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PERBANDINGAN ANTARA INFORMASI SUHU PERMUKAAN LAUT DARI DATA SATELIT DENGAN HASIL PEMODELAN DI WPP NRI-716 Komang Iwan Suniada
Bumi Lestari Journal of Environment Vol 16 No 1 (2016)
Publisher : Environmental Research Center (PPLH) of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/blje.2016.v16.i01.p05

Sea Surface Temperature (SST) data and information recently become a valuableinformation since its association with the climate, oceanography condition and fisherieshave been discovered. Unfortunately, SST information using satellite imagery frequentlyconstrained by atmospheric cloud cover since satellite sensor disability to gather any landor ocean surface information through the cloud. Modeling data is very required to fill theblank data resulted from satellite imagery under cloudy condition. This study conducted atSulawesi Sea to North Halmahera which is included to Fisheries Managing Area (FMA)716, to find out the strength and direction relationship between SST model and SST satellite.Result indicates there is a strong and same direction relationship between SST model andSST satellite (r=0.704, n=1516) with 0.2C diferrence so that SST model can be used to fillor substitute the blank of SST satellite.

CARBON STOCK ESTIMATION OF MANGROVE VEGETATION USING REMOTE SENSING IN PERANCAK ESTUARY, JEMBRANA DISTRICT, BALI Amandangi Wahyuning Hastuti; Komang Iwan Suniada; Fikrul Islamy
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 2 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Mangrove vegetation is one of the forest ecosystems that offers a potential of substantial greenhouse gases (GHG) emission mitigation, due to its ability to sink the amount of CO2 in the atmosphere through the photosynthesis process. Mangroves have been providing multiple benefits either as the source of food, the habitat of wildlife, the coastline protectors as well as the CO2 absorber, higher than other forest types. To explore the role of mangrove vegetation in sequestering the carbon stock, the study on the use of remotely sensed data in estimating carbon stock was applied. This paper describes an examination of the use of remote sensing data particularly Landsat-data with the main objective to estimate carbon stock of mangrove vegetation in Perancak Estuary, Jembrana, Bali. The carbon stock was estimated by analyzing the relationship between NDVI, Above Ground Biomass (AGB) and Below Ground Biomass (BGB). The total carbon stock was obtained by multiplying the total biomass with the carbon organic value of 0.47. The study results show that the total accumulated biomass obtained from remote sensing data in Perancak Estuary in 2015 is about 47.20±25.03 ton ha-1 with total carbon stock of about 22.18±11.76 tonC ha-1and CO2 sequestration 81.41±43.18 tonC ha-1.

Karakteristik Oseanografis Teluk Senggrong Banyuwangi Bambang Sukresno; Denny Wijaya Kusuma; Dinarika Jatisworo; Eko Susilo; Komang Iwan Suniada
Jurnal Kelautan Nasional Vol 14, No 3 (2019): DESEMBER
Publisher : Pusat Riset Kelautan

Penelitian ini ditujukan untuk mengetahui karakteristik oseanografis teluk Senggrong. Data yang digunakan meliputi suhu permukaan laut, konsentrasi klorofil-a, salinitas dan pH baik musim barat maupun musim timur. Data time series suhu permukaan laut dan klorofil-a menggunakan data dari satelit Aqua dan Terra dengan sensor Moderate Resolution Imaging Spectroradiometer (MODIS) tahun 2007 hingga 2018. Data insitu teluk Senggrong diperoleh dari pengukuran langsung yang dilakukan pada bulan April dan bulan September dengan menggunakan water quality checker (WQC). Untuk menampilkan distribusi spasial masing-masing variabel dilakukan interpolasi Krigging. Hasil penelitian menunjukan bahwa karakteristik oseanografis teluk Senggrong dipengaruhi oleh perubahan musim baik musim barat maupun musim timur. Suhu permukaan laut pada musim barat relatif lebih tinggi dibandingkan pada musim timur. Konsentrasi klorofil-a pada musim barat lebih rendah daripada musim timur. Salinitas pada musim barat lebih rendah dibandingkan pada musim timur, sedangkan pH pada musim barat lebih tinggi daripada musim timur. Pada musim barat teluk Senggrong memiliki suhu permukaan laut antara 28,1 ℃ – 31,6 ℃, konsentrasi klorofil-a sekitar 0,2 mg/m3– 0,5 mg/m3, salinitas sebesar 32 ppm – 33 ppm dan pH berkisar 8,4 – 8,7. Sedangkan pada musim timur suhu permukaan laut berkisar antara 24,9 ℃ – 30,7℃, konsentrasi klorofil-a sebesar 0,1 mg/m3 – 3,5 mg/m3, salinitas antara 34 ppm – 35 ppm dan pH sekitar 7,5 – 8,3.

