Indonesia Conference Directory

Corresponding Author
Prayudha Hartanto

Institutions
Geospatial Information Agency

Abstract
Accurate and high-resolution water depth information are important for wide range of coastal research and monitoring. In this case, providing an accurate bathymetric map is a major challenge for remote sensing. This study developed and evaluated a semi-parametric regression to extract depth information using various image datasets (Landsat 8, Sentinel 2A and Worldview 2). We compared the ability of these imageries to map depth information using generalized additive model (GAM). GAM is a semi-parametric generalized linear model which allow for nonlinear relationships between covariates and the target variable. We used the Morotai shallow water area in Indonesia to apply GAM in deriving depth information. We found that higher image spatial resolution results in higher mapping accuracies. This study highlights the potential of selected images and mapping techniques for deriving bathymetric data.

Keywords
bathymetry;SDB;depth;shallow water;GAM;regression model

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/QVmyzj3WYqcN

Corresponding Author
Dudy Wijaya

Institutions
a) Geodesy Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Indonesia
* wijaya.dudy[at]gmail.com

b) Division for Vertical Control Network, Geospatial Information Agency (BIG), Indonesia

Abstract
A new ocean tide model for the Indonesian Sea has been estimated by assimilating TOPEX+JASON (27 years), ENVISAT (8 years), GFO-1 (8 years), and 100 coastal gauge stations (2-5 years) data into a barotropic hydrodynamic model. The new model consists of more than 25 tidal constituents, with a spatial resolution of about 2.5-. The respond method was employed to estimate the amplitudes and phases of about 280 tidal constituents. Only constituents whose amplitudes are larger than 1 cm are added to construct the new model. According to comparisons with another 40 coastal tide gauge stations and collinear residual reduction test, the new model provides a better performance compared to global ocean models, in particular around shallow waters and coastal areas. This advantage is due to the following reasons: (i) fine-scale along-track tidal analysis of multi-mission altimetry and coastal tide gauge data and (ii) optimal estimates of friction velocity and the decorrelation length in the hydodynamical equations.

Keywords
Altimetry; tide gauge; hydrodynamic model; shallow waters

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/BpvgquKyYFMZ

Corresponding Author
Indah Kartika

Institutions
Hasanuddin University

Abstract
This research was conducted on March 2019 in Barrang Caddi Island, Spermonde Archipelago. The acquisition of Sentinel-2A satellite imagery was on February 24, 2019. DOS method (Dark Object Substraction) was used to atmospheric correction , water column correction using Lyzenga algorithm with values of ki / kj = 0.679844349 and a = -0,39554029. Image classification analysis using IsoData and K-Means unsupervised classification method. Gound truthing using the UPT (Underwater Photo Transect) method. Basic information on spectral values is obtained from Sentinel-2A satellites using band 2 with 490nm, band 3 with 560nm, band 4 with 665nm, and band 8 with 842nm. The results show that there are 4 dominant objects including live coral, rubble, algae, sand and seagrass. The highest spectral reflectance can be detected by green band (560nm) with IsoData and K-Means classifications. Unsupervised classification using IsoData method has capability to detect live coral and while the K-Means method is capable to explore the seagrass.

Keywords
Sentinel-2A, isodata, k-means, spectral, Spermonde

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/nm6HLavfJ2hr

Corresponding Author
Afif Prabowo Jatiandana.

Institutions
(a) Oceanography_Earth Science Department, Faculty of Earth Science and Technology (FEST), Bandung Institute of Technology (ITB), Jl. Ganesha 10, Bandung 40132, Indonesia

*afifprabowoj[at]gmail.com
*afifpj[at]students.itb.ac.id

Abstract
Indonesia is a region that is directly adjacent to the Pacific Ocean and the Indian Ocean which allows a thermal front phenomenon. The purpose of this study is to identify the presence of thermal fronts based on seasonal variations and inter-annual variations in Indonesia. The data are Sea Surface Temperature (SST), Ocean Nino Index (ONI), and Dipole Mode Index (DMI) with a span of time from January 2007 - December 2017 (11 years). The SST data is a level 3 Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellite image data with a resolution of 4 km. SST data processing uses remote sensing techniques and Geographic Information System (GIS). The results of this study indicate that the distribution of SST and thermal fronts are influenced by seasonal variations and inter-annual variations. The highest average thermal front event in Indonesian waters occurred in a combination of El-Nino and Positive IOD conditions. The highest average thermal front incidence in Indonesian waters also occurred during the East Season, while the smallest average occurred during the Transition Season II. During West Season, Transition Season II, and East Season, the largest number of thermal fronts was found in Western Indonesian Waters. Meanwhile, in the Transition Season I, the largest number of thermal fronts was found in Central Indonesian Waters.

