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

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

DERIVING INHERENT OPTICAL PROPERTIES FROM MERIS IMAGERY AND IN SITU MEASUREMENT USING QUASI-ANALYTICAL ALGORITHM

The  paper  describes inherent optical properties  (IOP)  of  the  Berau  coastal  waters  derived from in  situ measurements  and Medium  Resolution  Imaging  Spectrometer  (MERIS) satellite  data. Field  measurements  of optical  water,  total  suspended  matter  (TSM), and  chlorophyll-a  (Chl-a) concentrations were carried out during the dry season of 2007. During this periode, only four MERISdata were  coincided with in  situ measurements on 31 August  2007. The MERIS  top-of-atmosphere radiances were atmospherically corrected using the MODTRAN radiative transfer model. The in situ optical  measurement  have  been  processed  into apparent optical properties  (AOP) and sub  surface irradiance. The remote sensing reflectance of in situ measurement as well as MERIS data were inverted into  the  IOP  using quasi-analytical algorithm  (QAA).  The  result  indicated  that coefficient  of determination (R 2) of backscattering coefficients of suspended particles (bbp) increased with increasing wavelength,  however  the  R2 of  absorption  spectra  of  phytoplankton  (aph)  decreased  with  increasing wavelength

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

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

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

DETECTION OF TOTAL SUSPENDED SOLIDS DISTRIBUTION USING EMPIRICAL AND SEMI-ANALYTICAL MODELS IN BEKASI

Salah satu parameter dalam kualitas air adalah muatan padatan tersuspensi (MPT). Muatan padatan tersuspensi terdiri dari lumpur, pasir dan jasad renik yang disebabkan pengikisan tanah yang terbawa ke badan air. Penelitian ini bertujuan untuk mendeteksi sedimen tersuspensi di perairan Bekasi. Landsat 8 digunakan untuk analisis padatan tersuspensi dengan platform Google Earth Engine dengan membandingkan antara model empiris dan semi-analitik. Alur studi ini meliputi deliniasi wilayah non air menggunakan data citra surface reflectance, analisis MPT, dan visualisasi. Selanjutnya dilakukan validasi dengan data in situ, pemilihan model dan implementasi time series. Hasil deteksi MPT tertampil dengan tampilan warna yang berbeda sesuai dengan konsentrasinya. Hasil uji validasi dengan data in situ menunjukkan nilai Normalized Mean Absolute Error (NMAE) model semi-analitik lebih mendekati syarat minimum yaitu sebesar 66,8%, berbeda jauh dengan model empiris sebesar 43768%. Nilai Root Mean Square Error (RMSE) pun terlihat bahwa model semi-analitik menghasilkan nilai yang jauh lebih kecil sebesar 51,4 dan model empiris sebesar 58577,2. Hal ini menunjukkan bahwa model semi-analitik memiliki nilai yang lebih baik dalam mendeteksi sebaran MPT. Analisis time series menunjukkan bahwa persebaran MPT tahun 2015 – 2019 di perairan pesisir memiliki sebaran MPT yang sangat tinggi, karena banyaknya tambak dan muara sungai. Oleh karena itu, model semi-analitik lebih direkomendasikan untuk mengestimasi konsentrasi MPT dibandingkan dengan model empiris.One of the parameters in water quality is total suspended solids (TSS). TSS consists of mud and microorganisms caused by erosion of soil flowed into water bodies. This study aimed to detect suspended sediments in Bekasi coastal water by comparing empirical and semi-analytic models. Landsat 8 was used for analysis of suspended solids using the Google Earth Engine platform. The workflow of this study consisted of land masking by area delineation using surface reflectance image data, TSS analysis, and visualization. Then validation was done with in situ data, model selection and time series implementation. TSS detection results were displayed with a different color display according to the concentration. Validation test results with in situ data showed that the value of the Semi-Analytical Absolute Error (NMAE) model was closer to the minimum requirement of 66.8%, far different from the empirical model of 43768%. The value of Root Mean Square Error (RMSE) also showed that the semi-analytic model produced a much smaller value of 51.4 and the empirical model of 58577.2. This showed that the semi-analytic model has a better value in detecting the distribution of TSS. Time series analysis showed that the distribution of MPT in 2015 - 2019 in coastal waters had a very high TSS distribution, due to the number of ponds and river estuaries. Therefore, semi-analytical model was more recommended for estimating TSS concentrations than empirical model

Analisis Distribusi Total Suspended Matter Dan Klorofil-a Menggunakan Citra Terra Modis Level 1b Resolusi 250 Meter Dan 500 Meter (Studi Kasus Daerah Pesisir Kabupaten Pesawaran Provinsi Lampung Tahun 2012)

