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International Journal of Remote Sensing and Earth Sciences (IJReSES)
ISSN : 02166739     EISSN : 2549516X     DOI : -
Core Subject : Science,
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
STUDY ON LAND SURFACE TEMPERATURE CHARACTERISTICS OF HOT MUD ERUPTION IN EAST JAVA, INDONESIA Luhur Bayuaji; Hiroshi Watanabe; Hideyuki Tonooka; Josaphat Tetuko Sri Sumantyo; Hiroaki Kuze
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 6,(2009)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1576.275 KB) | DOI: 10.30536/j.ijreses.2009.v6.a1235

Abstract

hot mud has erupted in sidoarjo, east Java, Indonesia since 29 May 2006. It started as natural gas exploration project and punctured a geological structure at a depth of 2,8 km, releasing unprecedented volume of hot mud volcano (5x104 mcubix per day). By November 2006, it was estimated that hot mud had spread over (2,89 plus minus 0,10) x 106 m, swamping several villages with more than 10.000 people evacuated. In this research, by employing the advantage of spatial perspective of remote sensing imagery, the extent of hot mud spreading area and temperature distributions are derived from satellite images of the advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER) sensor onboard the Terra satellite. The mud spreading are was calculated using three visible or near infrared channels having a resolution of 15 m. Temperature distributions were calculated using the temperature or emissivity separation (TES) method on five thermal infraredchannels with a resolution of 90 m. The standard and water vapor scaling (WVS) methods were applied in the atmospheric correction process prior to the TES process. The result showed that the mud continued spreading during five months after the eruption. After 3-5 months from the eruption, the estimated temperature was about 30-69 degree of celcius in the mud spreading area. Also, estimations of the volume and weight of the hot mud were made on the basis of the visible of level 3 A product of ASTER and ground survey data. Keyword ASTER TIR, ASTER VNIR, Hot mud volcano, Temperature emissivity separation, Water vapor scaling method.
STUDY ON POTENTIAL FISHING ZONES (PFZ) INFORMATION BASED ON S-NPP VIIRS AND HIMAWARI-8 SATELLITES DATA Sartono Marpaung; Teguh Prayogo; Kuncoro Teguh Setiawan; Orbita Roswintiarti
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 1 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1341.416 KB) | 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.
COMPARATIVE TEST OF SEVERAL RAINFALL ESTIMATION METHODS USING HIMAWARI-8 DATA nanda alfuadi; Agie Wandala
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 13, No 2 (2016)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.472 KB) | DOI: 10.30536/j.ijreses.2016.v13.a2453

Abstract

Indonesian society needs information on potential hydrometeorological disasters, therefore the development of rainfall estimation methods becomes an important research activities to support disaster risk reduction. Central Kalimantan were selected as research location for comparative test of rainfall estimation methods based on Himawari-8 IR1 (11μm) data, because it has area with cloud cover fairly intensive throughout the year. Some rainfall estimation methods tested in this research are AE, CST, CSTM, IMSRA. Non Linear Relation, and Non Linear Inversion. Each of these methods tends to have a weakness in the value of accuracy, so this research aims to determine the most accurate method to be applied in Palangkaraya (27 meters above sea level) city and Muratewe (60 meters above sea level) district in Central Kalimantan. The experiment was conducted during the period of highest rainfall in January and February 2016 by converting the temperature data cloud tops (IR1) into a precipitation with AE, CST, CSTM, IMSRA, Non Linear Relation and Non Linear Inversion method. Based on the results of quantitative analysis, it was known that IMSRA was the best method which can be applied in rainfall estimation in Muarateweh’s and Palangka Raya’s winter period. The Accuracy of all estimation methods decreased when it was applied in Palangka Raya at afternoon and in Muarateweh at night until early morning. The estimation method with the lowest score was the AE with an average MSE value > 90 and the best estimation method was IMSRA with MSE value <12.
ESTIMATION OF AIR TEMPERATURE USING REMOTE SENSING BASED ON THERMAL DIFFUSIVITY APPROACH M.Rokhis Khomarudin; Ahmad Bey; Idung Risdiyanto
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 3,(2006)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (266.877 KB) | DOI: 10.30536/j.ijreses.2006.v3.a1203