Keywords
thermal front, SST, remote sensing, seasonal and inter-annual variations

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/XJbgxF2hDPdY

Corresponding Author
Kosasih Prijatna

Institutions
Geodesy Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung

Abstract
Sea level spatio temporal variability in Indonesian waters is an important oceanographic aspect to be investigated. This is related to the use of satellite altimetry data in physical geodesy studies in the region. Due to its location at the equatorial zone and as an archipelagic region, Indonesian waters should experience complex behavior and pattern in term of sea level. Identification and analysis of those phenomena require precise sea level observation over a long period of observation. Topex, Jason 1, Jason 2, and Jason 3 satellite altimetry missions have been observing sea level for more than two decades. In this research, the use of these altimetry data from 1992 to 2019 in identifying and analyzing the long term sea level variability in Indonesian waters will be investigated.

Keywords
satellite altimetry; sea level variability; Indonesian waters

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/4CE6QKBhzvjd

Corresponding Author
Sam Wouthuyzen

Institutions
a) Research Centre for Oceanography – Indonesian Institute of Sciences. Jl. Pasir Putih 1, Ancol Timur, Jakarta 14430, Indonesia.
b) Centre for Deep Sea Research – Indonesian Institute of Sciences. Jl. Y. Syaranamual, Poka, Ambon 97233 – Indonesia
c) Centre for Hydrography and Oceanography – Indonesian Navy, Jakarta, Indonesia.
d) Departement of Remote Sensing Technology, Indonesian Defence University, Bogor, Indonesia
e) Graduate Research School, College of Science and Engineering, James Cook University, Australia
f) Centre of Excellence for Tuna Conservation – Ambon, Jl. Y. Syaranamual, Poka, Ambon 97233 – Indonesia

Abstract
Salinity is an important conservative tracer in the ocean considered as a proxy to explain physical and chemical processes in the system (e.g. upwelling process and nutrient flux) controlling biological activities (e.g. primary production). Combining with temperature and chlorophyll-a (Chl-a), these three oceanographic parameters are important to reveal the water quality of a marine system supporting fishery. In a significantly large spatial scale system of ocean processes such as upwelling systems, the availability of spatial and temporal sea surface salinity (SSS), sea surface temperature (SST) and Chl-a data is essential to be used for this water quality purpose and is mostly sourced from remote sensing-based measurements. However, the satellite-derived SSS dataset (~4 to 9 years long) is not as temporally adequate as SST and Chl-a datasets (~3 decades long) thus, preventing a comprehensively spatio-temporal analysis of this water quality aspect. Since SSS can be approximated using satellite-derived ocean color products having the similar temporal length of datasets to the available SST and Chl-a datasets, predicted SSS can be produced from these ocean color products to fill the gap of the existing SSS dataset. Here, we estimated SSS from ocean color products of Aqua-MODIS satellite with a spatial resolution of 4 km by developing an empirical model. Ocean products used in this study were remote sensing reflectances (Rrs) at a range of blue (412, 433, 469 and 488 nm), green (531, 547 and 555 nm) and red wavelength (645, 667 and 678 nm). We also used absorption coefficients due to detritus material non-algae, Gelbstof and CDOM (ADG) at 443 nm and the absorption coefficient due to phytoplankton (APH) at 443 nm. We chose Banda Sea as our area of interest due to its large-scale upwelling system (~300 km x 300 km) providing an important ocean process related to fishery and the availability of in-situ salinity measurements in this location (i.e. CTD casts from series of R/V Baruna Jaya III, VII and VIII cruises and Argo floats), which a part of these datasets will be used to validate our empirical SSS model. As results, we found that ADG-using empirical model (polynomial regression order 5) produces the highest correlation to SSS with R2 of 0.940. The average of all Blue and Green Bands ratio of B/G (R2: 0.903), Blue Chromaticity [B/(B+G+R)] (R2: 0.917) and Green chromaticity [(G/(B+G+R)] (R2: 0.836) also show the similar result, while the rest ocean color products in our empirical model only produce weak correlation to SSS (R2<0.7). Due to its accuracy, ADG was selected as empirical model to estimate SSS. The root mean square error (RMSE) of this model was significantly small (0.130 psu). The predicted SSS using ADG is well validated to Argo floats (RMSE < 0.3 psu) and Aquarius satellite measuring SSS (RMSE: 0.15 psu). The accuracy of ADG-derived salinity at 443 nm indicates that this approach can be used to investigate upwelling process in

