Abstract. 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 R 2 = 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 R 2 = 0.663 and R 2 = 0.712. Keywords: bathymetry, Landsat 8, reflectance, Van Hengel and Spitzer algorithm INTRODUCTIONBathymetric mapping is important for the coastal zone and watershed management. Bathymetry measurement conventionally in the shallow area and wavy as in a reef area is very difficult and expensive even sometimes very dangerous. (Kanno et al., 2011). The bathymetry intertidal zone is needed to study the morphology of the seabed, the environment management of coastal resources and oceanographic modeling (Stumpf et al., 2003). The coastal oceanographic research and the protection of the water environment require the use of the high accuracy bathymetric data. The use of Lidar and Radar Bathymetry for the collection of bathymetric data with high resolution and accuracy is expensive (Kaimaris et al., 2012). Siregar et al., 2009 conducted a bathymetric study using three methods Kriging interpolation method, namely, the method of inverse distance to power, and minimum curvature method.One of the satellites that can be used for mapping shallow water bathymetry is Landsat 8. Landsat imagery has a spatial resolution of 30 meters are equipped with visible channel that required in the extraction of bathymetry map. Visible channel (blue, red and green) has the ability to penetrate the water to a certain depth, the blue channel has the ability to penetrate deeper into the water body. Jupp (1988) concluded that Landsat imagery can be used in Determining the water depth, band 2 (blue channel) has the ability to penetrate up to 25 meters of water depth, Kuncoro Teguh Setiawan et al. 80International Journal of Remote Sensing and Earth Science Vol. FORMOSAT (Kholil et al., 2007), Landsat and Quickbird (Nurlidiasari, 2004). The coefficient of determination (R 2 ) is used to give a more detailed picture of the ability of channel 1,2 and 3 of Quickbird imagery in explaining variations in water depth (Siregar et al., 2010).The maximum depth th...
Indonesia had a large diversity of coastal ecosystems. One part of the them is the coral reef. The concept of mapping coral reef ecosystems has been outlined in the RSNI document about the mapping of shallow marine waters. The aim of this study is to map shallow marine waters using the 1981 and 2006 lyzenga methods. The mapping was made based on three classes including coral reef, mixed seagrass and macroalgae, and substrate. The location of the study was conducted at Pemuteran Beach, Bali. The data used were Landsat 8 imagery acquisition on 14 April 2018. Stages of data processing include atmospheric correction, radiometric correction, pansharpening, masking, cropping, and water column correction and classification. Water column correction used the Lyzenga 1981 and 2006. Classification methods to distinguish objects of shallow marine waters using the unsupervised method. The results showed differences in the results of extraction of shallow marine waters information using the Lyzenga 1981 with the 2006 Lyzenga method. The extraction results with the Lyzenga 2006 method provide more detailed information in identifying the three classes of shallow marine waters. Indonesia memiliki keanekaragaman ekosistem pesisir yang cukup besar. Salah satu bagian dari ekosistem tersebut adalah ekosistem terumbu karang. Konsep pemetaan ekosistem terumbu karang telah dituangkan dalam RSNI tentang pemetaan habitat dasar perairan laut dangkal. Tujuan penelitian ini adalah untuk melakukan pemetaan habitat perairan laut dangkal dengan menggunakan metode lyzenga 1981 dan 2006. Pemetaan tersebut dibuat berdasarkan tiga kelas diantaranya: kelas terumbu karang, kelas campuran padang lamun dan makro alga, serta kelas substrat dasar. Lokasi penelitian dilaksanakan di Pantai Pemuteran, Bali. Data yang digunakan adalah citra Landsat 8 akuisisi 14 April 2018. Tahapan pengolahan data meliputi, koreksi atmosferik, koreksi radiometrik, proses pansharpening, proses masking darat air, cropping, serta koreksi kolom air serta klasifikasi. Koreksi kolom air menggunakan metode Lyzenga 1981 dan 2006. Klasifikasi untuk membedakan obyek habitat perairan laut dangkal menggunakan metode unsupervised . Hasil penelitian menunjukkan adanya perbedaan hasil ekstraksi informasi habitat perairan laut dangkal menggunakan metode Lyzenga 1981 dengan metode Lyzenga 2006. Hasil ekstraksi dengan metode Lyzenga 2006 memberikan informasi yang lebih detail dalam mengidentifikasi tiga kelas habitat perairan laut dangkal tersebut.
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.
Satellite Derived Bathymetry (SDB) is an alternative method to obtain bathymetry information data developed by utilizing image data as data sources. This study aimed to compare the accuracy of five empiric methods: the Stumpf Method, Polynomial Method, Multilinear Regression Method (MLR), Lyzenga Method, and Van Hengel and Spitzer Methods (VHS). This research was located in Benoa, Denpasar, and Bali using SPOT 6 satellite imagery with a spatial resolution of 6 meters as the data source. The acquisition was on August 12, 2017, in situ data. The accuracy test was carried out by calculating the coefficient of determination (R2) and the RMSE value. The SPOT 6 image requires an image interpretation process, including radiometric correction and atmospheric correction using DOS and land and water masking using the NDWI equation to obtain accuracy test and bathymetric information. Stumpf method has an RMSE of 5.72 meters, R2 of 0.27. The polynomial method has an RMSE of 6.99 meters R2 of 0.01. The Multilinear Regression method has an RMSE of 5.75 meters R2 of 0.34. The Lyzenga method has an RMSE of 7.66 meters R2 of 0.09. The Van Hengel and Spitzer method has an RMSE of 6.97 meters R2 of 0.03. Based on the results of calculations from this study, the Stumpf method has the highest accuracy with an RMSE of 5.72.
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