Kuncoro Teguh Setiawan
Unknown Affiliation

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

THE EFFECT OF DIFFERENT ATMOSPHERIC CORRECTIONS ON BATHYMETRY EXTRACTION USING LANDSAT 8 SATELLITE IMAGERY Kuncoro Teguh Setiawan; Yennie Marini; Johannes Manalu; Syarif Budhiman
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 (1113.457 KB) | DOI: 10.30536/j.ijreses.2015.v12.a2668

Abstract

Remote sensing technology can be used to obtain information bathymetry. Bathymetric information plays an important role for fisheries, hydrographic and navigation safety. Bathymetric information derived from remote sensing data is highly dependent on the quality of satellite data use and processing. One of the processing to be done is the atmospheric correction process. The data used in this study is Landsat 8 image obtained on June 19, 2013. The purpose of this study was to determine the effect of different atmospheric correction on bathymetric information extraction from Landsat satellite image data 8. The atmospheric correction methods applied were the minimum radiant, Dark Pixels and ATCOR. Bathymetry extraction result of Landsat 8 uses a third method of atmospheric correction is difficult to distinguish which one is best. The calculation of the difference extraction results was determined from regression models and correlation coefficient value calculation error is generated.
UTILIZATION OF SAR AND EARTH GRAVITY DATA FOR SUB BITUMINOUS COAL DETECTION Atriyon Julzarika; Kuncoro Teguh Setiawan
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 (1297.886 KB) | DOI: 10.30536/j.ijreses.2014.v11.a2612

Abstract

Remote sensing data can be used for geological and mining applications, such as coal detection. Coal consists of five classes of Anthracite, Bituminous, Sub-Bituminous, Lignite coal and Peat coal. In this study, the type of coal that is discussed is Sub bituminous, Lignite coal, and peat coal. This study aims to detect potential sub bituminous using Synthetic Aperture Radar (SAR) data, and earth gravity. One type of remote sensing data to detect potential sub bituminous, lignite coal and peat coal are SAR data and satellite data Geodesy. SAR data used in this study is ALOS PALSAR. SAR data is used to predict the boundary between Lignite coal with Peat coal. The method used is backscattering. In addition to the SAR data is also used to make height model. The method used is interferometry. Geodetic satellite data is used to extract the value of the earth gravity and geodynamics. The method used is physical geodesy. Potential sub-bituminous coal can be known after the correlation between the predicted limits lignite coal-peat coal by the earth gravity, geodynamics, and height model. Volume predictions of potential sub bituminous can be known by calculating the volume using height model and transverse profile test. The results of this study useful for preliminary survey of geological in mining exploration activities.
APPLICATION OF VAN HENGEL AND SPITZER ALGORITHM FOR INFORMATION ON BATHYMETRY EXTRACTION USING LANDSAT DATA Kuncoro Teguh Setiawan; Syifa Wismayati Adawiah; Takahiro OSAWA; I. Wayan Nuarsa
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 1 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (886.148 KB) | DOI: 10.30536/j.ijreses.2014.v11.a2603

Abstract

Remote sensing technology provides an opportunity for effective and efficient bathymetry mapping, especially in areas which level of depth changes quickly. Bathymetry information is very useful for hydrographic and shipping safety. Landsat medium resolution satellite imagery can be used for the extraction of bathymetry information. This study aims to extract information from the Landsat bathymetry by using Van Hengel and Spitzer rotation algorithm transformation (1991) in the water of Menjangan Island, Bali. This study shows that Van Hengel and Spitzer rotation algorithm transformation (1991) can be used to extract information on the bathymetry of Menjangan Island. Extraction of bathymetric information generated from Landsat TM imagery data in March 19, 1997 had shown the depth interval of (-0.6) m to (-12.3) m and R2 value of 0.671. While Data LANDSAT ETM + dated June 23, 2000 resulted in depth interval of 0 m to (-19.1) m and R2 value of 0.796. Furthermore, data LANDSAT ETM + dated March 12, 2003 resulted in depth interval of 0 m to (-22.5) m and R2 value of 0.931.
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.