PEMANFAATAN CITRA LANDSAT 8 UNTUK IDENTIFIKASI KONSENTRASI TOTAL SUSPENDED SOLID (TSS) DI PERAIRAN TELUK LAMBEUSO

2019 ◽  
Vol 6 (1) ◽  
pp. 37-42
Author(s):  
Anissa Zuhrita
Author(s):  
Bambang Trisakti ◽  
Nana Suwargana ◽  
I Made Parsa

Land conversion occurred in the lake catchment area caused the decreasing of water quality in many lakes of Indonesia. According to Lake Ecosystem Management Guidelines from Ministry of Environment, tropic state of lake water is one of parameters for assessing the lake ecosystem status. Tropic state can be indicated by the quantity of nitrogen, phosphorus, chlorophyll, and water clarity. The objective of this research is to develop the water quality algorithm and map the water clarity of lake water using Landsat 8 data. The data were standardized for sun geometry correction and atmospheric correction using Dark Object Subtraction method. In the first step, Total Suspended Solid (TSS) distributions in the lake were calculated using a semi empirical algorithm (Doxaran et al., 2002), which can be applied to a wide range of TSS values. Secchi Disk Transparency (SDT) distributions were calculated using our water clarity algorithm that was obtained from the relationship between TSS and SDT measured directly in the lake waters. The result shows that the water clarity algorithm developed in this research has the determination coefficient that reaches to 0,834. Implementation of the algorithm for Landsat 8 data in 2013 and 2014 showed that the water clarity in Kerinci Lake waters was around 2 m or less, but the water clarity in Tondano Lake waters was around 2 – 3 m. It means that Kerinci Lake waters had lower water clarity than Tondano Lake waters which is consistent with the field measurement results.


2017 ◽  
Vol 42 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Ulung Jantama Wisha ◽  
Ruzana Dhiauddin ◽  
Gunardi Kusumah

The Kampar River estuary has a unique tidal bore, namely Bono. A tidal bore is a natural phenomenon caused by the tidal flow which meet the flow of the river. Tidal bore "Bono" has an impact on the transport of suspended particles which is pretty much along the Kampar River. The purpose of this study is to determine the estimated concentration of total suspended solid in the river as the result of the transport by Bono in Kampar River estuary by Landsat 8 OLI. The primary data are Landsat 8 OLI sensor – on Path 126 and Row 60, recording date was on 23 -04-2016, which was analyzed spatially – and TSS in situ. The secondary data are tide forecasting data and topographical map of Indonesia. Distribution of total suspended solid indicates sediment transport and its distribution by TSS values ranged between 10-150 mg.L-1 and TSS in situ value ranged between 42-241 mg.L-1. Tidal range ranged from 0.78 to 4.2 m and current velocity ranged from 0-0.9 m.s-1, which generate tidal bore extending from the mouth to the river body, resulting in suspended particle transport along the river. TSS concentration is higher in the river estuary.


2019 ◽  
Vol 51 (1) ◽  
pp. 42
Author(s):  
Hendrata Wibisana ◽  
Bangun Muljo Soekotjo ◽  
Umboro Lasminto

Total suspended solid (TSS) is one of the parameters that uses for detecting health in aquatic environments. The distribution of the TSS value in the water body will affect the aquatic ecosystem. In this research will be analyzed the distribution value of TSS during 5 year period by utilizing Landsat 8 satellite image data, where the developed method is extraction of reflectance value from Landsat 8 satellite image for 5 years using SEADASS and then compiled the TSS algorithm with reflectance value that already obtained on the existing conditions, the algorithm obtained is estimated over 5 years back to get a picture of change and distribution of TSS value. As a case study , the coast of Ujung Pangkah Gresik was taken which has the mouth of the river Bengawan Solo. The results obtained from this study illustrate the decrease of TSS value during that time period, so that with this decrease can be concluded that at the point of field coordinate, TSS value was decreasing and causing the erosion in the environment.