TSM (Total Suspended Matter) adalah material tersuspensi berupa zat organik maupun anorganik yang memiliki diameter >1mm yang berada di permukaan air, sedangkan Klorofil-A adalah kelompok pigmen fotosintesis yang menyerap cahaya biru, dan merah, serta merefleksikan cahaya hijau. Keduanya dengan jumlah yang besar dapat menutupi permukaan air dan membuat air menjadi hangat dan mengurangi kemampuan air untuk memenuhi kebutuhan oksigen untuk kehidupan biota laut dengan kata lain dapat menganggu ekosistem perairan. Dalam pengamatan kualitas air, perlu adanya pengamatan tentang TSM dan Klorofil-A untuk waktu dan tempat yang spesifik, serta berkelanjutan. Data pengideraan jauh dapat menganalisa beberapa parameter dalam cara spasial dan temporal. Akan tetapi masalahnya adalah sulit untuk menemukan algoritma yang sesuai untuk setiap daerah. Dikarenakan setiap daerah memiliki karakteristik yang belum tentu sama. Dengan menggunakan data time series akan lebih baik dalam memonitoring kondisi kualitas air. MODIS adalah satelit yang memiliki time series harian, jadi sangat bagus untuk pengamatan daerah perairan. Data yang digunakan dalam pengamatan ini adalah Terra-MODIS level 1B resolusi 250 meter dan 500 meter bulan januari sampai september dan di validasi dengan data in situ bulan Agustus 2012. Beberapa model persamaan digunakan dalam penelitian ini untuk menganalisis sebaran konsentrasi TSM dan Klorofil-A. Hasil pengolahan data didapatkan transformasi kromatisiti kanal merah pada MODIS dapat digunakan untuk analisa sebaran koefisien TSM dengan nilai koefisien korelasi (R2) sebesar 0,484 sedangkan rasio antara kanal NIR dengan Kanal biru dapat digunakan untuk analisa sebaran konsentrasi Klorofil-A dengan koefisien korelasi sebesar (R2) 0,924

PERBANDINGAN KARAKTERISTIK SPEKTRAL (SPECTRAL SIGNATURE) PARAMETER KUALITAS PERAIRAN PADA KANAL LANDSAT ETM+ DAN ENVISAT MERIS (COMPARISON OF WATER CONSTITUENTS SPECTRAL SIGNATURE ON LANDSAT ETM+ AND ENVISAT MERIS BAND)

Pada penelitian ini dilakukan analisa konsentrasi tiga parameter kualitas perairan yang secara aktif mempengaruhi perjalanan cahaya pada kolom air, yaitu Total Suspended Matter (TSM), Chlorophyll a (Chl a) dan Color Dissolved Organic Matter (CDOM)) menggunakan data in situ hasil pengukuran spektroradiometer (350-950 nm, interval 3.3 nm) dan nilai konsentrasinya masing-masing hasil analisa laboratorium. Nilai remote sensing reflectance (Rrs) diturunkan dari pengukuran nilai radiance dan irradiance dengan menggunakan pendekatan bio-optical model. Karakteristik spektral dari nilai Rrs ini kemudian diubah kedalam jumlah kanal sensor ETM+ dan MERIS menggunakan informasi sensitivitas respon spektral (spectral response sensitivity) dari masing-masing sensor. Nilai Rrs yang sudah diubah digunakan untuk mengestimasi nilai konsentrasi tiga parameter kualitas perairan menggunakan metode optimisasi. Nilai konsentrasi yang dihasilkan kemudian divalidasi dengan konsentrasi hasil pengukuran laboratorium. Sensor ETM+ dengan empat kanal-nya hanya memberikan informasi lebih baik untuk TSM (R2=0.70) dan CDOM (R2=0.64), sedangkan untuk Chl a hanya memberikan nilai koefisien determinasi (R2) sebesar 0.46. Sensor MERIS dengan 10 kanal-nya memberikan hasil yang lebih baik dari sensor ETM+, dengan nilai koefisien determinasi (R2) lebih besar dari 0.70 untuk semua parameter. Nilai RMSE untuk sensor MERIS juga memperlihatkan hasil yang lebih baik dibandingkan sensor ETM+, dimana nilai RMSE dari sensor MERIS masing-masing 16.84 gm-3 (TSM), 2.66 mg m-3 (Chl a ) dan 0.26 m-1 (CDOM)). Sementara itu nilai RMSE dari sensor ETM+ adalah19.89 gm-3 (TSM), 4.96 mg m-3 (Chl a) dan 0.29 m-1 (CDOM). Kata kunci: Kualitas perairan, Landsat ETM+, Envisat MERIS, Spektroradiomete

Analisis Indeks Vegetasi Mangrove Teluk Gerupuk dan Teluk Ratai Menggunakan Landsat-8

Hal.13-26 : ilu

Kajian spesifikasi sensor satelit untuk pemantauan sumber daya pesisir dan laut

Hal.4-9 : ilus. ; 28 c