scholarly journals Mapping of shallow water bathymetry and reef geomorphology using Sentinel-2 satellite imagery in Genteng Besar and Genteng Kecil Island, Kepulauan Seribu

2021 ◽  
Vol 944 (1) ◽  
pp. 012048
Author(s):  
S B Agus ◽  
V P Siregar ◽  
S B Susilo ◽  
M S Sangadji ◽  
G F Tasirileleu ◽  
...  
Keyword(s):  
Shallow Water ◽  
Satellite Imagery ◽  
Depth Estimation ◽  
Benthic Habitat ◽  
Sensing Technology ◽  
Value Range ◽  
Position Index ◽  
Optimum Depth ◽  
The Given

Abstract Information on seafloor characteristics is one of the essential variables in coastal management and marine ecosystems. Application methods in remote sensing technology to study about characteristics of shallow waters have continuously been done. This research consists of two parts: an estimation of depth using Sentinel 2B satellite imagery with the Lyzenga algorithm and geomorphological classification of the benthic area using the Benthic Terrain Modeler (BTM) approach. BTM is a method to analyze benthic habitat and shallow water geomorphology. Integrated Depth data were analyzed using BTM to obtain bathymetric position index (BPI), slope, and classification of reef geomorphological structures. The resulting BPI value range is directly proportional to the given spatial area (scale factor). The slope is ranged between 0.01° – 19.24°, while optimum depth estimation is applicable until 10-meter. The values of BPI and slope were used as variables to classify the geomorphology of shallow water benthic areas based on the previous classification dictionary. Six geomorphological classes resulting from this study are Back Reef, Deep Depression, Depression, Lower Bank Shelf, Mid-Slope Ridges, and Reef Crest.

scholarly journals Removing Sun Glint from Optical Satellite Images of the Shallow Water Areas around Islands in the Spratly Islands Archipelago

2017 ◽  
Vol 33 (3) ◽  
Author(s):  
Yen Phan Quoc
Keyword(s):  
Shallow Water ◽  
Satellite Images ◽  
Image Data ◽  
Depth Estimation ◽  
The Sun ◽  
Model Estimate ◽  
Spratly Islands ◽  
Sensing Technology ◽  
Surrounding Areas ◽  
Optical Satellite Images

Remote sensing technology has an important role to provide information for the establishment of habitat and bathymetry maps in shallow water areas. However, sun glint on the water surface has changed spectral reflectance in body water recorded by the sensor, thus seriously distorting water column and benthic properties. So, the sun glint should be removed prior to image analysis to improve the accuracy. This study aims to remove the sun glint from Sentinel-2 multi-spectral satellite images by two common methods of Lyzenga and Hedley for shallow waters in the surrounding areas of the Spratly islands archipelago. The experimental results were evaluated by spectrographic comparison after calibration by the two methods. In addition, the efficiency of the two methods was clearly shown in the application of depth estimation using the Lyzenga method for image data at two points. The result increases the R2 correlation coefficient and decreases the root-mean-square RMSE of the model estimate of the significant amount of depth after calibration.

scholarly journals Shallow Water Seabed Profile Changes in 2016 - 2018 Based on Landsat 8 Satellite Imagery (Case Study: Semak Daun Island, Karya Island and Gosong Balik Layar)

Omni-Akuatika ◽  
2020 ◽  
Vol 16 (3) ◽  
pp. 26
Author(s):  
Zahra Safira Aulia ◽  
Triguardi Tharik Ahmad ◽  
Ratih Rachma Ayustina ◽  
Fauzi Tri Hastono ◽  
Rizqi Rizaldi Hidayat ◽  
...  
Keyword(s):  
Shallow Water ◽  
Satellite Imagery ◽  
Accuracy Assessment ◽  
Satellite Image ◽  
Benthic Habitat ◽  
Landsat 8 ◽  
Marine Tourism ◽  
Profile Changes ◽  
High Level

Seribu Islands is one of the marine tourism destinations in  Jakarta. The high level of tourism in the Seribu Islands can be a threat to shallow water seabed profile habitat. Therefore, monitoring of changes in shallow water seabed profile habitat is needed so the sustainability can be monitored. This study aimed to determine changes in the shallow water seabed profile on Karya Island, Semak Daun Island, and Gosong Balik Layar in 2016 and 2018 based on Landsat 8 Satellite Imagery. Methods of this research used satellite image pre-processing, image classification, field survey, image reclassification, and accuracy assessment.  The results showed that the coral area had decrease trend, while the area of Seagrass mix Seaweed had increased. The result of this classification had an accuracy value of 71.52%. Keywords: remote sensing, multispectral imagery, Lyzenga, benthic habitat, Seribu Island

scholarly journals THE BOTTOM SUBSTRATE SHALLOW WATER MAPPING USING THE QUICK BIRD SATELLITE IMAGERY

2010 ◽  
Vol 2 (1) ◽  
Author(s):  
Vincentius Siregar
Keyword(s):  
High Resolution ◽  
Shallow Water ◽  
Satellite Imagery ◽  
Transformation Method ◽  
Live Coral ◽  
Bottom Substrate ◽  
Accuracy Test ◽  
Coral Sand ◽  
Water Mapping

