scholarly journals ACCURACY OF UNSUPERVISED CLASSIFICATION TO DETERMINE CORAL HEALTH USING SPOT-6 AND SENTINEL-2A

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 503-509 ◽  
Author(s):  
N. Nurdin ◽  
M. Lanuru ◽  
M. Akbar AS ◽  
I. Kartika ◽  
T. Komatsu ◽  
...  
Keyword(s):  
Shallow Water ◽  
Accuracy Assessment ◽  
Unsupervised Classification ◽  
Live Coral ◽  
Natural Death ◽  
Dead Coral ◽  
Reflectance Analysis ◽  
Coral Health ◽  
Ground Truthing ◽  
Sentinel 2A

Abstract. Characteristics of corals spectral from different species are expected to have optically different characters. The aims of this research are to compare unsupervised classification between IsoData and K-Means methods with Lyzenga application, and to analyze the precision of SPOT-6 and Sentinel-2A satellite imagery in classsifying shallow water habitat. The image processing are atmosferic correction, cropping, masking, Depth Invariant Index, Unsupervised classification, ground truthing, reclassify, accuracy assessment, and shallow water habitat spectral reflectance analysis. Rubble and dead coral with algae were indicating as coral death due to either damaging human activity or natural death such as bleaching. The accuracy of unsupervised classification IsoData and K-Means method have the same accuracy 62.50%. The IsoData method is better detected live coral and algae. Rubble were dominant detected in K-Means method.

scholarly journals CORAL REEFS ON INHABITED AND UNINHABITED SMALL ISLANDS, SPERMONDE ARCHIPELAGO, INDONESIA

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 609-616
Author(s):  
N. Nurdin ◽  
K. Amri ◽  
A. R. Rasyid ◽  
D. A. T. Pulubuhu ◽  
N. Nurdin ◽  
...  
Keyword(s):  
Coral Reef ◽  
Ground Truth ◽  
Unsupervised Classification ◽  
Anthropogenic Factors ◽  
Live Coral ◽  
Small Islands ◽  
Landsat Images ◽  
Dead Coral ◽  
Reef Ecosystem ◽  
Spermonde Archipelago

Abstract. The small islands in Indonesia is providing important ecosystem services. It is important to identify damages of a coral reef ecosystem and whether natural factors or anthropogenic factors are the main causes. Landsat images obtained with different sensors were analyzed for mapping coral reef on inhabited and uninhabited small islands, Spermonde archipelago, Indonesia. Overall accuracies of three habitats classification were 89.2% and 85.6%, respectively. They are live coral, dead coral and non-coral. Ground truth surveys were selected by using the unsupervised classification method The live coral in inhabited islands was slightly greater than in uninhabited. An increasing area of live coral was about 5.3 ha of the total area in 1990 per year while a decreasing of dead coral was 3.5 ha per year in inhabited islands. In uninhabited island, a decreasing speed of live coral habitat area was about 0.6 per year. During 29 years, a significant increase in the dead coral and decrease in live corals. It has been identified that the significant controlling factor for the disturbances in reef ecosystem is derived from natural and anthropogenic.

scholarly journals A COMPARATIVE STUDY OF ADVANCED LAND USE/LAND COVER CLASSIFICATION ALGORITHMS USING SENTINEL-2 DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 665-670 ◽  
Author(s):  
K. Nivedita Priyadarshini ◽  
M. Kumar ◽  
S. A. Rahaman ◽  
S. Nitheshnirmal
Keyword(s):  
Land Use ◽  
Maximum Likelihood ◽  
Land Cover ◽  
Accuracy Assessment ◽  
Unsupervised Classification ◽  
Sensor Data ◽  
Support Vector ◽  
Classification Algorithms ◽  
Land Use Land Cover ◽  
Sentinel 2A