Abstract

The measurement of air temperature usually used thermometer in the meteorology or climate station under Bureau of Meteorology and Geophysics. In Indonesia, there are some limitations in air temperature measurement and then they could not provide the spatial high resolution information. The measurement of air temperature is very important for analyzing the human comfort, photosynthesis, and vegetation growth which we need saome details spatial information. However, when data were sparse, the underlying assumptions about the variation among sampled points often differed and the choice of interpolation method and parameters then became critical. Often though data may be too sparse to use any of the interpolation methods, alternate ways to derive spatially representative values of air temperature need to researched. The data that could provide spatial information are remote sensing. The objective of this research is to estimate air temperature using remote sensing data (NOAA/AVHRR and LANDSAT/TM), based on thermal diffusivity approach. The steps of this research include the calibration of surface temperature, the determination of amplitude, and the estimation of air temperature. Based on this research, the best equation to calculate surface temperature from NOAA AVHRR is Ulivieri et al equation. This equation shows the higher correlation between surface temperatures from NOAA/AVHRR and the observation in the field than the other equation. Physically, this research could estimate air temperature from satellites data, but statistically, this research has not enough significancy to describe the field observation. Keywords: physical model, temperature, remote sensing.
VERIFICATION OF PISCES DISSOLVED OXYGEN MODEL USING IN SITU MEASUREMENT IN BIAK, ROTE, AND TANIMBAR SEAS, INDONESIA Armyanda Tussadiah; Joko Subandriyo; Sari Novita; Widodo Setyo Pranowo
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 1 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1154.221 KB) | DOI: 10.30536/j.ijreses.2017.v14.a2681

Abstract

Dissolved oxygen (DO) is one of the most chemical primary data in supported life for marine organisms. Ministry of Marine Affairs and Fisheries Republic of Indonesia through Infrastructure Development for Space Oceanography (INDESO) Project provides dissolved oxygen data services in Indonesian Seas for 7 days backward and 10 days ahead (9,25 km x 9.25 km, 1 daily). The data based on Biogeochemical model (PISCES) coupled with hydrodynamic model (NEMO), with input data from satellite acquisition. This study investigated the performance and accuracy of dissolved oxygen from PISCES model, by comparing with the measurement in situ data in Indonesian Seas specifically in three outermost islands of Indonesia (Biak Island, Rote Island, and Tanimbar Island). Results of standard deviation values between in situ DO and model are around two (St.dev ± 2). Based on the calculation of linear regression between in situ DO with the standard deviation obtained a high determinant coefficient, greater than 0.9 (R2 ≥ 0.9). Furthermore, RMSE calculation showed a minor error, less than 0.05. These results showed that the equation of the linear regression might be used as a correction equation to gain the verified dissolved oxygen.
ORTORECTIFICATION OF SPOT-4 DATA USING RATIONAL POLYNOMIAL COEFFICIENTS Danang Surya Candra
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (794.009 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1827

Abstract

Orthorectification  of  satellite  imagery  can  be  done  in  two  ways  i.e.,  rigorous sensor  model  and  the  approximation  model  of  the  satellite’s  orbit.  Dependence  on  physicalparameters,  to  make  rigorous  sensor  model  is  more  complicated  and  difficult  to  apply.  The approximation  model  can be either  Rational Polynomial Coefficients (RPC)  model  or  parallel projection  system.  RPC  is  a  mathematical  model  which  is  not  depends  on  the  sensor.  It  is used to improve the positioning accuracy when the parameter of the physical sensor model is  unknown.  This  study  assessed  orthorectification  of  SPOT-4  using  the  RPC  model  with  7 coefficients. Root Mean Square Error (RMSE) of GCPs obtained from the study  was less than 1  pixel.  RPC  did  not  depend  on  physical  and  satellite  orbit  parameters.  Thus  the  RPC  was simpler and easier to apply.
ESTIMATION OF GROSS PRIMARY PRODUCTION USING SATELLITE DATA AND GIS IN URBAN AREA, DENPASAR A.R. As-syakur; T. Osawa; IW.S. Adnyana
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 7, No 1 (2010): Vol 7,(2010)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1860.11 KB) | DOI: 10.30536/j.ijreses.2010.v7.a1544

