Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Ecotrophic, Journal of Environmental Science JFMR (Journal of Fisheries and Marine Research) MAJALAH ILMIAH GLOBE Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Bambang Sukresno
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 10 Documents
Search

 1 
PENGEMBANGAN PETA PRAKIRAAN DAERAH PENANGKAPAN IKAN Bambang Sukresno; Denny Wijaya Kusuma
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.2021.005.02.25

Abstract

Riset pengembangan Peta Prakiraan Daerah Penangkapan Ikan (PPDPI) telah berjalan sejak tahun 2000 yang dilakukan oleh Balai Riset dan Observasi Laut (BROL) - Kementerian Kelautan dan Perikanan. PPDPI merupakan salah satu upaya pemerintah dalam mendukung pengelolaan sumberdaya perikanan yang bertanggungjawab dan berkelanjutan. Dalam pengembanganya, PPDPI disusun berdasarkan pada data satelit yang mampu menyajikan parameter oseanografis dengan resolusi spatial yang tinggi serta resolusi temporal harian. Beberapa parameter yang digunakan untuk analisis antara lain suhu permukaan laut, konsentrasi klorofil-a, tinggi permukaan laut, sub surface temperature  dan dilengkapi dengan informasi kecepatan angin serta tinggi gelombang. Terdapat beberapa jenis peta yang dihasilkan, antara lain PPDPI nasional, PPDPI pelabuhan dan PPDPI spesies khusus. Metode pembuatan PPDPI pada awalnya menggunakan proses yang sederhana berupa tumpang susun (overlay) beberapa data satelit. Kemudian mengalami perkembangan dengan dilakukanya image analysis identifikasi fenomena front. Pada penyusunan PPDPI untuk spesies khusus dilakukan dengan analisis Generalized Aditif Model (GAM), sedangkan PPDPI ikan tuna disusun berdasarkan analisis Empirical Cumulative Distribution Function. Berdasarkan pada validasi menggunakan data penangkapan ikan dapat diketahui bahwa akurasi PPDPI memberikan informasi dengan akurasi yang cukup tinggi, bahkan mencapai 87,2%. Pendistribusian informasi PPDPI kepada pengguna baik nelayan maupun pemangku kepentingan dan pengambil kebijakan dilakukan dengan berbagai media sehingga dapat di akses secara mudah, cepat dan mampu menjangkau ke seluruh wilayah Indonesia. The Institute for Marine Research and Observation (IMRO) - Ministry of Marine Affairs and Fisheries has initiated research on the Potential Fishing Ground (PFG) since 2000. PFG is one of the government’s intentions to reinforce responsible and sustainable fisheries resources management. In its development, we compiled PFG based on satellite data which can provide oceanographic variables with high spatio-temporal resolution. The data employed for the assessment include sea surface temperature, chlorophyll-a concentration, sea level, subsurface temperature, and completed by information of wind speed and wave height. There are several types of maps presented, including PFG for nationwide coverage, PFG of fishing port-based, and PFG of species-based. The initial design applied to develop the PFG was a direct process of superimposing several satellite data. The further method of PFG analysis was single image edge detection to identify the sea surface temperature front. The other method performed to produce PFG of species based was the Generalized Additive Model (GAM). Furthermore, PFG for tuna was prepared based on the analysis of the Empirical Cumulative Distribution Function. Based on the validation using the fishing logbook, we can verify that the PFG provides information with high accuracy of 87.2%. The distribution of PFG information to users including fishermen, stakeholders and policy makers is carried out with various platforms so that we can access it throughout the Indonesian area.
DYNAMICAL ANALYSIS OF BANDA SEA CONCERNING WITH EL NINO, INDONESIAN THROUGH FLOW AND MONSOON BY USING SATELLITE DATA AND NUMERICAL MODEL Bambang Sukresno; I W. Kasa
ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) Vol 3 No 2
Publisher : Master Program of Environmental Science, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (336.082 KB)