<p><strong>Abstract.</strong> Land Use/ Land Cover (LU/LC) is a major driving phenomenon of distributed ecosystems and its functioning. Interpretation of remote sensor data acquired from satellites requires enhancement through classification in order to attain better results. Classification of satellite products provides detailed information about the existing landscape that can also be analyzed on temporal basis. Image processing techniques acts as a platform for analysis of raw data using supervised and unsupervised classification algorithms. Classification comprises two broad ranges in which, the analyst specifies the classes by defining the training sites called supervised classification where as automatically clustering of pixels to the defined number of classes namely the unsupervised classification. This study attempts to perform the LU/LC classification for Paonta Sahib region of Himachal Pradesh which is a major industrial belt. The data obtained from Sentinel 2A, from which the stacked bands of 10<span class="thinspace"></span>m resolution are only used. Various classification algorithms such as Minimum Distance, Maximum Likelihood, Parallelepiped and Support Vector Machine (SVM) of supervised classifiers and ISO Data, K-Means of unsupervised classifiers are applied. Using the applied classification results, accuracy assessment is estimated and compared. Of these applied methods, the classification method, maximum likelihood provides highest accuracy and is considered to be the best for LU/LC classification using Sentinel-2A data.</p>

scholarly journals Remote Sensing of Population and Coral Destruction for Long Term on Small Islands

2019 ◽  
Author(s):  
Nurjannah Nurdin ◽  
Muhammad Hatta ◽  
Supriadi Mashoreng ◽  
Khairul Amri ◽  
Dwia Aries Tina Pulubuhu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Accuracy Assessment ◽  
Atmospheric Correction ◽  
Principal Component ◽  
Population Data ◽  
Unsupervised Classification ◽  
Live Coral ◽  
Small Islands ◽  
True Color ◽  
Dynamic Population

In general, remote sensing has proven to be a powerful tool in the overall understanding of natural and anthropogenic phenomena. Satellites have become useful tools for tasks such as characterization, monitoring, and the continuous prospecting of natural resources. This research aims to analyze spatial dynamic and destructive on coral reefs area and correlation between live coral reduction and population on small islands. Landsat MSS, TM, ETM, and OLI-TIRS are used to spatial analyze of coral reef dynamics from 1972 to 2016. The image processing includes gap-filling, atmospheric correction, geometric correction, image composite (true color), water column correction, unsupervised classification, reclassification, accuracy assessment. The statistical analysis identifies the relationship between dynamic population data with a reduction of live coral, namely Principal Component Analysis (PCA) and Multiple Regression Analysis. The effect of the population shows a positive correlation with the reduction in the area of live coral, although it is significant. The fact is the practice of coral destruction on an island; it is usually not only caused or carried out by residents who live on the island but also carried out by other residents of different islands.

scholarly journals Comparing of Landsat 8 and Sentinel 2A using Water Extraction Indexes over Volta River

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Clement Kwang ◽  
Edward Matthew Osei Jnr ◽  
Adwoa Sarpong Amoah
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Unsupervised Classification ◽  
Water Bodies ◽  
Water Extraction ◽  
Landsat 8 ◽  
Sensing Data ◽  
Optimal Classifier ◽  
Sentinel 2A

Remote sensing data are most often used in water bodies’ extraction studies and the type of remote sensing data used also play a crucial role on the accuracy of the extracted water features. The performance of the proposed water indexes among the various satellite images is not well documented in literature. The proposed water indexes were initially developed with a particular type of data and with advancement and introduction of new satellite images especially Landsat 8 and Sentinel, therefore the need to test the level of performance of these water indexes as new image datasets emerged. Landsat 8 and Sentinel 2A image of part Volta River was used. The water indexes were performed and then ISODATA unsupervised classification was done. The overall accuracy and kappa coefficient values range from 98.0% to 99.8% and 0.94 to 0.98 respectively. Most of water bodies enhancement indexes work better on Sentinel 2A than on Landsat 8. Among the Landsat based water bodies enhancement ISODATA unsupervised classification, the modified normalized water difference index (MNDWI) and normalized water difference index (NDWI) were the best classifier while for Sentinel 2A, the MNDWI and the automatic water extraction index (AWEI_nsh) were the optimal classifier. The least performed classifier for both Landsat 8 and Sentinel 2A was the automatic water extraction index (AWEI_sh). The modified normalized water difference index (MNDWI) has proved to be the universal water bodies enhancement index because of its performance on both the Landsat 8 and Sentinel 2A image.

