scholarly journals DETEKSI AWAL HABITAT PERAIRAN LAUT DANGKAL MENGGUNAKAN TEKNIK OPTIMUM INDEX FACTOR PADA CITRA SPOT 7 DAN LANDSAT 8

2019 ◽  
Vol 4 (2) ◽  
pp. 174-192
Author(s):  
Anang Dwi Purwanto ◽  
Kuncoro Teguh Setiawan
Keyword(s):  
Shallow Water ◽  
Image Interpretation ◽  
Image Data ◽  
Environmental Conservation ◽  
Landsat 8 ◽  
Blue Band ◽  
Composite Image ◽  
Sensing Technology ◽  
Optimum Index Factor

Informasi keberadaan habitat perairan laut dangkal semakin dibutuhkan terutama dalam kegiatan pelestarian lingkungan dan monitoring di wilayah pesisir. Komponen penyusun ekosistem habitat dasar perairan laut dangkal di antaranya terumbu karang dan lamun dimana lokasi keberadaan obyek habitat ini cenderung berdekatan. Dalam interpretasi ekosistem habitat dasar perairan laut dangkal terkendala oleh lokasi keberadaan ekosistem yang berasosiasi dengan obyek lainnya. Tujuan penelitian ini adalah menentukan kombinasi komposit kanal terbaik dalam mengidentifikasi obyek habitat dasar perairan laut dangkal di Pantai Pemuteran, Bali. Data citra satelit yang digunakan dalam penelitian ini adalah citra SPOT 7 akuisisi tanggal 11 April 2018 dan citra Landsat 8 akuisisi tanggal 14 April 2018, sedangkan data terkait informasi sebaran habitat dasar perairan laut dangkal diperoleh berdasarkan hasil survei lapangan yang telah dilakukan pada tanggal 7-13 April 2018 di Pantai Pemuteran, Bali. Data citra satelit diperoleh dari Pusat Teknologi dan Data LAPAN. Untuk menentukan kombinasi dari 3 (tiga) kanal terbaik dalam interpretasi habitat dasar perairan laut dangkal digunakan metode Optimum Index Factor (OIF) dimana metode ini menggunakan nilai standar deviasi dan koefisien korelasi dari kombinasi 3 (tiga) kanal citra yang digunakan. Hasil penelitian menunjukkan kombinasi komposit 2 (hijau), 3 (merah) dan 4 (NIR) mempunyai nilai OIF tertinggi untuk citra SPOT 7, sedangkan kombinasi komposit 2 (biru), 4 (merah) dan 6 (SWIR 1) Mempunyai nilai OIF tertinggi untuk citra Landsat 8. Interpretasi sebaran habitat dasar perairan laut dangkal dapat dilakukan secara efektif dengan menggunakan citra komposit RGB 423 untuk citra SPOT 7 dan RGB 642 untuk citra Landsat 8.DETECTION OF SHALLOW WATER HABITATS USING OPTIMUM INDEX FACTORS TECHNIQUE ON SPOT 7 AND LANDSAT 8 IMAGERY. Information of the existence of the shallow water habitat is required especially in environmental conservation and monitoring of activities in coastal areas. The component of the shallow water habitat including coral reefs and seagrass where the location of the existence of these relatively close together. Interpretation of the shallow water habitat is constrained by the location of ecosystem associated with other objects. The aim of study is to determine the best combination of band composites in identifying the shallow water habitat in Pemuteran Beach, Bali. The study used SPOT 7 imagery (acquisition on April 11, 2018) and Landsat 8 imagery (acquisition on April 14, 2018). The data of the shallow water habitat based on the result of field survey was conducted on 7-13 April 2018 at Pemuteran Beach, Bali. Image data obtained from Remote Sensing Technology and Data Center of LAPAN. Determination of combination of 3 (three) bands the shallow water habitat using Optimum Index Factor (OIF) method where this method used standard deviation value and correlation coefficient from combination of 3 (three) bands. The results show the composite combinations of band 2 (green), band 3 (red) and band 4 (NIR) have the highest OIF values for SPOT 7 image, while the composite combinations of band 2 (blue), band 4 (red) and band 6 (SWIR 1) have the highest OIF values for Landsat 8 image. Interpretation of distribution of shallow water habitat can be done effectively using RGB 423 composite image (SPOT 7) and RGB 642 composite image (Landsat 8).