Abstract

Banda sea is subjected to external force such as El Nino South Oscillation (ENSO), Indonesian Through Flow (ITF) andMonsoon. All of these component Combined with Current System, caused sea dynamic. This study aimed to get further knowledge aboutBanda sea dynamic. Based on this phenomenon , this study was conducted with an hypothesis that sea level anomaly (SLA) and seasufrace temperature (SST) will decrease during ENSO event. Also that SLA and SST will seasonally change concerning with Monsoon.The pattern of current in eastern of Banda sea will be seasonally different concerning with monsoon while in western of Banda sea isalmost constant according to ITFThis research carried out in Banda Sea within the rectangular region from 122.42 E to 131.47 E , Latitude 03.47 S to 07.65 S.in period of 1996 to 2006 consist of northwest monsoon, southeast monsoon, 1st transitional month in April and 2nd transitional monthin October. Spatial analysis used to analyze annual and seasonal distribution of SST and SLA from satellite dataset, also by comparisonbetween wind data, ITF pathway and numerical model. SST derived from NOAA / AVHRR satellite data by applying MCSST algorithm,SLA derived from Topex/ Poseidon and Jason-1 Satellite data by applying Inverse distance weighted interpolation, while numerical modelderived from barothropic model using Princeton ocean model.Sea level anomaly and sea surface temperature is decrease according to ENSO event, such as descrease of SLA and SST duringENSO event in 1997 , 2002 and 2004. Sea level anomaly and sea surface temperature is change according to Monsoon that reverse every6 (six) month. SST and SLA get maximum level during northwest monsoon in November to March and get Minimum during Southeastmonsoon in May to September. There are strong correlation coefficient between annual Sea level anomaly and annual Sea SurfaceTemperature with index value up to 0.817104. on the other side correlation coefficient between seasonal Sea level anomaly and SeasonalSea Surface Temperature is 0.576469. Based on Patern of current we found that Western part of Banda sea is strongly affected by ITFwhile eastern part of Banda sea is strongly affected by monsoon.
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.
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.
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.
Comparison of interpolation methods for sea surface temperature data Kusuma, Denny Wijaya; Murdimanto, Ari; Sukresno, Bambang; Jatisworo, Dinarika
JFMR (Journal of Fisheries and Marine Research) Vol. 2 No. 2 (2018): JFMR
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | 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.
PENGEMBANGAN PETA PRAKIRAAN DAERAH PENANGKAPAN IKAN Sukresno, Bambang; Kusuma, Denny Wijaya
JFMR (Journal of Fisheries and Marine Research) Vol. 5 No. 2 (2021): JFMR
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2021.005.02.25

