TIME SERIES ANALYSIS OF TOTAL SUSPENDED SOLID (TSS) USING LANDSAT DATA IN BERAU COASTAL AREA, INDONESIA

Water quality information is usually used for the first examination of the pollution.  One of the parameters of water quality is Total Suspended Solid (TSS), which describes the amount of matter of particles suspended in the water. TSS information is also used as initial information about waters condition of a region. TSS could be derive from Landsat data with several combinations of spectral channels to evaluate the condition of the observation area for both the waters and the surrounding land. The study aimed to evaluate Berau waters condition in Kalimantan, Indonesia, by utilizing TSS dynamics extracted from Landsat data. Validated TSS extraction algorithm was obtained by choosing the best correlation between  field data and image data. Sixty pairs of points had been used to build validated TSS algorithms for the Berau Coastal area. The algorithm was TSS = 3.3238 * exp (34 099 * Red Band Reflectance). The data used for this study were Landsat 5 TM, Landsat 7 ETM and Landsat 8 data acquisition in 1994, 1996, 1998, 2002, 2004, 2006, 2008 and 2013. For detailed evaluation, 20 regions were created along the watershed up to the coast. The results showed the fluctuation of TSS values in each selected region. TSS value increased if there was a change of any kind of land cover/land used into bareland, ponds, settlements or shrubs. Conversely, TSS value decreased if there was a wide increase of mangrove area or its position was very closed to the ocean

DIGITAL IMAGE PROCESSING OF SPOT-4 FOR SHORELINE EXTRACTION IN LAMPUNG BAY

Shoreline is an imaginary line separating land and seawater. The intensification of land used/land cover at Lampung bay causes shoreline change either abrasions or accretions. The objectives of this study were to compare the shoreline extraction based on the digital image processing of SPOT-4 using ratio band of infrared and green band, Normalized Difference Vegetation Index (NDVI), and (band infrared) methods and to analyze shoreline change at Lampung Bay. Those methods applied on both cloudy free and cloudy SPOT-4 images and the result compared with RBI map as reference. The result showed that the best metod for shoreline axtraction was ratio band due to accuracy high and stable eventhough it applied on cloudy image. The shoreline changes at Lampung Bay along 2008 to 2012 caused by accretions. The total area of accretion at Lampung Bay for fours years were 662 Ha with the rates 165 Ha/year. The high of accretion rate caused by reclamation for urban built up, fishponds and mangrove

THE EFFECT OF THE EXTENT OF CORAL REEF AREA ON UNIFORM BOTTOM REFLECTANCE DETERMINATION FOR WATER COLUMN CORRECTION USING LANDSAT ETM

In one pixel of 30 meter spatial resolution of Landsat ETM multispectral sensor might consist of mixed bottom substrate types. The influence of a mixture of bottom substrate on the Landsat data can be a source of errors and together with the extent of coral reef area might contribute to affect the determination of uniform bottom reflectance. This study aimed to assess the effect of the extent of coral reef area on uniform bottom reflectance determination for water column correction. Lyzenga method was used for water column correction. This study carried out in two case studies using two sites with different size of coral reef ecosystems area i.e., Tidung island, in the Province of Jakarta and Maratua island, in the Province of East Kalimantan. Tidung island was selected to represent small area of coral reef ecosystem, while Maratua island was selected to represent relatively larger area of coral reef ecosystem. The results showed that the extent of coral reef influenced the determination of training sample areas for uniform bottom reflectance using Landsat ETM. The combination of moderate spatial resolution and the small area of coral reef ecosystem lead to the difficulties for uniform bottom substrate type determination at different depths

HARMFUL ALGAL BLOOM 2012 EVENT VERIFICATION IN LAMPUNG BAY USING RED TIDE DETECTION ON SPOT 4 IMAGE

In mid-December 2012, harmful algal bloom phenomenon occurred in Lampung Bay. Harmful Algal Bloom (HAB) is blooming of algae in aquatic ecosystems. It has negative impact on living organism, due to its toxic. This study was applied Red Tide (RT) detection algorithm on SPOT 4 images and verified the distribution of HAB 2012 event in Lampung Bay. The HAB event in 2012 in Lampung Bay can be detected by using RT algorithm on SPOT 4 images quantitatively and qualitatively. According to field measurement, the phytoplankton blooming which happen at Lampung Bay in 2012 were Cochlodinium sp. Image analysis showed that Cochlodinium sp has specific pattern of RT with values, digitally, were 13 to 41 and threshold value of red band SPOT 4 image was 57. The total area of RT distribution, which are found in Lampung Bay, was 11,545.3 Ha. Based on the RT classification of RT images and field data measurement, the RT which is caused many fishes died on the western coastal of Lampung Bay spread out from Bandar Lampung City to Batumenyan village. By using confusion matrix, the accuracy of this this method was 74.05 %. This method was expected to be used as early warning system for HAB monitoring in Lampung Bay and perhaps in another coastal region of Indonesia

INTERSEASONAL VARIABILITY IN THE ANALYSIS OF TOTAL SUSPENDED SOLIDS(TSS) IN SURABAYA COASTAL WATERS USING LANDSAT-8 SATELLITE DATA