scholarly journals Research Bathymetry Mapping of Shallow Water Areas around Islands in the Truong Sa Archipelago by Deep - Remote sensing technology

2017 ◽  
Vol 33 (4) ◽  
Author(s):  
Phan Quoc Yen ◽  
Dao Khanh Hoai ◽  
Dinh Thi Bao Hoa
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Satellite Image ◽  
Image Data ◽  
Landsat 8 ◽  
Military Operations ◽  
Sensing Technology ◽  
Remote Sensing Techniques ◽  
Map Data ◽  
The Military

Satellite image data is being researched and applied effectively in the survey and establishment of bathymetry mapping in shallow water areas in both time and human terms. Remote sensing techniques contribute to rapid updating of topography, timely assurance of civil and military operations such as maritime safety, environmental security and rescue, Warfare in the military, especially the ability to remotely monitor disputed areas. The article experiment with the Stumpf et al algorithm to estimate the shallow water depths on the Spratly Island by Landsat 8 image. The correlation coefficient of the model R2 is 0.924; RMSE is 0.99m. In addition, the results are compared with the map data of C-map and use 12 actual test points scores to evaluate the accuracy of the model.

Assessment of mangrove forest change in Ca Mau province using satellite images in the period of 1988 - 2018

2021 ◽  
Vol 66 (1) ◽  
pp. 175-187
Author(s):  
Duong Phung Thai ◽  
Son Ton
Keyword(s):  
Satellite Images ◽  
Satellite Image ◽  
Image Interpretation ◽  
Image Data ◽  
Vegetation Coverage ◽  
Landsat 8 ◽  
Mangrove Forests ◽  
Forest Change ◽  
Shrimp Ponds ◽  
Area Classification

On the basis of using practical methods, satellite image processing methods, the vegetation coverage classification system of the study area, interpretation key for the study area, classification and post-classification pro cessing, this research introduces how to exploit and process multi-temporal satellite images in evaluating the changes of forest area. Landsat 4, 5 TM and Landsat 8 OLI remote sensing image data were used to evaluate the changes in the area of mangrove forests (RNM) in Ca Mau province in the periods of 1988 - 1998, 1998 - 2013, 2013 - 2018, and 1988 - 2018. The results of the image interpretation in 1988, 1998, 2013, 2018 and the overlapping of the above maps show: In the 30-year period from 1988 to 2018, the total area of mangroves in Ca Mau province was decreased by 28% compared to the beginning, from 71,093.3 ha in 1988 reduced to 51,363.5 ha in 2018, decreasing by 19,729.8 ha. The recovery speed of mangroves is 2 times lower than their disappearance speed. Specifically, from 1988 to 2018, mangroves disappeared on an area of 42,534.9 hectares and appeared on the new area of 22,805 hectares, only 12,154.5 hectares of mangroves remained unchanged. The fluctuation of mangrove area in Ca Mau province is related to the process of deforestation to dig shrimp ponds, coastal erosion, the formation of mangroves on new coastal alluvial lands and soil dunes in estuaries, as well as planting new mangroves in inefficient shrimp ponds.

scholarly journals Research of total phosphorus concentration in Hefei Ring River based on landsat-8 satellite image data

2019 ◽  
Vol 136 ◽  
pp. 06032
Author(s):  
Kun Ding ◽  
Chen Yang ◽  
Chuan-hua Zhu ◽  
Yong Zhang ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Total Phosphorus ◽  
Satellite Image ◽  
Water Environment ◽  
Image Data ◽  
Phosphorus Concentration ◽  
Landsat 8 ◽  
Total Phosphorus Concentration ◽  
Important Indicator ◽  
Daily Monitoring ◽  
Sensing Technology

