scholarly journals A Comparative Study on the Generation of COMS Level 3 Product for Sea Surface Temperature

2015 ◽  
Vol 10 (1) ◽  
pp. 43-56
Author(s):  
Dae-Sun Kim ◽  
◽  
Kwang-Jin Kim ◽  
Jaeil Cho ◽  
Sung-Rae Chung ◽  
...  
Keyword(s):  
Comparative Study ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Level 3

scholarly journals Geographic Information System for Tuna Fishing Areas in Bitung waters

2018 ◽  
Vol 6 (2) ◽  
pp. 147
Author(s):  
J. Ch. Kumaat ◽  
M. M. F. Rampengan ◽  
S. T. B. Kandoli
Keyword(s):  
Temperature Distribution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Sea Surface ◽  
Modis Data ◽  
Surface Temperature Distribution ◽  
Tuna Fishing ◽  
Level 3 ◽  
Data Level

The existence of the fishing in the waters will always be dynamic, constantly changing or changed following the movement of environmental conditions, which naturally fish will choose a more appropriate habitat. Predicted zone of Tuna fish catch can be done by detecting the distribution of chlorophyll-a and sea surface temperature distribution from Aqua MODIS image.  This study aims to predict the local zone tuna fishing in the sea around the city of Bitung based on the distribution of chlorophyll-a and sea surface temperature by using satellite image Aqua MODIS data level-3. A series of research activities are conducted in stages are: image collection, image cutting in accordance with the desired area, image extraction, data interpolation, map overlay, and the last is the map layout.  The result of sea surface temperature (SST) and chlorophyll-a concentration in the ocean waters of Bitung and surrounding areas shows the chlorophyll-a and sea surface temperature varies each season. The highest chlorophyll-a distribution is in the second transitional season in September and the lowest in the west season in December. The highest sea surface temperature distribution is in the eastern seasons in June and the lowest in the eastern seasons in August. The results showed at some of the most potential fishing points of Tuna in the transitional season II wherein each month in the season potentially forming the Tuna fishing areaKeywords: Tuna, chlorophyll-a, SST, Aqua, Modis ABSTRAK Keberadaan daerah penangkapan ikan di perairan akan selalu bersifat dinamis, selalu berubah atau berpindah mengikuti pergerakan kondisi lingkungan, yang secara alamiah ikan akan memilih habitat yang lebih sesuai.  Zona tangkapan ikan Tuna yang diprediksi dapat dilakukan dengan mendeteksi distribusi klorofil-a dan distribusi suhu permukaan laut dari citra Aqua MODIS. Penelitian ini bertujuan untuk memprediksi zona lokal penangkapan ikan tuna di laut sekitar kota Bitung, berdasarkan distribusi klorofil-a dan suhu permukaan laut dengan menggunakan citra satelit Aqua MODIS data level-3. Serangkaian kegiatan penelitian yang dilakukan secara bertahap adalah: koleksi gambar, pemotongan gambar sesuai dengan area yang diinginkan, ekstraksi gambar, interpolasi data, overlay peta, dan terakhir adalah tata letak peta. Hasil dari Suhu Permukaan Laut (SST) dan konsentrasi klorofil-a di perairan laut Bitung dan sekitarnya menunjukkan klorofil-a dan suhu permukaan laut bervariasi setiap musim. Distribusi klorofil-a tertinggi adalah pada musim peralihan kedua pada bulan September dan terendah di musim barat pada bulan Desember. Distribusi suhu permukaan laut tertinggi adalah di musim timur pada bulan Juni dan terendah di musim timur pada bulan Agustus. Hasil penelitian menunjukkan pada beberapa titik penangkapan ikan Tuna yang paling potensial pada musim peralihan II dimana setiap bulan di musim tersebut berpotensi membentuk daerah penangkapan Tuna.Kata Kunci: Tuna, Chlorofil-a, SPL, Aqua, Modis

JPSS VIIRS level 3 uncollated sea surface temperature product at NOAA

2017 ◽  
Vol 11 (3) ◽  
pp. 032405 ◽  
Author(s):  
Alexander Ignatov ◽  
Irina Gladkova ◽  
Yanni Ding ◽  
Fazlul Shahriar ◽  
Yury Kihai ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Level 3

scholarly journals SEBARAN SUHU PERMUKAAN LAUT (SPL) SECARA SPASIAL DAN TEMPORAL DI PERAIRAN SELAT ALAS PROVINSI NUSA TENGGARA BARAT

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Didik Santoso
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Image ◽  
Temporal Distribution ◽  
Secondary Data ◽  
Sea Surface ◽  
Primary Data ◽  
Average Temperature ◽  
Level 3 ◽  
Research Period

