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<![CDATA[VARIABILITY AND VALIDATION OF SEA SURFACE TEMPERATURE ESTIMATED BY PATHFINDER ALGORITHM OF NOAA-AVHRR SATELLITE IN THE NORTH PAPUA WATERS ]]>
<![CDATA[Bisman Nababan]]>;
<![CDATA[Bidawi Hasyim]]>;
<![CDATA[Hilda I.N. Bada]]>
<![CDATA[ International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 8, (2011) ]]>
Publisher : <![CDATA[National Institute of Aeronautics and Space of Indonesia (LAPAN) ]]>
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DOI: 10.30536/j.ijreses.2011.v8.a1738
<![CDATA[Variability and validation of sea surface temperatures (SST) in north Papua waters were conducted using SST estimated by Pathfinder algorithm of NOAA AVHRR satellite and SST measurements from TAO buoy in 2001-2009. Satellite data (SST Pathfinder) were daily, weekly, and monthly composite with 4x4 km2 resolution and downloaded from http://poet.jpl.nasa.gov. In situ data (SST measurement from buoy TAO) were measured at a depth of 1.5 m and recorded every hour (http://www.pmel.noaa.gov/tao_deliv). The in situ data then converted into daily, weekly, and monthly average data. In general, the SST values of both satellite and in situ SST in the north Papua waters ranged between 27.10 - 31.90 °C. During the east season (June-September), SST values (27.90-31.90 °C) were generally higher than the SST values ( 27.10-30.13 °C) during the west season (December-February). In general, the SST values both day-time and night-time from in situ and the satellite measurements showed no significant differences except in waters close to the shore. The results also showed that the coefficient of determination values (R2) between the satellite and the in situ SST measurements were relatively low (65%) and up to 5% of RMSE. The relatively low correlation between in situ dan satellite SST measurements may be due to high cloud coverage (90-96%) in the north Papua waters so that SST satellite data become less representative of the in situ data. These results also indicated that the Pathfinder algorithm can not be used as a valid estimate of SST NOAA AVHRR satellite for the north Papua waters. Keywords: SST Pathfinder, NOAA AVHRR, Validation, TAO buoy, North Papua Waters]]>
<![CDATA[DOWNWELLING DIFFUSE ATTENUATION COEFFICIENTS FROM IN SITU MEASUREMENTS OF DIFFERENT WATER TYPES ]]>
<![CDATA[Bisman Nababan]]>;
<![CDATA[Veronica S.A. Louhenapessy]]>;
<![CDATA[Risti E Arhatin]]>
<![CDATA[ International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 10, No 2 (2013) ]]>
Publisher : <![CDATA[National Institute of Aeronautics and Space of Indonesia (LAPAN) ]]>
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DOI: 10.30536/j.ijreses.2013.v10.a1851
<![CDATA[Process of light reduction or loss (attenuation) by scattering and absorption is affected bysolar zenith, time, depth, and seawater constituents. Downwelling diffuse attenuation coefficient (Kd)is important to understand for light penetration and biological processes in ocean ecosystem. It is,therefore, important to know the Kd value and its variability in ocean ecosystem. The objective of thisstudy was to determine downwelling diffuse attenuation coefficients and its variability form in situmeasurements of different water types. In situ downwelling irradiances (Ed) were measured using asubmersible marine environmental radiometer instrument (MER) during a clear sky, calm watercondition, and at the time range of 10:30 a.m. up to 14:00 p.m. local time in the northeastern Gulf ofMexico in April 2000. In general, Ed values decreases exponentially with depth. Ed at 380 nmexhibited the lowest attenuation (the most penetrative light), while Ed at 683 nm exhibited the highestattenuation (the most light loss at the top of water column). Overall, the Kd patterns tended to decreasefrom 380 nm to 490 nm (blue-green wavelength), and increase from 490 nm to 683 nm (green-redwavelength). Kd values in offshore region were relatively lower than in coastal region. Kd can be usedto determine the depth of euphotic zone in offshore or teh case-1 water type and the depth of oneoptical depth (the water column depth where the ocean color satellite can possibly sense).]]>
