage of AD is confined to the geometrical properties (area, perimeter, height, length, elongation, circularity, rectangular, and fractal dimension) of the echogram or acoustic backscattering images, while the ANN used back-propagation technique and a sigmoid activation function to transform the input to output. The results show that the accuracy of identifying fish school for various ANN learning rate value is about 73.3%. We observed that the school of Lemuru Sardinella lemuru, which is dominant in the Strait of Bali during the time of the survey, takes elongated geometrical formation and occupied particular water depth. Future study will incorporate the more complete set of AD, for example by employing the energetic dimension, to improve the accuracy of the school identification. Keywords: school identification, acoustic descriptor, artificial neural networks

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 (IJReSES) Vol 15, No 2 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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.

DETECTING THE SPATIAL DISTRIBUTION OF SETTLEMENTS ON VOLCANIC REGION USING IMAGE LANDSAT-8 OLI IMAGERY . Suwarsono; M. Rokhis Khomarudin
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 1 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Geologically, Indonesia region is on track ring of fire, brings the consequence that the danger of volcanic eruption could occur at any time. Information sites where the settlement is located in the affected areas on emergency response process is needed in quick time. The availability of up to date data is important because it illustrates the actual condition of the region. Active volcanic landforms ranging from the crater to footslope in general is prone area to volcanic eruption, either by the threat of lava flows, pyroclastic falls, or lahars. This study aims to detect the spatial distribution of the settlement on volcanic region using Landsat-8 OLI. Parameters used for the detection of settlements is Normalized Difference Build-up Index (NDBI). Research methods include radiometric correction, delineation of the boundaries of volcanic landforms, NDBI value extraction, extraction of settlement areas, as well as the accuracy assesment. Study area is Sinabung Volcano region located in the province of North Sumatera. Recently, the volcano experienced a devastating and catastrophic eruption. The results showed that the spatial distribution of settlements on volcanic landforms can be detected quickly from Landsat-8 OLI based on NDBI parameters with a sufficient degree of accuracy.

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