scholarly journals Lethal effects of habitat degradation on fishes through changing competitive advantage

2012 ◽  
Vol 279 (1744) ◽  
pp. 3899-3904 ◽  
Author(s):  
Mark I. McCormick
Keyword(s):  
Community Dynamics ◽  
Habitat Degradation ◽  
Interspecific Interactions ◽  
Interference Competition ◽  
Live Coral ◽  
Dead Coral ◽  
Thermal Bleaching ◽  
Coral Reef Ecosystems ◽  
Pomacentrus Amboinensis ◽  
Habitat Generalist

Coral bleaching has caused catastrophic changes to coral reef ecosystems around the world with profound ecological, social and economic repercussions. While its occurrence is predicted to increase in the future, we have little understanding of mechanisms that underlie changes in the fish community associated with coral degradation. The present study uses a field-based experiment to examine how the intensity of interference competition between juveniles of two species of damselfish changes as healthy corals degrade through thermal bleaching. The mortality of a damselfish that is a live coral specialist ( Pomacentrus moluccensis ) increased on bleached and dead coral in the presence of the habitat generalist ( Pomacentrus amboinensis ). Increased mortality of the specialist was indirectly owing to enhanced aggression by the generalist forcing the specialist higher up and further away from shelter on bleached and dead coral. Evidence from this study stresses the importance of changing interspecific interactions to community dynamics as habitats change.

scholarly journals SATELLITE-DERIVED BATHYMETRY: ACCURACY ASSESSMENT ON DEPTHS DERIVATION ALGORITHM FOR SHALLOW WATER AREA

2017 ◽  
Vol XLII-4/W5 ◽  
pp. 159-164 ◽  
Author(s):  
N. M. Said ◽  
M. R. Mahmud ◽  
R. C. Hasan
Keyword(s):  
Shallow Water ◽  
Accuracy Assessment ◽  
Water Area ◽  
Bathymetric Data ◽  
Sensing Technology ◽  
Shallow Water Area ◽  
Multispectral Satellite Imagery ◽  
Marginal Improvement ◽  
Acquisition Technique ◽  
Hydrographic Surveying

Over the years, the acquisition technique of bathymetric data has evolved from a shipborne platform to airborne and presently, utilising space-borne acquisition. The extensive development of remote sensing technology has brought in the new revolution to the hydrographic surveying. Satellite-Derived Bathymetry (SDB), a space-borne acquisition technique which derives bathymetric data from high-resolution multispectral satellite imagery for various purposes recently considered as a new promising technology in the hydrographic surveying industry. Inspiring by this latest developments, a comprehensive study was initiated by National Hydrographic Centre (NHC) and Universiti Teknologi Malaysia (UTM) to analyse SDB as a means for shallow water area acquisition. By adopting additional adjustment in calibration stage, a marginal improvement discovered on the outcomes from both Stumpf and Lyzenga algorithms where the RMSE values for the derived (predicted) depths were 1.432 meters and 1.728 meters respectively. This paper would deliberate in detail the findings from the study especially on the accuracy level and practicality of SDB over the tropical environmental setting in Malaysia.

scholarly journals DEPTH ESTIMATION OF SHALLOW WATER USING MULTISPECTRAL SATELLITE IMAGERY SENTINEL-2A

Jurnal Segara ◽  
2020 ◽  
Vol 16 (3) ◽  
Author(s):  
Arip Rahman
Keyword(s):  
Shallow Water ◽  
Test Data ◽  
Remote Sensing Data ◽  
Depth Estimation ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Data Set ◽  
Svm Algorithm ◽  
Sentinel 2A