Total phosphorus (TP) in water is an important indicator reflecting water environment and water ecology. If the concentration exceeds the standard, it will directly lead to eutrophication. The daily monitoring of total phosphorus in water bodies has already mentioned the important agenda of environmental protection, while the routine testing has a large workload and heavy tasks. We used satellite remote sensing technology to extract image data and establish a mathematical models, what was used to invert the total phosphorus concentration in water. Taking the Ring River as an example, we selected different time nodes to sample and measure the TP value, and use the landsat-8 image data to establish a semi-empirical regression model. The model structure, the calculation results found that the error with the measured data is within the controllable range. The method is simple in operation, saves resources, manpower and financial resources, and can accurately reflect the actual situation of the water body TP.

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 THE EFFECT OF DIFFERENT ATMOSPHERIC CORRECTIONS ON BATHYMETRY EXTRACTION USING LANDSAT 8 SATELLITE IMAGERY

2017 ◽  
Vol 12 (1) ◽  
pp. 13 ◽  
Author(s):  
Kuncoro Teguh Setiawan ◽  
Yennie Marini ◽  
Johannes Manalu ◽  
Syarif Budhiman
Keyword(s):  
Remote Sensing ◽  
Satellite Image ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Image Data ◽  
Landsat 8 ◽  
Calculation Error ◽  
Sensing Technology ◽  
The Difference ◽  
Landsat Satellite

Remote sensing technology can be used to obtain information bathymetry. Bathymetric information plays an important role for fisheries, hydrographic and navigation safety. Bathymetric information derived from remote sensing data is highly dependent on the quality of satellite data use and processing. One of the processing to be done is the atmospheric correction process. The data used in this study is Landsat 8 image obtained on June 19, 2013. The purpose of this study was to determine the effect of different atmospheric correction on bathymetric information extraction from Landsat satellite image data 8. The atmospheric correction methods applied were the minimum radiant, Dark Pixels and ATCOR. Bathymetry extraction result of Landsat 8 uses a third method of atmospheric correction is difficult to distinguish which one is best. The calculation of the difference extraction results was determined from regression models and correlation coefficient value calculation error is generated.

scholarly journals IDENTIFICATION OF MANGROVE FORESTS USING MULTI-RESOLUTION SATELLITE IMAGERY

Jurnal Segara ◽  
2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Anang Dwi Purwanto
Keyword(s):  
Remote Sensing ◽  
Mangrove Forest ◽  
Image Data ◽  
Field Measurements ◽  
Landsat 8 ◽  
Mangrove Forests ◽  
Remote Sensing Technology ◽  
Red Edge ◽  
Sensing Technology ◽  
Sentinel 2A

The development of remote sensing technology for identifying various of coastal and marine ecosystems which one of them is mangrove forest increasing rapidly. Identification of mangrove forests visually is constrained by much of combinations of RGB composite. The aims of this research is to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using Optimum Index Factor (OIF) method. The image data used represents 3 levels of intermediate to high resolution spatial resolution including Landsat 8 imagery (30 m) acquisition on 30 May 2013, Sentinel 2A image (10 m) acquisition on 18 March 2018 and SPOT 6 image (6 m) acquisition on 10 January 2015. Data of mangrove distributions used were the results of field measurements in the period 2013-2015. The results showed that the band composites of 564 (NIR+SWIR+Red) of Landsat 8 image and the band composites of 8a114 (Vegetation Red Edge+SWIR+Red) of Sentinel 2A are the best RGB composites for identifying mangrove forest, while the band composites of 341 (Red+NIR+Blue) of SPOT 6 image is  also the best colour composites (R-G-B) for identifying mangrove forest in Segara Anakan, Cilacap. The RGB composites of images developed from Landsat 8 and Sentinel 2A image are able to distinguish objects of mangrove forest from surrounding objects more clearly, but image composites from SPOT 6 image still require additional of association elements to identify mangrove objects.The development of remote sensing technology for identifying various of coastal and marine ecosystems which one of them is mangrove forest increasing rapidly. Identification of mangrove forests visually is constrained by much of combinations of RGB composite. The aims of this research is to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using Optimum Index Factor (OIF) method. The image data used represents 3 levels of intermediate to high resolution spatial resolution including Landsat 8 imagery (30 m) acquisition on 30 May 2013, Sentinel 2A image (10 m) acquisition on 18 March 2018 and SPOT 6 image (6 m) acquisition on 10 January 2015. Data of mangrove distributions used were the results of field measurements in the period 2013-2015.The results showed that the band composites of 564 (NIR+SWIR+Red) of Landsat 8 image and the band composites of 8a114 (Vegetation Red Edge+SWIR+Red) of Sentinel 2A are the best RGB composites for identifying mangrove forest, while the band composites of 341 (Red+NIR+Blue) of SPOT 6 image is  also the best colour composites(R-G-B) for identifying mangrove forest in Segara Anakan, Cilacap. The RGB composites of images developed from Landsat 8 and Sentinel 2A image are able to distinguish objects of mangrove forest from surrounding objects more clearly, but imagecomposites from SPOT 6 image still require additional of association elements to identify mangrove objects.