VARIABILITY OF SEA SURFACE TEMPERATURE AT FISHERIES MANAGEMENT AREA 715 IN INDONESIA AND ITS RELATION TO THE MONSOON, ENSO AND FISHERY PRODUCTION Komang Iwan Suniada
International Journal of Remote Sensing and Earth Sciences Vol. 17 No. 2 (2020)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2020.v17.a3370

Sea surface temperature (SST) is one of the important oceanographic and climateparameters. Its variability and anomalies often influence the environment and organisms, both in theoceans and on land. This study aims to identify the variability of SST and help the fisheriescommunity to understand how climate phenomena such as ENSO and monsoonal phases (representedby wind speed) are related to SST and fishery production in Fisheries Management Area (FMA) 715.SST was measured at Parimo, which represents conditions in the western part of the area insideTomini Bay, and at Bitung, which represents SST in the open ocean, with a more exposuredgeographical position. SST was derived from MODIS satellite imagery, downloaded from the oceancolordatabase (https://oceancolor.gsfc.nasa.gov/) with a 4 km spatial resolution, from January 2009 toDecember 2018. Wind speed data, historical El Niño or La Niña events, and fish production data werealso used in the study. Pearson’s correlation (Walpole, 1993) was used to test the relationshipbetween SST variability or anomaly and ENSO and monsoons. The results show that the SSTcharacteristics and variability of the Parimo and Bitung waters are very different, although they bothlie in the same FMA 715. SST in Parimo waters is warmer, but with lower variability than in Bitungwaters. SST in Parimo has a low correlation with ENSO (r=0.06, n=66), low correlation with windspeed (r=-0.29, n=120), with also a low correlation between SST anomaly and ENSO (r=0.05, n=66).SST in Bitung has a higher, but inverse, correlation with ENSO (r=-0.53, n=66), high correlation withwind speed (r=-0.60, n=119), with also a high correlation between SST anomaly and ENSO (r=-0.74,n=66). Unlike in other parts of Indonesia, fishery production in Parimo, or the western part insideTomini Bay, is not affected by ENSO events.

ROLLING MOSAIC METHOD TO SUPPORT THE DEVELOPMENT OF POTENTIAL FISHING ZONE FORECASTING FOR COASTAL AREAS Komang Iwan Suniada; Eko Susilo; Wingking Era Rintaka Siwi; Nuryani Widagti
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 2 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2019.v16.a3252

The production of the Indonesian Institute for Marine Research and Observationâ€™s mapping of forecast fishing areas (peta prakiraan daerah penangkapan ikan or PPDPI) based on passive satellite imagery is often constrained by high-cloud-cover issues, which lead to sub-optimal results. This study examines the use of the rolling mosaic method for providing geophysical variables, in particular, seasurface temperature (STT) together with minimum cloud cover, to enable clearer identification of oceanographic conditions. The analysis was carried out in contrasting seasons: dry season in July 2018 and rainy season in December 2018. In general, the rolling mosaic method is able to reduce cloud cover for sea-surface temperature (SST) data. A longer time range will increase the coverage percentage (CP) of SST data. In July, the CP of SST data increased significantly, from 15.3 % to 30.29% for the reference 1D mosaic and up to 84.19 % to 89.07% for the 14D mosaic. In contrast, the CP of SST data in December tended to be lower, from 4.93 % to 13.03% in the 1D mosaic to 41.48 % to 51.60% in the14D mosaic. However, the longer time range decreases the relationship between the reference SST data and rolling mosaic method data. A strong relationship lies between the 1D mosaic and 3D mosaics, with correlation coefficients of 0.984 for July and 0.945 for December. Furthermore, a longer time range will decrease root mean square error (RMSE) values. In July, RMSE decreased from 0.288Â°C (3D mosaic) to 0.471Â°C (14D mosaic). The RMSE value in December decreased from 0.387Â°C (3D mosaic) to 0.477Â°C (14D mosaic). Based on scoring analysis of CP, correlation coefficient and RMSE value, results indicate that the 7D mosaic method is useful for providing low-cloud-coverage SST data for PPDPI production in the dry season, while the 14D mosaic method is suitable for the rainy season.

CARBON STOCK ESTIMATION OF MANGROVE VEGETATION USING REMOTE SENSING IN PERANCAK ESTUARY, JEMBRANA DISTRICT, BALI Amandangi Wahyuning Hastuti; Komang Iwan Suniada; Fikrul Islamy
International Journal of Remote Sensing and Earth Sciences Vol. 14 No. 2 (2017)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2017.v14.a2841

Mangrove vegetation is one of the forest ecosystems that offers a potential of substantial greenhouse gases (GHG) emission mitigation, due to its ability to sink the amount of CO2 in the atmosphere through the photosynthesis process. Mangroves have been providing multiple benefits either as the source of food, the habitat of wildlife, the coastline protectors as well as the CO2 absorber, higher than other forest types. To explore the role of mangrove vegetation in sequestering the carbon stock, the study on the use of remotely sensed data in estimating carbon stock was applied. This paper describes an examination of the use of remote sensing data particularly Landsat-data with the main objective to estimate carbon stock of mangrove vegetation in Perancak Estuary, Jembrana, Bali. The carbon stock was estimated by analyzing the relationship between NDVI, Above Ground Biomass (AGB) and Below Ground Biomass (BGB). The total carbon stock was obtained by multiplying the total biomass with the carbon organic value of 0.47. The study results show that the total accumulated biomass obtained from remote sensing data in Perancak Estuary in 2015 is about 47.20Â±25.03 ton ha-1 with total carbon stock of about 22.18Â±11.76 tonC ha-1and CO2 sequestration 81.41Â±43.18 tonC ha-1.

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