The objective of this study was to explore the capability of high resolution satellite data of QuicBird to map the characteristics of the bottom shallow water (habitat) using the transformation method of two bands (blue and green) by implementing "depth invariant index" algorithm i.e., Y = ln Band 1 - (ki/kj) ln Band 2. The result provide more detail information on the characteristic of the bottom shallow water comparing to the used of original band (RGB). The classification of the transformed image showed 6 classes of bottom substrats i.e., Live coral, Death, Coral, Sand mix coral, Sand mix algae, andMacro algae with Sand. The accuracy test of the map derived from the classification was about 79%.Keywords: bottom shallow water, Quick Bird image, depth invariant index, classification

SHALLOW WATER HABITAT MAPPING AND REEF FISH STOCK ESTIMATION USING HIGH RESOLUTION SATELLITE DATA

2013 ◽  
Vol 5 (2) ◽  
Author(s):  
Vincentius P. Siregar ◽  
Sam Wouthuyzen ◽  
Andriani Sunuddin ◽  
Ari Anggoro ◽  
Ade Ayu Mustika
Keyword(s):  
High Resolution ◽  
Reef Fish ◽  
Satellite Imagery ◽  
Field Survey ◽  
Coral Cover ◽  
Fish Density ◽  
Fish Stock ◽  
Benthic Habitat ◽  
Live Coral ◽  
Stock Estimation

Shallow marine waters comprise diverse benthic types forming habitats for reef fish community, which important for the livelihood of coastal and small island inhabitants. Satellite imagery provide synoptic map of benthic habitat and further utilized to estimate reef fish stock. The objective of this research was to estimate reef fish stock in complex coral reef of Pulau Pari, by utilizing high resolution satellite imagery of the WorldView-2 in combination with field data such as visual census of reef fish. Field survey was conducted between May-August 2013 with 160 sampling points representing four sites (north, south, west, and east). The image was analy-zed and grouped into five classes of benthic habitats i.e., live coral (LC), dead coral (DC), sand (Sa), seagrass (Sg), and mix (Mx) (combination seagrass+coral and seagrass+sand). The overall accuracy of benthic habitat map was 78%. Field survey revealed that the highest live coral cover (58%) was found at the north site with fish density 3.69 and 1.50 ind/m2at 3 and 10 m depth, respectively. Meanwhile, the lowest live coral cover (18%) was found at the south site with fish density 2.79 and 2.18  ind/m2 at 3 and 10 m depth, respectively. Interpolation on fish density data in each habitat class resulted in standing stock reef fish estimation:  LC (5,340,698 ind), DC (56,254,356 ind), Sa (13,370,154 ind), Sg (1,776,195 ind) and Mx (14,557,680 ind). Keywords: mapping, satellite imagery, benthic habitat, reef fish, stock estimation

The Potential of the Russian Language Textbook in the Formation of Primary Schoolchildren’s Communicative Literacy

2018 ◽  
Vol 79 (8) ◽  
pp. 35-40
Author(s):  
M. I. Kuznetsova
Keyword(s):  
Primary School ◽  
Russian Language ◽  
Primary School Children ◽  
Written Text ◽  
Russian Literary ◽  
The Given ◽  
The Russian Language ◽  
Speech Situation ◽  
Linguistic Means

One of the goals of the Russian language course in the primary school is the formation of the communicative literacy. The content of the course should be aimed at understanding the wealth of linguistic means by primary school children; the formation of the ability to detect a violation of linguistic norms and the inadequacy of the linguistic means used in the speech situation; the accumulation of the experience in choosing of linguistic means in accordance with the peculiarities of the speech situation; the creation of oral and written texts that meet the criteria of content, connectivity, compliance with the norms of the Russian literary language. The article considers the classification of exercises that contribute to the formation of communicative literacy. The author gives the examples of exercises where the student acts in different roles: the student is an observer of the speech situation and analyzes the adequacy of the choice of linguistic means; the student is a direct participant in the given speech situation and makes a choice of language facilities; the student is offered to create the speech situation himself, to independently construct an oral and written text.

scholarly journals MultiKOC: Multi-One-Class Classifier Based K-Means Clustering

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 134
Author(s):  
Loai Abdallah ◽  
Murad Badarna ◽  
Waleed Khalifa ◽  
Malik Yousef
Keyword(s):  
Clustering Algorithm ◽  
Main Idea ◽  
Molecular Classification ◽  
Positive Sample ◽  
Classification Problems ◽  
Multiple Cancer ◽  
Multiple Tumor ◽  
One Class Classifier ◽  
The Given