Abstrak: Tujuan dari penelitian ini adalah unutk Menentukan sebaran suhu permukaan laut (SPL) secara spasial dan temporal  di Selat Alas Provinsi NTB. Lokasi penelitian di wilayah perairan Selat Alas. Waktu penelitian selama 5 bulan yaitu dari bulan Agustus-Desember 2015. Data penelitian berupa data primer SPL Selat Alas dan data sekunder berupa data citra satelit Aqua MODIS Level-3 dengan resolusi spasial 0,05o x 0,05o dan resolusi temporal 8 harian sebagai data bulanan yang cakupan waktunya dari Agustus 2008 sampai dengan Desember 2012. Data dianalisis dengan menggunakan algoritma Miami Pathfinder SST (MPFSST). Hasil penelitian menunjukkan bahwa secara spasial sebaran SPL Selat Alas didominasi oleh suhu rendah terutama yang berlokasi di bagian selatan, dan bagian tengah selat dengan suhu rata-rata sebesar 26.50C. Sedangkan secara temporal sebaran SPL wilayah perairan Selat Alas menunjukkan bahwa penurunan SPL terjadi disetiap bulan Agustus dan mulai meningkat pada bulan berikutnya, hingga mencapai suhu tertinggi pada bulan Desember, dan hal ini berulang setiap tahunnya. Suhu tinggi mendominasi seluruh bagian selat dengan suhu rata-rata 29.50C pada bulan November dan 29.00C pada bulan Desember. Akan tetapi pada bulan Desember, pada bagian utara selat suhu rata-rata nya  lebih tinggi dari daerah lainnya yaitu sebesar 29.70C.  Kata kunci: Citra Satelit , Selat Alas, Suhu Permukaan Laut, Spasial, Temporal Abstract: The purpose of this study is to determine the spatial and temporal distribution of sea surface temperature (SST) in the Alas Strait of NTB Province. Research location in the Alas Strait waters. The research period  is 5 months, from August to December 2015. The research data are in the form of primary data on the Alas Strait Sea Surface Temperature and secondary data in the form of Aqua satellite image MODIS Level-3, with spatial resolution of 0.05o x 0.05o and 8 daily temporal resolutions, as monthly data from August 2008 to December 2012. Data were analyzed using the Miami Pathfinder SST algorithm (MPFSST). The results of the study indicate that spatially the distribution of Alas Strait Surface Temperature is dominated by low temperatures, especially those located in the south, and the central part of the strait with an average temperature of 26.50C. While temporally the distribution of Sea Surface Temperature in the Alas Strait waters region shows that the decline occurred every August and began to increase the following month, until it reached the highest temperature in December, and this recurs every year. High temperatures dominate the entire strait with an average temperature of 29.50C in November and 29.00C in December. However, in December, in the northern part of the strait the average temperature was higher than other regions, which amounted to 29.70C. Keywords: Satellite Imagery, Alas Strait, Sea Surface Temperature, Spatial, Temporal 

scholarly journals Impact of Sea Surface Temperature and Measurement Sampling on the SMOS Level 3 Salinity Products

2014 ◽  
Vol 11 (7) ◽  
pp. 1245-1249 ◽  
Author(s):  
Roberto Sabia ◽  
Alejandro Cristo ◽  
Marco Talone ◽  
Diego Fernandez-Prieto ◽  
Marcos Portabella
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Level 3

scholarly journals MENGENAL SUHU PERMUKAAN LAUT DARI PENGINDERAAN JAUH

OSEANA ◽  
2017 ◽  
Vol 42 (4) ◽  
pp. 40-54
Author(s):  
Marindah Yulia Iswari
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Ocean Color ◽  
Temperature Data ◽  
Sea Surface ◽  
Physical Parameters ◽  
Sensing Technology ◽  
Level 3 ◽  
Surface Temperature Data

IDENTIFYING SEA SURFACE TEMPERATURE THROUGH REMOTE SENSING. Sea surface temperature is one of the physical parameters of oceanography that is useful to determine the water quality. Sea surface temperature can be observed using remote sensing technology. Remote sensing sensors must have a thermal infrared or a passive microwave to identify sea surface temperature. NASA's Ocean Color Web has provided sea surface temperature data processed by NASA's Ocean Biology Processing Group (OBPG) team. MODIS and VIIRS are remote sensing instruments used for sea surface temperature data on NASA's Ocean Color Web. The SST data provided in the form of data level 2 and level 3 are processed in daily, weekly, monthly and even yearly.

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