The spatial and temporal capabilities of remote sensing data are very effective for monitoring the value of total suspended solids(TSS) in water using optical sensors. In this study,TSS observations were conductedin the westseason, transition season 1, east season, and transition season 2 in 2018 and 2019. Landsat 8 image data wereused,extracted into TSS values using a semi-analytic model developed in the Mahakam Delta, East Kalimantan, Indonesia. The TSS data obtained were then analysed for distribution patterns in each season. The sample points were randomly scattered throughout the study area. The TSS distribution pattern in the west season showeda high concentration spread over the coastal area to theoff sea, while the pattern in the east season only showeda high concentration inthecoastal areas. Transitional seasons1 and 2 showed different patterns of TSS distribution in 2018 and 2019, with more varied values. The distribution of TSS is strongly influenced by the season. Observation of each cluster resultedin the conclusion thathuman activity and the rainfall rate can affect the concentration of TSS

PREDIKSI POLA PERSEBARAN TUMPAHAN MINYAK MENGGUNAKAN DATA CITRA SATELIT SENTINEL-1 DI PERAIRAN BINTAN, KEPULAUAN RIAU

Bintan is one of the regions with annual cases of oil spills, which were excluded from tank cleaning and black waste disposal activities. In arranging oil spill response, it is important to know the areas that are potentially affected, using oil spill trajectory model by GNOME. SAR (Sentinel-1) data is used to create coordinates for oil spills location in GNOME. SAR data processing is using SNAP software, with Lee Algorithm filter (window 5x5). The areas that potentially exposed to oil spills are known based on Environmental Sensitivity Index (ESI). In this model, oil spill will reach the Bintan Coast within 2 to 5 days with average surface current speed of 4.28 m/s (West Monsoon). The estimated of oil total amount is 1,767 barrel, which 1,157 barrel polluted the coast, 606 barrel has evaporation and dispersion and the other 4 barrel was off map. The most sensitive area to oil spills are Trily Resort Center Bintan and Sebong Bay (Index 10D). The ESI average among the Bintan region are Index 3A and 3B such as Lagoi, Tanjung Berakit, Pulau Pangkil, Pulau Mapur, Cabana, Pulau Lobam, Pantai Mayang Sari, Pantai Indah Club Med Bintan, Bintan Lagoon Resort, Pantai Senggiling, and Pengudang

THE RELATIONSHIP BETWEEN TOTAL SUSPENDED SOLID (TSS) AND CORAL REEF GROWTH (CASE STUDY OF DERAWAN ISLAND, DELTA BERAU WATERS)

Total suspended solid (TSS) is one of the water quality parameters and limiting factor affecting coral reef growth. In this study, we used the algorithm of TSS= 3.3238*e(34.099* Green band) (where green band is reflectance band 2) to extract TSS from Landsat satellite data. The algorithm was validated with field data. Water column correction method developed by Lyzenga was used to map coral reef. The result showed that the coral reef area in Berau waters decreased significantly (about 12,805 ha or around 36 % ) from the year of 1979 to 2002. The most coral reef reduced area was detected around Derawan Island (about 5,685 ha). Further, some areas changed into sand dune. TSS concentration around Delta Berau and Derawan Island increased aproximately twice from 15- 35 mg/l in 1979 to 20-65 mg/l in 2002. The increase of TSS concentration was followed by the decrease of coral reef area

Pengembangan Model Identifikasi Habitat Bentik Menggunakan Pendekatan Segmentasi Object-Based Image Analysis (OBIA) dan Algoritma Machine Learning (Studi Kasus: Pulau Pari, Kepulauan Seribu)

Identifikasi dan klasifikasi habitat bentik di perairan dangkal menggunakan citra satelit semakin berkembang. Pengembangan model dalam mengidentifikasi objek habitat bentik sangat penting untuk mengisi kebutuhan pemetaan habitat bentik dengan akurasi yang memadai. Penelitian ini bertujuan untuk mengembangkan model identifikasi habitat bentik dari data citra satelit penginderaan jauh menggunakan metode segmentasi berbasis objek dan algoritma klasifikasi machine learning. Tiga pendekatan klasifikasi digital yang digunakan adalah support vector machine (SVM), decision tree (DT) dan random forest (RF). Ketiga algoritma tersebut diterapkan pada hasil segmentasi citra berbasis objek untuk menguji akurasi dari hasil klasifikasi habitat bentik. Data yang digunakan adalah citra satelit resolusi tinggi SPOT 6 yang diakuisisi pada wilayah Gugus Pulau Pari pada tanggal 20 Mei 2020. Hasil penelitian menunjukkan pendekatan segmentasi berbasis objek membentuk pola segmen yang lebih rapat pada obyek heterogen dibandingkan dengan obyek yang relatif homogen (misalnya obyek daratan dan perairan). Algoritma machine learning yang diterapkan pada hasil segmentasi berbasis objek menghasilkan nilai akurasi keseluruhan (overall accuracy) lebih dari 70% untuk setiap algoritma, dengan rincian hasil adalah 75.83% untuk SVM, 74.17% untuk DT, dan 83.33% untuk RF. Dari ketiga algoritma machine learning yang diterapkan pada hasil segmentasi berbasis objek terlihat algoritma RF memiliki nilai akurasi yang paling baik dibandingkan dengan algoritma lainnya

ALGORITMA DUA DIMENSI UNTUK ESTIMASI MUATAN PADATAN TERSUSPENSI MENGGUNAKAN DATA SATELIT LANDSAT-8, STUDI KASUS: TELUK LAMPUNG

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