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All Journal JFMR (Journal of Fisheries and Marine Research) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital International Journal of Remote Sensing and Earth Sciences (IJReSES) The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Ari Murdimanto
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Earth & Planetary Sciences Engineering Environmental Science

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ANALISIS PENERAPAN METODE GAP FILLING UNTUK OPTIMALISASI PEROLEHAN DATA SUHU PERMUKAAN LAUT BEBAS AWAN DI SELAT BALI Dinarika Jatisworo; Ari Murdimanto; Denny Wijaya Kusuma; Bambang Sukresno; Dessy Berlianty
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 2 Desember 2018
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (971.173 KB) | DOI: 10.30536/j.pjpdcd.2018.v15.a2981

Abstract

Sea Surface Temperature (SST) sensed from infrared satellite sensors has a limitation caused by clouds cover. This limitation affects SST data to be not optimal because there are many empty areas without SST information. Gap Filling is a simple method for combining multitemporal satellite data to generate cloud free data. This research will apply Gap Filling method from two SST data, namely Himawari-8 and Multiscale Ultrahigh Resolution Sea Surface Temperature (MUR-SST). Cloud free daily SST data generated by this method has ~2 Km spatial resolution and daily temporal resolution. Validation of cloud-free SST data using in situ measurement data shows Mean Absolute Deviation (MAD) value 0.29 is smaller than MAD value from MUR-SST and Himawari-8 data. High correlation between cloud free SST data and insitu data is reflected from Kendall's Tau correlation value of 0.7966 or 79.66% and R2 with 0.93 value. These results indicate that the cloud free daily SST data can be used as valid estimation of SST condition in Bali Strait.
THREE-WAY ERROR ANALYSIS OF SEA SURFACE TEMPERATURE (SST) BETWEEN HIMAWARI-8, BUOY, AND MUR SST IN SAVU SEA Bambang Sukresno; Rizki Hanintyo; Denny Wijaya Kusuma; Dinarika Jatisworo; Ari Murdimanto
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 1 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1152.453 KB) | DOI: 10.30536/j.ijreses.2018.v15.a2855

Abstract

Variance errors of Himawari-8, buoy, and Multi-scale Ultra-high Resolution (MUR) SST in Savu Sea have been investigated. This research used level 3 Himawari-8 hourly SST, in situ measurement of buoy, and daily MUR SST in the period of December 2016 to July 2017. The data were separated into day time data and night time. Skin temperature of Himawari-8 and subskin tempertaure of MUR SST were corrected with the value of 15∆Tdept">  before compared with buoy data. Hourly SST of Himawari-8 and buoy data were converted to daily format by averaging process before collocated with MUR SST data. The number of 2,264 matchup data are obtained. Differences average between Himawari-8, buoy and MUR SST were calculated to get the value of variance (Vij).  Using three-way error analysis, variance errors of each observation type can be known. From the analysis results can be seen that the variance error of Himawari-8, buoy and MUR SST are 2.5 oC, 0.28oC and 1.21oC respectively. The accuracy of buoy data was better than the other. With a small variance errors, thus buoy data can be used as a reference data for validation of SST from different observation type.
Comparison of interpolation methods for sea surface temperature data Denny Wijaya Kusuma; Ari Murdimanto; Bambang Sukresno; Dinarika Jatisworo
JFMR (Journal of Fisheries and Marine Research) Vol 2, No 2 (2018): JFMR VOL 2 NO 2
Publisher : JFMR (Journal of Fisheries and Marine Research)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1560.952 KB) | DOI: 10.21776/ub.jfmr.2018.002.02.7

Abstract

Interpolation methods have been used in many applications to produce continuous surface data based on point data. The common interpolation methods for Sea Surface Temperature (SST) data are Inverse Distance Weighted (IDW), Kriging, Natural Neighbor Interpolation (NNI), and Spline. In this study, those four interpolation methods will be reviewed and compared to find the satisfactory method. The Argo float data was chosen as SST point data and Aqua MODIS image as validation data. Each method will be reviewed and compared to Aqua MODIS data to find the best performance. The assessment for testing the best interpolation model is smooth performance, Maximum and Minimum comparison, mean comparison, Root Mean Square Error (RMSE) and Standard Deviation Difference. The result shows that IDW interpolation is the best way to make spatial interpolation for SST.
THREE-WAY ERROR ANALYSIS OF SEA SURFACE TEMPERATURE (SST) BETWEEN HIMAWARI-8, BUOY, AND MUR SST IN SAVU SEA Bambang Sukresno; Rizki Hanintyo; Denny Wijaya Kusuma; Dinarika Jatisworo; Ari Murdimanto
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 1 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a2855

Abstract

Variance errors of Himawari-8, buoy, and Multi-scale Ultra-high Resolution (MUR) SST in Savu Sea have been investigated. This research used level 3 Himawari-8 hourly SST, in situ measurement of buoy, and daily MUR SST in the period of December 2016 to July 2017. The data were separated into day time data and night time. Skin temperature of Himawari-8 and subskin tempertaure of MUR SST were corrected with the value of 15∆Tdept">  before compared with buoy data. Hourly SST of Himawari-8 and buoy data were converted to daily format by averaging process before collocated with MUR SST data. The number of 2,264 matchup data are obtained. Differences average between Himawari-8, buoy and MUR SST were calculated to get the value of variance (Vij). Using three-way error analysis, variance errors of each observation type can be known. From the analysis results can be seen that the variance error of Himawari-8, buoy and MUR SST are 2.5 oC, 0.28oC and 1.21oC respectively. The accuracy of buoy data was better than the other. With a small variance errors, thus buoy data can be used as a reference data for validation of SST from different observation type.
Co-Authors Bambang Sukresno Bambang Sukresno Denny Wijaya Kusuma Denny Wijaya Kusuma Dessy Berlianty Dinarika Jatisworo Dinarika Jatisworo Rizki Hanintyo