scholarly journals Radiometric Cross Calibration and Validation Using 4 Angle BRDF Model between Landsat 8 and Sentinel 2A

2020 ◽  
Vol 12 (5) ◽  
pp. 806 ◽  
Author(s):  
M M Farhad ◽  
Morakot Kaewmanee ◽  
Larry Leigh ◽  
Dennis Helder
Keyword(s):  
Spectral Band ◽  
Image Data ◽  
Calibration Procedure ◽  
Landsat 8 ◽  
Blue Band ◽  
Calibration Uncertainty ◽  
Significant Difference ◽  
The Cross ◽  
Sentinel 2A ◽  
Cross Calibration

This work describes a proposed radiometric cross calibration between the Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI) sensors. The cross-calibration procedure involves (i) correction of the MSI data to account for spectral band differences with OLI and (ii) normalization of Bidirectional Reflectance Distribution Function (BRDF) effects in the data from both sensors using a new model accounting for the view zenith/azimuth angles in addition to the solar zenith/view angles. Following application of the spectral and BRDF normalization, standard least-squares linear regression is used to determine the cross-calibration gain and offset in each band. Uncertainties related to each step in the proposed process are determined, as is the overall uncertainty associated with the complete processing sequence. Validation of the proposed cross-calibration gains and offsets is performed on image data acquired over the Algodones Dunes site. The results of this work indicate that the blue band has the most significant offset, requiring use of the estimated cross-calibration offset in addition to the estimated gain. The highest difference was observed in the blue and red bands, which are 2.6% and 1.4%, respectively, while other bands shows no significant difference. Overall, the net uncertainty in the proposed process was estimated to be on the order of 6.76%, with the largest uncertainty component due to each sensor’s calibration uncertainty on the order of 5% and 3% for the MSI and OLI, respectively. Other significant contributions to the uncertainty include seasonal changes in solar zenith and azimuth angles, target site nonuniformity, variability in atmospheric water vapor, and/or aerosol concentration.

Information and estimation in image processing

1987 ◽  
Vol 45 ◽  
pp. 14-17
Author(s):  
B. Roy Frieden
Keyword(s):  
Image Processing ◽  
Optical System ◽  
Large Amplitude ◽  
Communication Theory ◽  
Image Data ◽  
Direct Approach ◽  
Ill Posed

Despite the skill and determination of electro-optical system designers, the images acquired using their best designs often suffer from blur and noise. The aim of an “image enhancer” such as myself is to improve these poor images, usually by digital means, such that they better resemble the true, “optical object,” input to the system. This problem is notoriously “ill-posed,” i.e. any direct approach at inversion of the image data suffers strongly from the presence of even a small amount of noise in the data. In fact, the fluctuations engendered in neighboring output values tend to be strongly negative-correlated, so that the output spatially oscillates up and down, with large amplitude, about the true object. What can be done about this situation? As we shall see, various concepts taken from statistical communication theory have proven to be of real use in attacking this problem. We offer below a brief summary of these concepts.