Abstract

Remote sensing data with high spatial resolution is very useful to provideinformation about Gross Primary Production (GPP) especially over spatial coverage in theurban area. Most models of ecosystem carbon exchange based on remote sensing data usedlight use efficiency (LUE) model. The aim of this research was to analyze the distributionof annual GPP urban area of Denpasar. Two main satellite data used in this study wereALOS/AVNIR-2 and Aster satellite data. Result showed that annual value of GPP usingALOS/AVNIR-2 varied from 0.130 gC m-2 yr-1 to 2586.181 gC m-2 yr-1. Meanwhile, usingAster the value varied from 0.144 gC m-2 yr-1 to 2595.264 gC m-2 yr-1. The annual value ofGPP ALOS was lower than the value of Aster, because ALOS have high spatial resolutionand smaller interval of spectral resolution compared to Aster. Different land use couldeffect the value of GPP, because the different land use has different vegetation type,distribution, and different photosynthetic pathway type. The high spatial resolution of theremote sensing data is crucial to discriminate different land cover types in urban region.With heterogeneous land cover surface, maximum value of GPP using ALOS/AVNIR-2was smaller than that of Aster, however, the annual mean of GPP value usingALOS/AVNIR-2 was higher than that of Aster.
Back Pages IJReSES Vol. 12, No. 1(2015) Editorial Journal
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 12, No 1 (2015)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3438.167 KB)

Abstract

Back Pages IJReSES Vol. 12, No. 1(2015)
SPECTRAL CHARACTERISTIZATION OF RICE FIELD USING MULTITEMPORAL LANDSAT ETM+ DATA I WAYAN NUARSA; SUSUMU KANNO; YASUHIRO SUGIMORI; FUMIHIKO NlSHIO
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 2(2005)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | 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.
AN EFFECTIVE INFORMATION SYSTEM OF DROUGHT IMPACT ON RICE PRODUCTION BASED ON REMOTE SENSING Rizatus Shofiyati; Wataru Takeuchi; Soni Darmawan; Parwati Sofan
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 2 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1667.47 KB) | DOI: 10.30536/j.ijreses.2014.v11.a2613

Abstract

Long droughts experienced in the past are identified as one of the main factors in the failure of rice production. In this regard, special attention to monitor the condition is encouraged to reduce the damage. Currently, various satellite data and approaches can withdraw valuable information for monitoring and anticipating drought hazards. MODIS, MTSAT, AMSR-E, TRMM and GSMaP have been used in this activity. Meteorological drought index (SPI) of the daily and monthly rainfall data from TRMM and GSMaP have analyzed for last 10-year period. While, agronomic drought index has been studied by observing the character of some indices (EVI, VCI, VHI, LST, and NDVI) of sixteen-day and monthly MODIS, MTSAT, and AMSR-E data at a period of 4 years. Network for satellite data transfer has been built between LAPAN (data provider), ICALRD (implementer), IAARD Cloud Computing, University of Tokyo (technical supporter), and NASA. Two information system have been developed: 1) agricultural drought using the model developed by LAPAN, and 2) meteorological drought developed by Takeuchi (University of Tokyo).The accuracy study using quantitative method for LAPAN model uses VHI is 60% (Kappa 0,44), while that of for University of Tokyo model uses qualitative model with KBDI value 500-600 shows an early indication of  drought for paddy field. This will help the government or field officers in rapid management actions for the indicated drought area.This paper describes the implementation and dissemination of drought impact monitoring model on the area of rice production center using an integrated information system satellite based model. The two developed information systems are effective for spatially dissemination of drought information.

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