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ESTIMASI BATIMETRI DARI DATA SPOT 7 STUDI KASUS PERAIRAN GILI MATRA NUSA TENGGARA BARAT Setiawan, Kuncoro Teguh; Manessa, Masita Dwi Mandini; Winarso, Gathot; Anggraini, Nanin; Girrastowo, Gigih; Astriningrum, Wikanti; Herianto, Herianto; Rosid, Syamsu; Supardjo, A. Harsono
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 2 Desember 2018
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Indonesia merupakan negara kepulauan dengan ribuan pulau besar dan kecil yang memliki perairan laut dangkal. Salah satu informasi yang dibutuhkan dari pulau-pulau tersebut adalah peta batimetri khususnya diperairan laut dangkal. Informasi tersebut masih sangat terbatas pada skala yang besar untuk skala yang lebih detil masih sangat terbatas. Untuk menyelesaikan permasalahan tersebut dibutuhkan teknogi penginderaan jauh. Salah satu pemanfaatan teknologi penginderaan jauh adalah untuk menghasilkan informasi batimetri. Banyak metode yang dapat digunakan untuk menghasilkan informasi batimetri dengan teknologi tersebut. Metode yang digunakan dalam penelitian ini adalah metode regresi linier berganda (MLR) yang dikembangkan oleh Lyzenga, 2006. Data yang akan di gunakan adalah citra satelit SPOT 7 di Perairan Laut Dangkal Gili Trawangan, Gili Meno dan Gili Air Pulau Lombok Provinsi Nusa Tenggara Barat. Metode penentuan batimetri tersebut dilakukan pada data kedalaman insitu dengan melakukan dua modifikasi yaitu yang pertama dengan tidak memperhatikan jenis objek habitat dasar dan yang kedua memperhatikan objek habitat dasar karang, lamun, makroalga dan substrat.Hasil dari penelitian ini memberikan korelasi R2 yang meningkat dari 0,721 menjadi 0,786 serta penuruanan nilai kesalahan RMSE dari 3,3 meter menjadi 2,9 meter.
Isu Penyelarasan Flight Information Region di atas Wilayah Natuna Supriyadi, Asep Adang; Manessa, Masita Dwi Mandini; Gultom, Rudy Agus Gemilang
JURNAL MANAJEMEN TRANSPORTASI & LOGISTIK Vol 5, No 3 (2018): NOVEMBER
Publisher : Sekolah Tinggi Manajemen Transportasi (STMT) Trisakti

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Abstract

Citizen sentiment is essential to evaluate the support toward government program. In 2015, Indonesian government proposed an acceleration program on re-alignment on Flight Information Region above Natuna area. Since then, primary of discussion is often be held as a formal or informal event. The data collected from 210 respondent, which consist of pilots, military staff, ATC staff, and academician. Furthermore, this study uses TF-IDW weighting technique to cluster the argument as positive, neutral, and negative sentiment. The result shows that most of Indonesia aviation community (75%) argue that FIR management should base on sovereignty and safety. Moreover, FIR issue under economic, national security and management shows significant positive respond (>90%) while FIR management under Singapore shows a negative response (100%). The result indicates that the aviation community supports the national program Natuna FIR re-alignment.
DETERMINATION OF THE BEST METHODOLOGY FOR BATHYMETRY MAPPING USING SPOT 6 IMAGERY: A STUDY OF 12 EMPIRICAL ALGORITHMS Manessa, Masita Dwi Mandini; Haidar, Muhammad; Hartuti, Maryani; Kresnawati, Diah Kirana
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 2 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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Abstract

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.
BOTTOM TYPES IDENTIFICATION IN SHALLOW CORAL REEF ECOSYSTEMS USING IMAGERY SATELLITE DATA MANESSA, MASITA DWI MANDINI; TANAKA, TASUKU; Osawa, Takahiro
Ecotrophic: Journal of Environmental Science Vol 7, No 2 (2012)
Publisher : Udayana University

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Abstract

Satellite data provide information about spectral signatures of objects in detail, based on the wide range of spectral wavelengths. Bottom types in a coral reef Ecosystems are diverse and each object has a different spectral signature. The aim of this research is to define bottom types using Multispectral and Hyperspectral imagery satellite data. Six processes were applied to Hyperspectral Images to identified bottom types using modification of Analytical Imaging and Geophysics LLC (AIG) hyperspectral analysis. The multispectral analysis was focused on correcting water column noise by applying the radiative water column algorithm (Lyzenga, 1978, 1981) and the modified image correction algorithm (Lyzenga et al., 2006). The results showed that multispectral image analysis was able to identify a fine complexity of b bottom types classes with 68.57% overall accuracy. In contrast, Hyperion image identified a coarse complexity of bottom types classes with 61.57% overall accuracy. This low result was caused by low spatial resolution which created a mixing pixel around image of thin and narrow shallow coral reef ecosystem. Spatial resolution, atmosphere and water scattering played an important role in bottom types identification.
SATELLITE-DERIVED BATHYMETRY USING RANDOM FOREST ALGORITHM AND WORLDVIEW-2 IMAGERY Manessa, Masita Dwi Mandini; Kanno, Ariyo; Sekine, Masahiko; Haidar, Muhammad; Yamamoto, Koichi; Imai, Tsuyoshi; Higuchi, Takaya
Geoplanning: Journal of Geomatics and Planning Vol 3, No 2 (2016): (October 2016)
Publisher : Department of Urban and Regional Planning, Diponegoro University

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Abstract

In empirical approach, the satellite-derived bathymetry (SDB) is usually derived from a linear regression. However, the depth variable in surface reflectance has a more complex relation. In this paper, a methodology was introduced using a nonlinear regression of Random Forest (RF) algorithm for SDB in shallow coral reef water. Worldview-2 satellite images and water depth measurement samples using single beam echo sounder were utilized. Furthermore, the surface reflectance of six visible bands and their logarithms were used as an input in RF and then compared with conventional methods of Multiple Linear Regression (MLR) at ten times cross validation. Moreover, the performance of each possible pair from six visible bands was also tested. Then, the estimated depth from two methods and each possible pairs were evaluated in two sites in Indonesia: Gili Mantra Island and Panggang Island, using the measured bathymetry data. As a result, for the case of all bands used the RF in compared with MLR showed better fitting ensemble, -0.14 and -1.27m of RMSE and 0.16 and 0.47 of R2 improvement for Gili Mantra Islands and Panggang Island, respectively. Therefore, the RF algorithm demonstrated better performance and accuracy compared with the conventional method. While for best pair identification, all bands pair wound did not give the best result. Surprisingly, the usage of green, yellow, and red bands showed good water depth estimation accuracy.