<![CDATA[VARIABILITAS SUHU PERMUKAAN LAUT DAN KONSENTRASI KLOROFIL-A DI SAMUDERA HINDIA BAGIAN TIMUR LAUT, BARAT SUMATERA ]]>
<![CDATA[Bisman Nababan]]>;
<![CDATA[Evelyn Grace Br Sihombing]]>;
<![CDATA[James P. Panjaitan]]>
<![CDATA[ Jurnal Teknologi Perikanan dan Kelautan Vol 12 No 2 (2021): NOVEMBER 2021 ]]>
Publisher : <![CDATA[Fakultas Perikanan dan Ilmu Kelautan ]]>
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DOI: 10.24319/jtpk.12.143-159
<![CDATA[Variabilitas suhu permukaan laut (SPL) dan konsentrasi klorofil-a (Chl-a) di Samudera Hindia bagian Timur Laut sebelah barat Sumatera diteliti menggunakan data satelit selama kurun waktu 22 tahun. Penelitian ini menggunakan gabungan data citra NOAA-AVHRR dan MODIS untuk SPL, data citra SeaWiFS dan MODIS untuk Chl-a, data angin permukaan bulanan diperoleh dari European Centre for Medium-Range Weather Forecasts (ECMWF). Data pendukung berupa indeks El Nino Southern Oscillation (ENSO) bulanan diperoleh dari laman https://www.ncdc.noaa.gov/teleconnections/enso/ indicators/soi/ dan Dipole Mode Index (DMI) bulanan diperoleh dari laman https://www.jamstec.go.jp/ virtualearth/general/en/index.html. Hasil penelitian menunjukkan bahwa SPL di daerah penelitian selama 22 tahun (1997-2019) berada pada kisaran 27,57°C-34,41°C. Nilai SPL yang lebih tinggi terjadi saat Musim Barat sampai Musim Peralihan-1, sementara nilai yang lebih rendah pada Musim Timur sampai Musim Peralihan-2. Variabilitas nilai SPL dipengaruhi oleh pola angin musiman, intensitas radiasi matahari, dan Indian Ocean Dipole Mode (IODM). Saat IOD Negatif menyebabkan nilai SPL yang lebih tinggi dan konsentrasi Chl-a lebih rendah dari biasanya. Konsentrasi klorofil-a selama 22 tahun berkisar antara 0,0757 mg/m3-1,3006 mg/m3, konsentrasi klorofil-a yang lebih tinggi terjadi saat akhir Musim Timur (Agustus) dan awal Musim Barat (Desember), sementara nilai yang lebih rendah saat Musim Peralihan-1. Tingginya SPL pada Musim Peralihan-1 (Maret-Mei) bersamaan dengan rendahnya Chl-a pada musim yang sama diduga akibat terjadinya fenomena IOD negatif. Variabilitas Chl-a dipengaruhi oleh pola angin musiman, pergerakan massa air, dan IOD.]]>
<![CDATA[VARIABILITAS SUHU PERMUKAAN LAUT DAN KONSENTRASI KLOROFIL-A DI PERAIRAN PALABUHANRATU DAN SEKITARNYA ]]>
<![CDATA[Bisman Nababan]]>;
<![CDATA[Afriandika D. Nirmawan]]>;
<![CDATA[James P. Panjaitan]]>
<![CDATA[ Jurnal Teknologi Perikanan dan Kelautan Vol 13 No 2 (2022): NOVEMBER 2022 ]]>
Publisher : <![CDATA[Fakultas Perikanan dan Ilmu Kelautan ]]>
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DOI: 10.24319/jtpk.13.145-162
<![CDATA[Penelitian ini bertujuan untuk mengetahui variabilitas Suhu Permukaan Laut (SPL) dan konsentrasi klorofil-a (Chl-a) di perairan Palabuhanratu dan sekitarnya. Penelitian ini menggunakan gabungan data citra satelit NOAA-AVHRR dan MODIS untuk SPL, SeaWiFS dan MODIS untuk Chl-a, data angin permukaan bulanan dari European Centre for Medium-Range Weather Forecasts (ECMWF). Data pendukung berupa indeks El Nino Southern Oscillation (ENSO) dan indeks dipole mode (DMI) bulanan. Hasil penelitian menunjukkan bahwa SPL di daerah penelitian selama 21 tahun (1997-2018) berada pada kisaran 23,14-33,45°C dimana SPL tertinggi terjadi saat akhir Musim Peralihan-1 (Mei), sementara nilai paling rendah ditemui pada saat awal Musim Peralihan-2 (September). Konsentrasi klorofil-a selama 21 tahun berkisar 0,063-13,363 mg/m3 dimana nilai Chl-a paling tinggi terjadi saat awal Musim Peralihan-2 (September), sementara nilai yang paing redah ditemui pada saat akhir Musim Peralihan-1 (Mei). Saat ENSO dan