In the computational biology community there are many biological cases that are considered as multi-one-class classification problems. Examples include the classification of multiple tumor types, protein fold recognition and the molecular classification of multiple cancer types. In all of these cases the real world appropriately characterized negative cases or outliers are impractical to achieve and the positive cases might consist of different clusters, which in turn might lead to accuracy degradation. In this paper we present a novel algorithm named MultiKOC multi-one-class classifiers based K-means to deal with this problem. The main idea is to execute a clustering algorithm over the positive samples to capture the hidden subdata of the given positive data, and then building up a one-class classifier for every cluster member’s examples separately: in other word, train the OC classifier on each piece of subdata. For a given new sample, the generated classifiers are applied. If it is rejected by all of those classifiers, the given sample is considered as a negative sample, otherwise it is a positive sample. The results of MultiKOC are compared with the traditional one-class, multi-one-class, ensemble one-classes and two-class methods, yielding a significant improvement over the one-class and like the two-class performance.

scholarly journals Quantitative Shape-Classification of Misfitting Precipitates during Cubic to Tetragonal Transformations: Phase-Field Simulations and Experiments

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1373
Author(s):  
Yueh-Yu Lin ◽  
Felix Schleifer ◽  
Markus Holzinger ◽  
Na Ta ◽  
Birgit Skrotzki ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Phase Field ◽  
Phase Field Model ◽  
Invariant Moments ◽  
Plane Normal ◽  
Plane Shape ◽  
Formation And Evolution ◽  
The Given ◽  
Good Agreement

The effectiveness of the mechanism of precipitation strengthening in metallic alloys depends on the shapes of the precipitates. Two different material systems are considered: tetragonal γ′′ precipitates in Ni-based alloys and tetragonal θ′ precipitates in Al-Cu-alloys. The shape formation and evolution of the tetragonally misfitting precipitates was investigated by means of experiments and phase-field simulations. We employed the method of invariant moments for the consistent shape quantification of precipitates obtained from the simulation as well as those obtained from the experiment. Two well-defined shape-quantities are proposed: (i) a generalized measure for the particles aspect ratio and (ii) the normalized λ2, as a measure for shape deviations from an ideal ellipse of the given aspect ratio. Considering the size dependence of the aspect ratio of γ′′ precipitates, we find good agreement between the simulation results and the experiment. Further, the precipitates’ in-plane shape is defined as the central 2D cut through the 3D particle in a plane normal to the tetragonal c-axes of the precipitate. The experimentally observed in-plane shapes of γ′′-precipitates can be quantitatively reproduced by the phase-field model.

scholarly journals A Novel GIS-Based Approach for Automated Detection of Nearshore Sandbar Morphological Characteristics in Optical Satellite Imagery

2021 ◽  
Vol 13 (11) ◽  
pp. 2233
Author(s):  
Rasa Janušaitė ◽  
Laurynas Jukna ◽  
Darius Jarmalavičius ◽  
Donatas Pupienis ◽  
Gintautas Žilinskas
Keyword(s):  
Satellite Imagery ◽  
Morphological Characteristics ◽  
Unsupervised Classification ◽  
Landsat 8 ◽  
Multi Scale ◽  
Medium Resolution ◽  
Wide Range ◽  
Position Index ◽  
Local Relief ◽  
Length Width

Satellite remote sensing is a valuable tool for coastal management, enabling the possibility to repeatedly observe nearshore sandbars. However, a lack of methodological approaches for sandbar detection prevents the wider use of satellite data in sandbar studies. In this paper, a novel fully automated approach to extract nearshore sandbars in high–medium-resolution satellite imagery using a GIS-based algorithm is proposed. The method is composed of a multi-step workflow providing a wide range of data with morphological nearshore characteristics, which include nearshore local relief, extracted sandbars, their crests and shoreline. The proposed processing chain involves a combination of spectral indices, ISODATA unsupervised classification, multi-scale Relative Bathymetric Position Index (RBPI), criteria-based selection operations, spatial statistics and filtering. The algorithm has been tested with 145 dates of PlanetScope and RapidEye imagery using a case study of the complex multiple sandbar system on the Curonian Spit coast, Baltic Sea. The comparison of results against 4 years of in situ bathymetric surveys shows a strong agreement between measured and derived sandbar crest positions (R2 = 0.999 and 0.997) with an average RMSE of 5.8 and 7 m for PlanetScope and RapidEye sensors, respectively. The accuracy of the proposed approach implies its feasibility to study inter-annual and seasonal sandbar behaviour and short-term changes related to high-impact events. Algorithm-provided outputs enable the possibility to evaluate a range of sandbar characteristics such as distance from shoreline, length, width, count or shape at a relevant spatiotemporal scale. The design of the method determines its compatibility with most sandbar morphologies and suitability to other sandy nearshores. Tests of the described technique with Sentinel-2 MSI and Landsat-8 OLI data show that it can be applied to publicly available medium resolution satellite imagery of other sensors.

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