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Estimation Chlorophyll-A Using Landsat-8 Imagery in Shallow Water: Effect of Atmospheric and Algorithm

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Estimation Chlorophyll-A Using Landsat-8 Imagery in Shallow Water: Effect of Atmospheric and Algorithm The IJICS (International Journal of Informatics and Computer Science) Vol 5 No 1, March 2021, Page 57-63 ISSN 2548-8384 (online), ISSN 2548-8449 (print) Available Online at https://ejurnal.stmik-budidarma.ac.id/index.php/ijics/index DOI 10.30865/ijics.v5i1.2954 Estimation Chlorophyll-a Using Landsat-8 Imagery in Shallow Water: Effect of Atmospheric and Algorithm Abdi Sukmono*, Lilik Kristianingsih Department of Geodetic Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia Email: 1,*[email protected], [email protected] Coressponding Author: 1,*[email protected] Submitted: 06/03/2021; Accepted: 28/03/2021; Published: 29/03/2021 Abstract−Chlorophyll-a estimation using remote sensing technology is being challenged to improve its accuracy. Various algorithms and correction methods need to be studied, including the influence of the atmosphere. It can influence the passage of the electromagnetic wave from the sun to the object and from the object to the sensor that makes the difference on the image reflectance. There are two kinds of reflectance; which are ToA (Top of Atmosphere) reflectance and BoA (Bottom of Atmosphere) reflectance. ToA reflectance is the reflectance captured by the sensor yet BoA reflectance is the reflectance of the object corrected by the atmosphere. ToA reflectance is produced by radiometric calibration while BoA reflectance is made of atmospheric correction process. This research studies aims to compare those to reflectance to investigate the impact of atmospheric correction usage on chlorophyll-a case study. The waters of Wedung district is chosen as the research field because it is the largest area in Demak regency. This study used DOS (Dark Object Substractions), FLAASH (Fast Line of sight Atmospheric Analysis of Spectral Hypercubes), and 6SV (Second Simullations of a Satellite Signal in the Solar Spectrum) correction method. To compare between ToA and BoA reflectance in the calculation of chlorophyll-a, the writer used the algorithms of Wouthuyzen, Wibowo, Pentury, Much Jisin and also Lestari Laksmi. The result shown is that the usage of BoA image reflectance (atmospherically corrected) had a better model result than ToA image reflectance. This is indicated from the consecutive determination coefficient values of ToA reflectance which are 0,2292; 0,4562; 0,2292; 0,2252. Meanwhile the consecutive coefficient values of BoA reflectance by DOS correction method are 0,5251; 0,5575; 0,5251; 0,6939; by FLAASH correction method are 0,6168, 0,5041, 0,6168, 0,614; by 6SV method are 0,6436; 0,4033; 0,6436; 0,6365. The result of hypothesis and validation test is that atmospheric correction significantly influences on the calculation of chlorophyll-a in Wedung district except using Wibowo algorithm. Keywords: Chlorophyll-a Algorithm; Effect of Athmospheric; Landsat 8; Shallow Water 1. INTRODUCTION Chlorophyll-a is a very important parameter in the study of the level of productivity of ocean waters. According to [1] , Chlorophyll-a is a pigment of phytoplankton that can be used as a parameter marine productivity. Chlorophyll-a concentration above 0.2 mg / L indicate the presence of phytoplankton life. This can be used as a marker where fishing is combined with other oceanographic parameters. Because phytoplankton are the food source for fish surface. In the development of data chlorophyll-A is also often used as a parameter to indicate the quality of the water environment. Mapping the distribution of chlorophyll-a conventionally by taking samples of the data field is currently less effective, because it requires considerable time and energy are adequate. Though data on the distribution of chlorophyll- A is needed quickly to make ocean model. Therefore, today the determination of the value of chlorophyll-a lot of remote sensing using satellite technology. Some satellites have been designed and used as a means of mapping the distribution of chlorophyll-a. Determination of chlorophyll-a using remote sensing technology still needs to increase accuracy. One of the techniques used is atmospheric correction. It is a process to eliminate errors caused by atmospheric influences on the image. Atmospheric correction able to eliminate the influence from the atmosphere and return the reflectance value according to the actual object's reflectance value on the earth's surface [2]. The correction is done by considering various atmospheric parameters in the correction process, including seasonal factors, and the climatic conditions at the location of the image recording (eg tropical, sub-tropical, and others). It features the ability to fix atmospheric disturbances such as mist, smoke, and other. The influence of the atmosphere occur during the recording process the image in which the electromagnetic waves from the sun to the earth's surface and from the object to the sensor impaired as it passes through the atmosphere, the disorder can be either scattering or absorption. This will have an impact on image data obtained, in which the data recorded by the satellite sensors with data on the object will be different. Figure 1. Atmospheric influence on the recordings of satellite imagery [3] Copyright © 2021, Abdi Sukmono. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Page 57 The IJICS (International Journal of Informatics and Computer Science) Vol 5 No 1, March 2021, Page 57-63 Abdi Sukmono, Estimation Chlorophyll-a Using Landsat-8 Imagery in Shallow Water: Effect of Atmospheric and Algorithm Figure 1 shows that the atmosphere can influence the electromagnetic waves from the sun to the object and from the object to the sensor which causes an error in the image data, in which the image data obtained with the desired data is not the same such errors can be minimized by performing atmospheric correction. In satellite image processing, there are several models of atmospheric correction. In general atmospheric correction models are often used include: 1. DOS Atmospheric correction. According [4], the principle of this method is to improve the radiometric values (pixel value in the image due to atmospheric disturbances). If there is no atmosphere, dark colored object or usually in the form of water and the shadow of the cloud should have a pixel value of 0, if the object is not worth 0 then the value is biased. 2. FLAASH Atmospheric correction. It corrected image by suppressing or eliminating the effect of water vapor, oxygen, carbon dioxide, methane, ozone and molecular and aerosol scattering by radiative transfer codes MODTRAN-4. This correction is applied to each pixel [5]. 3. 6SV Atmospheric correction. Atmospheric correction methods 6S (Second Simulation of a Satellite Signal in the Solar Spectrum) was performed using a web-based 6S atmospheric code in http://6s.ltdri.org/ [6]. The recorded energy data recorded by the satellite is called reflectance. Reflectance, there are two kinds, namely reflectance TOA (Top of Atmosphere) and reflectance BoA (Bottom of Atmosphere). TOA reflectance is the reflectance captured by satellite sensors while the reflectance BoA is reflectance on the object that has been corrected atmosphere. TOA reflectance obtained by radiometric calibration and reflectance BoA obtained from atmospheric correction process. This study will compare the reflectance ToA (without atmospheric correction) and reflectance BoA. This is used to determine how its influence in the calculation of chlorophyll-a. Reflectance is used as input data on the algorithm used. In the process of atmospheric correction, every place needs a different approach algorithm model because each place has a different atmospheric character depending on the climate and character of the area. Therefore, the study of the use of atmospheric correction to a particular area needs to be studied further related to its effectiveness and models appropriate correction. There are some basic algorithms that can be used for calculation of chlorophyll-a using Landsat TM satellite imagery, such as: 1. Wouthuyzen Algorithm [7] Chl = 10,359 (TM2/TM1) – 2,355 (1) 2. Wibowo Algorithm [8] Log Chl = 2,41 (TM3/TM2) + 0,187 (2) 3. Pentury Algorithm [9] Chl = 2,3868 (TM2/TM1) -0,4671 (3) 4. Much Jisin dan Lestari Laksmi Algorithm [10] Chl = 17,912 (퐵1−퐵2) − 0,3343 (4) 퐵1+퐵2 Where TM1, TM2, TM3 is number of band on landsat TM satelit imagery 2. RESEARCH METHODOLOGY 2.1 Materials The data used in this study are: 1. Chlorophyll-a in situ On April 29, 2016. 2. Data Distribution coordinate points each sample point on 29 April, 2016. 3. Landsat 8 Path 120 Row 65 Acquisition of 29 April 2016. 4. Quickbird imagery in June 2015. 5. Data salinity dated October 15, 2013. 6. The horizontal visibility, wind speed and wind speed azimuth April 29th, 2016. 7. Pigments Concentration April 29, 2016. 8. Solar zenithal angel, Solar Azimuthal angel, angel zenithal Sensor, Sensor Azimuthal angel. 9. Data acquisition Landsat 8 April 29, 2016. The tools or equipment of research are : 1. GPS Handheld, for determine position of sample 2. Sample packing of chlorophyll-A Insitu 3. Spectrofotometer 2.2 Methods This study used a model of atmospheric correction 6SV, FLAASH and Dark of substraction (DOS). It was applied to four algorithm. The results of the four algorithms were regressed with the data in situ chlorophyll. The best model algorithm was determined from the highest value of R2 (coeficient of determination) and lowest RMSE. The algorithm selected, then statistically tested using the t test. This test to check how much influence the atmospheric correction to the accuracy Page 58 The IJICS (International Journal of Informatics and Computer Science) Vol 5 No 1, March 2021, Page 57-63 Abdi Suknomo, Estimation Chlorophyll-a Using Landsat-8 Imagery in Shallow Water: Effect of Atmospheric and Algorithm of estimation. Area of this research located at shallow marine in districs of Wedung, Demak, Central Java.
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