Abstract

Riset pengembangan Peta Prakiraan Daerah Penangkapan Ikan (PPDPI) telah berjalan sejak tahun 2000 yang dilakukan oleh Balai Riset dan Observasi Laut (BROL) - Kementerian Kelautan dan Perikanan. PPDPI merupakan salah satu upaya pemerintah dalam mendukung pengelolaan sumberdaya perikanan yang bertanggungjawab dan berkelanjutan. Dalam pengembanganya, PPDPI disusun berdasarkan pada data satelit yang mampu menyajikan parameter oseanografis dengan resolusi spatial yang tinggi serta resolusi temporal harian. Beberapa parameter yang digunakan untuk analisis antara lain suhu permukaan laut, konsentrasi klorofil-a, tinggi permukaan laut, sub surface temperature  dan dilengkapi dengan informasi kecepatan angin serta tinggi gelombang. Terdapat beberapa jenis peta yang dihasilkan, antara lain PPDPI nasional, PPDPI pelabuhan dan PPDPI spesies khusus. Metode pembuatan PPDPI pada awalnya menggunakan proses yang sederhana berupa tumpang susun (overlay) beberapa data satelit. Kemudian mengalami perkembangan dengan dilakukanya image analysis identifikasi fenomena front. Pada penyusunan PPDPI untuk spesies khusus dilakukan dengan analisis Generalized Aditif Model (GAM), sedangkan PPDPI ikan tuna disusun berdasarkan analisis Empirical Cumulative Distribution Function. Berdasarkan pada validasi menggunakan data penangkapan ikan dapat diketahui bahwa akurasi PPDPI memberikan informasi dengan akurasi yang cukup tinggi, bahkan mencapai 87,2%. Pendistribusian informasi PPDPI kepada pengguna baik nelayan maupun pemangku kepentingan dan pengambil kebijakan dilakukan dengan berbagai media sehingga dapat di akses secara mudah, cepat dan mampu menjangkau ke seluruh wilayah Indonesia. The Institute for Marine Research and Observation (IMRO) - Ministry of Marine Affairs and Fisheries has initiated research on the Potential Fishing Ground (PFG) since 2000. PFG is one of the government’s intentions to reinforce responsible and sustainable fisheries resources management. In its development, we compiled PFG based on satellite data which can provide oceanographic variables with high spatio-temporal resolution. The data employed for the assessment include sea surface temperature, chlorophyll-a concentration, sea level, subsurface temperature, and completed by information of wind speed and wave height. There are several types of maps presented, including PFG for nationwide coverage, PFG of fishing port-based, and PFG of species-based. The initial design applied to develop the PFG was a direct process of superimposing several satellite data. The further method of PFG analysis was single image edge detection to identify the sea surface temperature front. The other method performed to produce PFG of species based was the Generalized Additive Model (GAM). Furthermore, PFG for tuna was prepared based on the analysis of the Empirical Cumulative Distribution Function. Based on the validation using the fishing logbook, we can verify that the PFG provides information with high accuracy of 87.2%. The distribution of PFG information to users including fishermen, stakeholders and policy makers is carried out with various platforms so that we can access it throughout the Indonesian area.
ANALISIS PENERAPAN METODE GAP FILLING UNTUK OPTIMALISASI PEROLEHAN DATA SUHU PERMUKAAN LAUT BEBAS AWAN DI SELAT BALI Jatisworo, Dinarika; Murdimanto, Ari; Kusuma, Denny W.; Sukresno, Bambang; Berlianty, Dessy
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 2 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v15i2.3341

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 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.
PRESENT UNDERSTANDING OF ACEH TSUNAMI (APPLICATIONS OF DATA FROM FIELD TO SATELLITE OBSERVATIONS) I Gede Hendrawan; Bambang Sukresno; Yasuhiro Sugimori
International Journal of Remote Sensing and Earth Sciences Vol. 4 (2007)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2007.v4.a1222

Abstract

Application of data from field to satellite observation and simulation has been made as present understanding of Aceh tsunami. Tsunami has attracted attention after struck Aceh in December 26th 2004, generated by a strong eartquake with magnitude Mw=9.0. The eatrhquake triggered giant tsunami waves that propagated throughout the Indian Ocean, causing extreme inundation and destruction along the northern and western coast of Sumatra. Within hours, the tsunami devastated the distant shores of Thailand to east as well as Sri Lanka, India and Maldives to the west. The tsunami also caused deaths, and destruction in Somalia and other nations of East Africa. The tsunami was recorded on tidal stations throughout the Indian Oceans in worldwide. Unlike the Pacific, the Indian Ocean does not yet have a network of deep-ocean pressure sensors, and so coastal tide gauges provide the only direct measurement of Indian Ocean stunami amplitudes. We had many lessons and basic knowledge which had already been learned from this tragic event in the Indian Ocean. Many more lessons should be learned in the near future as this tragedy unfolds and reverals many failures to value and protect human life in this neglected region of the world.
Co-Authors Ari Murdimanto Berlianty, Dessy Denny Wijaya Kusuma Denny Wijaya Kusuma Dessy Berlianty Dinarika Jatisworo Dinarika Jatisworo I Gede Hendrawan I W. Kasa Jatisworo, Dinarika Kusuma, Denny W. Kusuma, Denny Wijaya Murdimanto, Ari Rizki Hanintyo YASUHIRO SUGIMORI