IOD positif terjadi bersamaan menyebabkan kecepatan angin Tengara meningkat sehinga mengakibatkan peningkatan intensitas upwelling di Perairan Palabuhanratu dan sekitarnya yang mengakibatkan nilai SPL yang lebih rendah dan konsentrasi Chl-a yang lebih tinggi dari biasanya. Variabilitas nilai SPL dan Chl-a dipengaruhi oleh pola angin musiman, intensitas radiasi matahari, fenomena anomali iklim ENSO, dan Indian Ocean Dipole Mode (IODM). Tingginya konsentrasi klorofil-a pada sekitar bulan Agustus-Oktober bersamaan dengan rendahnya SPL pada bulan yang sama diduga akibat terjadinya fenomena upwelling.]]>
<![CDATA[PEMETAAN PARTISIPATIF DAN MONITORING PENGELOLAAN KEBUN KEMENYAN MASYARAKAT DESA HUTA PAUNG KECAMATAN POLLUNG ]]>
<![CDATA[Jonson Lumban-Gaol]]>;
<![CDATA[Bisman Nababan]]>;
<![CDATA[Riza Aitiando Pasaribu]]>;
<![CDATA[Muhammad]]>;
<![CDATA[Ni Putu Ratna Suhita]]>
<![CDATA[ Jurnal Rekayasa Teknik Sipil dan Lingkungan - CENTECH Vol. 4 No. 1 (2023): Jurnal Rekayasa Teknik Sipil dan Lingkungan, APRIL ISSN 2722-0230 (Online) ]]>
Publisher : <![CDATA[UKI Press ]]>
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DOI: 10.33541/cen.v4i1.4803
<![CDATA[The community has managed the benzoin forest in Paung Village, Pollung District, for hundreds of years, but the land ownership status is state land. In line with government programs to involve the community in forest management, such as by establishing social forests, it is necessary to conduct preparations such as mapping the boundaries of community forest management. In this community service activity, the boundaries of community benzoin forest management have been mapped with the application of geospatial technology, namely the integration of remote sensing satellite technology and the Global Positioning System (GPS) to determine boundary coordinates. Boundary mapping of the benzoin forest was carried out in a participatory manner by directly involving the community who had conducted activities in the benzoin forest. Based on mapping the boundaries of the Benzoin forest management area, the average area managed by the community is around 2 ha per family. The monitoring results around the benzoin forest show decreased vegetation cover. But the vegetation land cover in the Benzoin forest management area of the Paung village Forest Village community has not changed. The benzoin forest area of the Puang village community is maintained since the community uses benzoin resin, so trees are not cut down.]]>
<![CDATA[PEMETAAN EKOSISTEM LAMUN DENGAN DAN TANPA KOREKSI KOLOM AIR DI PERAIRAN PULAU PAJENEKANG, SULAWESI SELATAN ]]>
<![CDATA[Ilyas, Turissa Pragunanti]]>;
<![CDATA[Bisman Nababan]]>;
<![CDATA[Hawis Madduppa]]>;
<![CDATA[Dony Kushardono]]>
<![CDATA[ Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 12 No. 1 (2020): Jurnal Ilmu dan Teknologi Kelautan Tropis ]]>
Publisher : <![CDATA[Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University ]]>
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DOI: 10.29244/jitkt.v12i1.26598
<![CDATA[Koreksi kolom air dalam pemetaan habitat bentik menggunakan data satelit dapat meningkatkan nilai akurasi informasi yang dihasilkan, seperti yang telah dilakukan oleh peneliti sebelumnya. Penelitian ini bertujuan untuk melihat distribusi lamun dengan perlakuan dengan dan tanpa koreksi kolom air menggunakan klasifikasi berbasis objek (OBIA) di Pulau Pajanekang. Data sebaran padang lamun dan non lamun sebanyak 347 titik diambil pada Juli-Agustus 2018 dengan transek 1x1 m2. Data satelit yang digunakan adalah citra satelit SPOT-7 akuisisi pada 27 Maret 2017 dengan resolusi 6x6 m2. Pada penelitian ini metode klasifikasi OBIA menggunakan beberapa algoritma klasifikasi seperti Support Vector Machine (SVM), Bayes, K-Nearest Neighbour (KNN), dan Decision Tree (DT) untuk memetakan habitat bentik dan lamun. Hasil penelitian menunjukkan bahwa penerapan perlakuan dengan koreksi kolom air dan tanpa koreksi kolom air pada pemetaan ekosistem habitat bentik dan lamun dengan menggunakan beberapa algoritma klasifikasi menunjukkan hasil akurasi yang tidak berbeda nyata. Namun demikian, dari empat algoritma yang digunakan, algoritma Bayes tanpa koreksi kolom air memberikan nilai akurasi tertinggi untuk pemetaan habitat bentik sebesar 70,36% dan habitat lamun sebesar 66,47%. Hal tersebut menunjukkan bahwa koreksi kolom air tidak selamanya memberikan hasil yang lebih baik dalam klasifikasi habitat bentik dan lamun dari citra satelit digital.]]>