GEOMATIKA ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 25
Author(s):  
Niken Dwi Wijayanti

<p>Perairan Porong merupakan daerah muara sungai yang mengalami proses sedimentasi akibat bermuaranya air Sungai Porong ke Selat Madura yang membawa sedimen. Hal tersebut diduga akan menyebabkan terjadinya perubahan garis pantai yang ada di sekitarnya. Disamping itu, perubahan morfologi daratan seperti abrasi atau sedimentasi dipengaruhi oleh faktor oseanografi fisik seperti arus. Penelitian ini bertujuan untuk memahami pengaruh arus terhadap distribusi <em>Total Suspended Solid</em> (TSS) serta dampaknya terhadap perubahan garis pantai di Perairan Sidoarjo-Pasuruan. Data yang digunakan yaitu citra Landsat 7 (2002) dan Landsat 8 (2013 dan 2017) yang diperoleh dari<em> United States Geological Survey </em>serta data arus dari <em>Copernicus Marine Environment Monitoring Service</em>. Penginderaan jauh digunakan untuk menganalisa perubahan garis pantai dan distribusi TSS. Hasil penelitian menunjukkan arus, dengan kecepatan 0.02-0.1 m/s, di Perairan Sidoarjo-Pasuruan berpengaruh terhadap distribusi TSS dengan arah menuju Barat dan Barat Laut. Konsentrasi TSS yang tinggi di perairan dekat pantai menyebabkan terjadinya perubahan garis pantai yang ditandai dengan tingginya sedimentasi di lokasi tersebut. Lebih lanjut hasil menunjukkan bahwa perubahan garis pantai di Sidoarjo-Pasuruan tahun 2002-2013 sebesar 9,305 km dan 2013-2017 sebesar 3,226 km. Peningkatan konsentrasi TSS di Perairan Sidoarjo-Pasuruan sebanding dengan penambahan garis pantai.</p><p><em><br /></em></p>


Author(s):  
Muchlisin Arief ◽  
Syifa Wismayati Adawiah ◽  
Maryani Hartuti ◽  
Ety Parwati

Remote sensing technique is a powerful tool for monitoring the coastal zone. Optical sensors can be used to measure water quality parameters Total Suspended Matter (MPT). In order to be able to extract information MPT, the satellite data need to be validated with in situ measurements that make the relationship between the reflectance band with concentration MPT measurement results. In this model, do the correlation between the measurement results with the reflectance values band 3 and band 4. then obtained a linear equation, then calculated using the argument of a ratio of 60:75 to each of the correlation coefficient, the obtained linear equation two Dimension T (X3, X4) = 2313.77 X3 + 4741.11 X4 + 314.95. Based on the concentration MPT of dated June 3, 2015 was lower than in the west to the east. this is because the east is already contaminated with the plant, effluent solids by humans, while the west for still many floating net fish, and mangrove. Based on the results of measurement and calculation results , is still far from perfect (accuracy 60%), one factor is the value thresholding, when determining the boundary between: clouds, sea, and land. Generally indicates that the model is still in need for repair. Abstrak Penginderaan jauh adalah alat yang ampuh untuk memantau zona pesisir. Sensor optik dapat digunakan untuk mengukur parameter kualitas air Total Suspended Solid/Muatan Padatan Tersuspensi (MPT). Agar supaya dapat mengekstraksi informasi MPT, maka, data satelit perlu divalidasi dengan pengukuran in situ yaitu membuat hubungan antara reflektansi band dengan konsentrasi MPT hasil pengukuran. Pada model ini, dilakukan korelasi antara hasil pengukuran dengan nilai reflektansi band3 dan band4, maka diperoleh persamaan linier, kemudian dihitung dengan menggunakan dalil perbandingan 60 : 75, untuk masing-masing koefisien korelasinya, maka diperoleh persamaan linier dua dimensi T(X3,X4) = 2313.77 X3 + 4741,11 X4 + 314.95.  Berdasarkan konsentrasi MPT  pada 3 Juni 2015 di sebelah baratlebih rendah dibandingkan sebelah timur. Hal ini dikarenakan sebelah timur sudah terkontaminasi dengan pabrik, buangan benda padat oleh manusia, sedangkan sebelah barat karena masih banyak keramba jaring apung ikan dan mangrove. Berdasarkan hasilnya antara pengukuran dan hasil perhitungan, masih jauh dari sempuna (ketelitiannya 60 %), salah satu faktornya adalah dalam menentukan nilai thresholding, pada saat  menentukan batas antara: awan, laut dan darat. Secara umum menunjukkan bahwa model yang masih membutuhkan perbaikan.


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