Shallow water bathymetry estimation from remote sensing data has been increasing widespread, as an alternative to traditional bathymetry measurement that has disturbed by technical and logistic problem. Deriving bathymetry data from Sentinel 2A images, at visible wavelength (blue, green and red) 10 meter spatial resolution was carried out around the waters of the Kemujan Island Karimunjawa National Park Central Java. Amount of 1280 points data are used as training data sets and 854 points data as test data set produced from sounding. Dark Object Substraction (DOS) has been to correct atmospherically the Sentinel-2A images. Several algorithm has been applied to derive bathymetry data, including: linear transform, ratio transform and support vector machine (SVM). The highest correlation between depth prediction and observe resulted from SVM algorithm with a coefficient of determination (R2) 0.71 (training data) and 0.56 (test data). The assessment of the accuracy of the three methods using RMSE and MAE values, the SVM algorithm has the smallest value (< 1 m). This indicates that the SVM algorithm has a high accuracy compared to the other two methods. The bathymetry map derived from Sentinel 2A imagery cannot be used as a reference for navigation.

scholarly journals KONDISI EKOSISTEM TERUMBU KARANG DI PERAIRAN KRUENG RAYA, KABUPATEN ACEH BESAR

2021 ◽  
Vol 8 (1) ◽  
pp. 11
Author(s):  
Nurul Najmi ◽  
M Rizki Fazillah ◽  
Muhammad Agustiar
Keyword(s):  
Coral Reef ◽  
Coral Cover ◽  
Live Coral ◽  
Coral Mortality ◽  
Coral Reef Ecosystem ◽  
Dead Coral ◽  
High Increase ◽  
Mortality Index ◽  
Malacca Strait ◽  
Reef Ecosystem

This study aims to analyze the condition of the coral reef ecosystem including the substrate, genus composition, and the level of coral mortality in the waters of the Malacca Strait, Masjid Raya District, Aceh Besar District. The research was conducted from October 2016 to October 2019 in the waters of the Malacca Strait, Masjid Raya District, Aceh Besar District. The research site is divided into three stations consisting of Lhok Mee Station, Ahmad Rhang Manyang and Benteng Inong Balee Station. Data were collected using the Point Intercept Transect method. The results showed that the condition of coral reefs at Lhok Mee Station was in the damaged category with coral cover ranging from 6.56% - 13.44%. Ahmad Rhang Manyang Station is included in the moderate to good category with coral cover ranging from 38.75% - 67.19%. Meanwhile, Benteng Inong Balee Station is included in the medium category with coral cover ranging from 45.94% - 56.88%. The monitoring results found that 30 coral genera with the highest composition of the coral genera came from the Porites genus, while other coral genera were unevenly distributed. The value of the mortality index for Lhok Mee Station shows a high increase in mortality of live coral to dead coral. Meanwhile, Ahmad Rhang Manyang and Benteng Inong Balee stations have low coral mortality index values.

scholarly journals A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images

2019 ◽  
Vol 11 (10) ◽  
pp. 1230 ◽  
Author(s):  
Jinsong Deng ◽  
Yibo Huang ◽  
Binjie Chen ◽  
Cheng Tong ◽  
Pengbo Liu ◽  
...  
Keyword(s):  
Green Space ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Principal Component ◽  
Transformation Method ◽  
Yangtze River Delta ◽  
Reference Points ◽  
Hybrid Classifier ◽  
Comparison Approach ◽  
Sentinel 2A

Monitoring urban expansion and greenspace change is an urgent need for planning and decision-making. This paper presents a methodology integrating Principal Component Analysis (PCA) and hybrid classifier to undertake this kind of work using a sequence of multi-sensor SPOT images (SPOT-2,3,5) and Sentinel-2A data from 1996 to 2016 in Hangzhou City, which is the central metropolis of the Yangtze River Delta in China. In this study, orthorectification was first applied on the SPOT and Sentinel-2A images to guarantee precise geometric correction which outperformed the conventional polynomial transformation method. After pre-processing, PCA and hybrid classifier were used together to enhance and extract change information. Accuracy assessment combining stratified random and user-defined plots sampling strategies was performed with 930 reference points. The results indicate reasonable high accuracies for four periods. It was further revealed that the proposed method yielded higher accuracy than that of the traditional post-classification comparison approach. On the whole, the developed methodology provides the effectiveness of monitoring urban expansion and green space change in this study, despite the existence of obvious confusions that resulted from compound factors.

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