<![CDATA[Klasifikasi Habitat Dasar Berbasis Objek di Perairan Dangkal Karang Lebar dan Pulau Lancang: Classification of Benthic Habitat based on Object in Shallow Waters of Karang Lebar and Lancang Island ]]>
<![CDATA[Siregar, Vincentius]]>;
<![CDATA[Nababan, Bisman]]>;
<![CDATA[Utama, Pria Wibawa]]>
<![CDATA[ Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 15 No. 2 (2023): Jurnal Ilmu dan Teknologi Kelautan Tropis ]]>
Publisher : <![CDATA[Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University ]]>
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DOI: 10.29244/jitkt.v15i2.36036
<![CDATA[Teknik klasifikasi berbasis objek (OBIA) merupakan salah satu teknik pemetaan habitat bentik selain metode konvensional (berbasis piksel). Pemetaan metode OBIA dengan memanfaatkan algoritma machine learning terbatas pada perairan Karang Lebar dan Pulau Lancang. Penelitian ini bertujuan untuk mengetahui performa algoritma machine learning (support vector machine (SVM), decision tree (DT), random forest (RF), dan k-nearest neighbour (KNN) dalam mengklasifikasikan habitat bentik perairan dangkal berdasarkan objek menggunakan data satelit Sentinel-2. Metode klasifikasi yang digunakan adalah metode OBIA dengan dua tingkatan analisis. Hasil analisis Agglomerative Hierarchial Clustering diperoleh sebanyak 6 kelas habitat bentik yaitu karang, patahan karang (rubble), lamun, pasir rubble, dan pasir. Tingkat pertama adalah memisahkan darat, laut dangkal dan laut lebih dalam. Tingkat kedua adalah klasifikasi menggunakan algoritma machine learning, hasil klasifikasi menunjukkan alogritma SVM mendapatkan nilai akurasi yang lebih tinggi dibandingkan algoritma lainnya dengan akurasi sebesar 84% di perairan Karang Lebar, kemudian pada perairan Pulau Lancang mendapatkan akurasi sebesar 80% dengan algoritma SVM. Habitat dasar perairan dangkal Karang Lebar dan Pulau Lancang mampu dipetakan dengan baik menggunakan metode OBIA. Perbedaan tingkat akurasi antara perairan Karang Lebar dan Pulau Lancang disebabkan oleh tingkat kekeruhan perairan.]]>
<![CDATA[VARIABILITY AND VALIDATION OF SEA SURFACE TEMPERATURE ESTIMATED BY PATHFINDER ALGORITHM OF NOAA-AVHRR SATELLITE IN THE NORTH PAPUA WATERS ]]>
<![CDATA[Bisman Nababan]]>;
<![CDATA[Bidawi Hasyim]]>;
<![CDATA[Hilda I.N. Bada]]>
<![CDATA[ International Journal of Remote Sensing and Earth Sciences Vol. 8 (2011) ]]>
Publisher : <![CDATA[BRIN ]]>
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DOI: 10.30536/j.ijreses.2011.v8.a1738
<![CDATA[Variability and validation of sea surface temperatures (SST) in north Papua waters were conducted using SST estimated by Pathfinder algorithm of NOAA AVHRR satellite and SST measurements from TAO buoy in 2001-2009. Satellite data (SST Pathfinder) were daily, weekly, and monthly composite with 4x4 km2 resolution and downloaded from http://poet.jpl.nasa.gov. In situ data (SST measurement from buoy TAO) were measured at a depth of 1.5 m and recorded every hour (http://www.pmel.noaa.gov/tao_deliv). The in situ data then converted into daily, weekly, and monthly average data. In general, the SST values of both satellite and in situ SST in the north Papua waters ranged between 27.10 - 31.90 °C. During the east season (June-September), SST values (27.90-31.90 °C) were generally higher than the SST values ( 27.10-30.13 °C) during the west season (December-February). In general, the SST values both day-time and night-time from in situ and the satellite measurements showed no significant differences except in waters close to the shore. The results also showed that the coefficient of determination values (R2) between the satellite and the in situ SST measurements were relatively low (65%) and up to 5% of RMSE. The relatively low correlation between in situ dan satellite SST measurements may be due to high cloud coverage (90-96%) in the north Papua waters so that SST satellite data become less representative of the in situ data. These results also indicated that the Pathfinder algorithm can not be used as a valid estimate of SST NOAA AVHRR satellite for the north Papua waters.]]>
<![CDATA[DOWNWELLING DIFFUSE ATTENUATION COEFFICIENTS FROM IN SITU MEASUREMENTS OF DIFFERENT WATER TYPES ]]>
<![CDATA[Bisman Nababan]]>;
<![CDATA[Veronica S.A. Louhenapessy]]>;
<![CDATA[Risti E. Arhatin]]>
<![CDATA[ International Journal of Remote Sensing and Earth Sciences Vol. 10 No. 2 (2013) ]]>
Publisher : <![CDATA[BRIN ]]>
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DOI: 10.30536/j.ijreses.2013.v10.a1851
<![CDATA[Process of light reduction or loss (attenuation) by scattering and absorption is affected by solar zenith, time, depth, and seawater constituents. Downwelling diffuse attenuation coefficient (Kd) is important to understand for light penetration and biological processes in ocean ecosystem. It is, therefore, important to know the Kd value and its variability in ocean ecosystem. The objective of this study was to determine downwelling diffuse attenuation coefficients and its variability form in situ measurements of different water types. In situ downwelling irradiances (Ed) were measured using a submersible marine environmental radiometer instrument (MER) during a clear sky, calm water condition, and at the time range of 10:30 a.m. up to 14:00 p.m. local time in the northeastern Gulf of Mexico in April 2000. In general, Ed values decreases exponentially with depth. Ed at 380 nm exhibited the lowest attenuation (the most penetrative light), while Ed at 683 nm exhibited the highest attenuation (the most light loss at the top of water column). Overall, the Kd patterns tended to decrease from 380 nm to 490 nm (blue-green wavelength), and increase from 490 nm to 683 nm (green-red wavelength). Kd values in offshore region were relatively lower than in coastal region. Kd can be used to determine the depth of euphotic zone in offshore or teh case-1 water type and the depth of one optical depth (the water column depth where the ocean color satellite can possibly sense).]]>
<![CDATA[COMPARISON OF CHLOROPHYLL CONCENTRATION ESTIMATION USING TWO DIFFERENT ALGORITHMS AND THE EFFECT OF COLORED DISSOLVED ORGANIC MATTER ]]>
<![CDATA[Bisman Nababan]]>
<![CDATA[ International Journal of Remote Sensing and Earth Sciences Vol. 5 (2008) ]]>
Publisher : <![CDATA[BRIN ]]>
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DOI: 10.30536/j.ijreses.2008.v5.a1232
<![CDATA[The effect of colored dissolved organic matter (CDOM) on the Sea-viewing Wide Field-of-view Sensor(Sea WiFS) OC4v4 and the MODIS algorithms used to estimate chlorophyll-a was studied using satellite and situ data collated during seasonal cruises in the Northeastern Gulf of Mexico between 1997 and 2000. For chlorophyll-a concentrations 50 mg m, OC4v4 generally overestimated chlorophyll-a concentration by up to 300 percent. The MODIS algorithm provided better estimates of high CDOM concentration, found typically nearshore in noterhn summer and spring. For oceanic waters where chlorophyll-a concentrations 1.0 mg m, both OC4v4 and MODIS algorithm had errors within the Sea WiFS mission specification (35 percent) during fall. The OC4v4 algorithm is more susceptible to artifacts due to CDOM absorption of light at 443 mm.]]>
