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All Journal JFMR (Journal of Fisheries and Marine Research) MAJALAH ILMIAH GLOBE International Journal of Remote Sensing and Earth Sciences (IJReSES) The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Rizki Hanintyo
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Earth & Planetary Sciences Education Engineering Environmental Science

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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.
VARIABILITAS KLOROFIL-A MELALUI SATELIT MULTI RESOLUSI PULAU BALI, INDONESIA Rizki Hanintyo; Dinarika Jatisworo
JFMR (Journal of Fisheries and Marine Research) Vol 5, No 2 (2021): JFMR VOL 5 NO.2
Publisher : JFMR (Journal of Fisheries and Marine Research)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2021.005.02.26

Abstract

Klorofil-a (Chl-a) merupakan informasi yang sangat penting untuk mengetahui kesuburan suatu perairan. Dalam studi ini kami menyajikan analisis komparatif variabilitas klorofil-a dari produk level 3 Chl-a pada  4 (empat) data satelit yaitu Aqua MODIS, VIIRS-SNPP, Himawari-8, dan Sentinel 3 OLCI pada wilayah Selat Bali. Analisis didasarkan pada data rerata bulanan Chl-a pada tahun 2020. Hasil perhitungan rerata statistik menunjukkan bahwa informasi chl-a pada satelit Aqua MODIS dan Sentinel 3 OLCI mengalami peningkatan nilai rerata di bulan mei hingga agustus sedangkan pada satelit Himawari 8 AHI dan Suomi NPP VIIRS cenderung stabil dan tidak menunjukkan variasi. Variabilitas klorofil-a sangat nampak di daerah selat bali dan cenderung statis di daerah kepulauan Nusa Penida dan bali utaraChlorophyll-a (Chl-a) is very important information to determine the fertility of water. In this study, we present a comparative analysis of the variability of chlorophyll-a from level 3 Chl-a products on 4 (four) satellite data, namely Aqua MODIS, VIIRS-SNPP, Himawari-8, and Sentinel 3 OLCI in the Bali Strait region. The analysis is based on Chl-a's monthly average data in 2020. The results of mean statistical calculations show that the Chl-a concentration has been increased at mei to august from Aqua MODIS and Sentinel 3 OLCI satellite data. In the other hand, Himawari 8 AHI and Suomi NPP VIIRS tend to be stable and didn’t show any variation. The Chl-a concentration showed high variability in bali strait area and tend to be stable in Nusa Penida Island and north bali seas.
ANALISIS SPASIO-TEMPORAL VARIABILITAS SUHU PERMUKAAN LAUT DI WILAYAH PENGELOLAAN PERIKANAN BERDASARKAN DATA SATELIT MODIS AQUA: STUDI KASUS DI WPP 573 DAN WPP 715 Dinarika Jatisworo; Denny Wijaya Kusuma; Bambang Sukresno; Rizki Hanintyo
Majalah Ilmiah Globe Vol. 22 No. 2 (2020): GLOBE VOL 22 NO 2 TAHUN 2020
Publisher : Badan Informasi Geospasial

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Wilayah Pengelolaan Perairan (WPP) 573 akan lebih dipengaruhi oleh fenomena yang terjadi pada Samudra Hindia, sedangkan Samudra Pasifik akan lebih dominan berpengaruh terhadap karakteristik di WPP 715. Penelitian ini bertujuan untuk melihat variabilitas dan tren suhu permukaan laut (SPL) selama16 tahun (2003-2018) dengan menggunakan data satelit Aqua MODIS. Hasil penelitian menunjukkan variabilitas SPL tahunan di WPP 715 cenderung lebih hangat 0,3ºC dibandingkan dengan SPL tahunan WPP 573. Tren kenaikan suhu teridentifikasi signifikan hanya pada WPP 715 dengan besaran kemiringan 0,038 per tahun, sedangkan di WPP 573 juga terjadi kenaikan suhu dengan kemiringan sebesar 0,029 per tahun namun tidak signifikan berdasarkan perhitungan statistik. Sebaran suhu hangat tahunan secara spasial pada WPP 573 adalah selatan perairan Selat Sunda, Laut Sawu, Selat Lombok, Selat Alas, dan Laut Arafura bagian selatan, sedangkan di WPP 715 adalah Teluk Tomini, pesisir Laut Halmahera, Teluk Berau, dan Teluk Bintuni.
RETRIEVING COASTAL SEA SURFACE TEMPERATURE FROM LANDSAT-8 TIRS FOR WANGI-WANGI ISLAND, WAKATOBI, SOUTHEAST SULAWESI, INDONESIA Eko Susilo; Rizki Hanintyo; Adi Wijaya
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2019.v16.a3044

Abstract

The new Landsat generation, Landsat-8, is equipped with two bands of thermal infrared sensors (TIRS). The presence of two bands provides for improved determination of sea surface temperature (SST) compared to existing products. Due to its high spatial resolution, it is suitable for coastal zone monitoring. However, there are still significant challenges in converting radiance measurements to SST, resulting from the limitations of in-situ measurements. Several studies into developing SST algorithms in Indonesia waters have provided good performance. Unfortunately, however, they have used a single-band windows approach, and a split-windows approach has yet to be reported. In this study, we investigate both single-band and split-window algorithms for retrieving SST maps in the coastal zone of Wangi-Wangi Island, Wakatobi, Southeast Sulawesi, Indonesia. Landsat-8 imagery was acquired on February 26, 2016 (01: 51: 44.14UTC) at position path 111 and and row 64. On the same day, in-situ SST was measured by using Portable Multiparameter Water Quality Checker – 24. We used the coefficient of correlation (r) and root mean square error (RMSE) to determine the best algorithm performance by incorporating in-situ data and the estimated SST map. The results showed that there were differences in brightness temperature retrieved from TIRS band10 and band 11. The single-band algorithm based on band 10 for Poteran Island clearly showed superior performance (r = 69.28% and RMSE = 0.7690°C). This study shows that the split-window algorithm has not yet produced a accurate result for the study area.
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 Adi Wijaya Ari Murdimanto Bambang Sukresno Bambang Sukresno Denny Wijaya Kusuma Dinarika Jatisworo Eko Susilo