Keywords
Sea Surface Salinity, Ocean Color, empirical model, Banda Sea

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/Qpxy2NELuVMd

Corresponding Author
dina anggreni sarsito

Institutions
Geodesy Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung
Jl. Ganesha 10 Bandung, Indonesia

Abstract
Sea level variability is one of fundamental parameters for scientific development such as modeling the Earths climate. In addition, this parameter also plays crucial rules in mitigating socio-economic hazards due to sea level changes, especially in coastal areas. Mitigating the sea level hazards in an archipelagic country like Indonesia becomes more essential, since the country is geographically constructed by various bathymetric depths with different type of seas. One of attempts to study the sea level variability is to take benefit from satellite altimetry data. The TOPEX+JASON altimetry missions have observed sea level during more than 25 years, and hence the rate of sea level variability can thoroughly be studied. In this research, regional-scale variations in sea level over the Indonesian sea will be examined.

Keywords
altimetry, sea level variability, Indonesia

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/4QrhRj3YMVpG

Corresponding Author
Khafid Rizki Pratama

Institutions
a) Mathilda Batlayeri Meteorological Station, BMKG, Jalan Harapan Saumlaki 97664, Indonesia
b) Head of Center for Research and Development, BMKG, Jalan Angkasa Pura 1 Kemayoran 10610, Indonesia
c) Head of Center for Marine Meteorology, BMKG, Jalan Angkasa Pura 1 Kemayoran 10610, Indonesia
d,e,g,h) Center for Marine Meterorology, BMKG, Jalan Angkasa Pura 1 Kemayoran 10610, Indonesia
f) Paotere Marine Meteorological Station, BMKG, Makassar 90163, Indonesia
*fuadislami21[at]gmail.com
I,j) Teluk Bayur Marine Meteorological Station, BMKG, Padang 25123, Indonesia

Abstract
Producing better wind wave numerical forecasting products by utilizing real time ocean wave observation data is still a challenge for marine meteorologist. The altimeter sensors installed on the Sentinel SAR/1B and JASON-3 satellites have the ability to do spectral measurement to determine the wave energy with the growth rate of wind waves frequency that will be formed. This study examines the verification and evaluation of wind waves from WaveWatch-3 model (Ina-Waves Products) by comparing wave spectral of Sentinel SAR/1B and JASON-3 satellites during Ina-PRIMA 2018 research in June with the wind waves footprint-directional wave-spectral technique. The output of WaveWatch-3 model based on a comparison of numerical Gaussian swell spectrum shows that the wave growth pattern is dominantly in the frequency of 0.11 - 0.34 Hz with an accuracy of swell formation of 83% from Sentinel SAR/1B satellite observations. The results of Ina-Waves model from the WaveWatch-3 model output with deep water waves along the shipping tracks and 5 buoy points show that the accuracy of significant wave height at 85% and the error rate is 0.45 meters from the Sentinel SAR/1B. Correction of the comparison of Sentinel SAR/1B and JASON-3 satellites resulted in a correction of Ina-Waves products of 0.40 meters. This result becomes a correction of input data towards the development of numerical surface waves models in Indonesian waters.

Keywords
Wind waves; Ina-Waves; Altimeter satellite

Topic
Marine Geodesy and Satellite Oceanography

Link: https://ifory.id/abstract/paGDwVF6zgev