Determination of the added masses and damping coefficients during coupled motions of two ships in shallow water parallel to the vertical wall

2021 ◽  
pp. 16-25
Author(s):  
В.Ю. Семенова ◽  
К.И. Баканов
Keyword(s):  
Shallow Water ◽  
Vertical Wall ◽  
Three Dimensional ◽  
Hydrodynamic Coefficients ◽  
Damping Coefficients ◽  
Added Masses ◽  
Joint Motions ◽  
National Practice ◽  
Simultaneous Influence

В статье рассматривается определение коэффициентов демпфирования и присоединенных масс, возникающих при совместной качке двух судов в условиях мелководья параллельно вертикальной стенке на основании решения трехмерной потенциальной задачи. Определение гидродинамических коэффициентов осуществляется на основании методов интегральных уравнений и зеркальных отображений. Представленное решение в отечественной практике является новым. В статье приводятся результаты расчетов коэффициентов присоединенных масс и демпфирования, возникающих при качке двух одинаковых судов, расположенных лагом к волнению и параллельно вертикальной стенке в зависимости от изменения расстояний как между судами, так и между судами и вертикальной стенкой. Проводится исследование влияния различных фарватеров на величины гидродинамических коэффициентов, а именно: мелководного фарватера, мелководного фарватера с вертикальной стенкой, мелководного фарватера со вторым параллельно качающимся судном и мелководного фарватера с вертикальной стенкой и вторым судном. Таким образом, в работе учитывается одновременное влияния мелководья, вертикальной стенки и второго судна. Показано увеличение значений коэффициентов присоединенных масс и демпфирования при уменьшении расстояний между судами и между судами и вертикальной стенкой. Также показано значительное совместное влияние вертикальной стенки и второго судна на коэффициенты присоединенных масс и демпфирования по сравнению с другими видами стесненных фарватеров. The article discusses the determination of damping coefficients and added masses arising from the joint motions of two ships in shallow water conditions parallel to the vertical wall based on the solution of a three-dimensional potential problem. Determination of hydrodynamic coefficients is carried out on the basis of the methods of integral equations and mirror images. The solution presented in the national practice is new The article presents the results of calculating the coefficients of added masses and damping arising from the motions of two identical ships located lagged to the sea and parallel to the vertical wall, depending on the change in the distances between the ships and between the ships and the vertical wall. A study is being made of the influence of various waterways on the values ​​of hydrodynamic coefficients, namely: a shallow waterway, a shallow waterway with a vertical wall, a shallow waterway with a second parallel oscillating ship and a shallow waterway with a vertical wall and a second ship. Thus, the work takes into account the simultaneous influence of shallow water, vertical wall and the second ship. An increase in the values of the coefficients of added masses and damping with a decrease in the distances between ships and between ships and the vertical wall is shown. It also shows a significant combined effect of the vertical wall and the second ship on the added mass and damping coefficients in comparison with other types of constrained waterways.

Making Of Classification Land Cover Through Result Of Visual Data Satellite Image Analysis Landsat 8 OLI : Case Study in Tapaktuan District, South Aceh District

2021 ◽  
Vol 6 (1) ◽  
pp. 59-65
Author(s):  
Safridatul Audah ◽  
Muharratul Mina Rizky ◽  
Lindawati
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Sensing Technology ◽  
Open Land ◽  
Cover Class ◽  
Satellite Image Analysis

Tapaktuan is the capital and administrative center of South Aceh Regency, which is a sub-district level city area known as Naga City. Tapaktuan is designated as a sub-district to be used for the expansion of the capital's land. Consideration of land suitability is needed so that the development of settlements in Tapaktuan District is directed. The purpose of this study is to determine the level of land use change from 2014 to 2018 by using remote sensing technology in the form of Landsat-8 OLI satellite data through image classification methods by determining the training area of the image which then automatically categorizes all pixels in the image into land cover class. The results obtained are the results of the two image classification tests stating the accuracy of the interpretation of more than 80% and the results of the classification of land cover divided into seven forms of land use, namely plantations, forests, settlements, open land, and clouds. From these classes, the area of land cover change in Tapaktuan is increasing in size from year to year.

Sign in / Sign up

Export Citation Format

Share Document