Comparison of interpolation methods for sea surface temperature data D

Kusuma, Denny Wijaya; Murdimanto, Ari; Sukresno, Bambang; Jatisworo, Dinarika

doi:10.21776/ub.jfmr.2018.002.02.7

Cited by 15 publications

(12 citation statements)

References 7 publications

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“…The spline method was applied to interpolate the sea surface temperature in the southern part of the Indian Ocean [81]. Moreover, the model generated by the spline method was compared to the models interpolated by the IDW, NNI and kriging methods.…”

Section: Splinementioning

confidence: 99%

Analysis of Terrain Modelling Methods in the Coastal Zone

Lewicka¹

2023

Communications

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ResumeGeospatial data are increasingly used to model the terrain in the coastal zone, in particular in shallow waterbodies (with a depth of up to 1 m). In order to generate a terrain relief, it is important to choose a method for its modelling that will allow it to be accurately projected. Therefore, the aim of this publication is to analyze the terrain modelling methods in the coastal zone. For the purposes of the research, five most popular methods for terrain modelling were described: Inverse Distance Weighted (IDW), Modified Shepard's Method (MSM), Natural Neighbor Interpolation (NNI), kriging and spline. Each of the methods has been described in a uniform way in terms of: the essence of its operation, mathematical expression and application examples. The advantages and disadvantages of each of the methods for terrain modelling are also discussed. It should be stated that the choice of the method for the terrain modelling of a shallow waterbody is not unambiguous, as it depends on the type of data recorded during bathymetric and photogrammetric measurements.

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Section: Splinementioning

confidence: 99%

Analysis of Terrain Modelling Methods in the Coastal Zone

Lewicka¹

2023

Communications

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“…Interpolasi data spasial memiliki tujuan untuk melakukan interpolasi dari dua titik, dimana metode tersebut memperkirakan nilai sebuah variabel lokasi tidak tersampel dan berlokasi di dalam area yang dicakup oleh lokasi tersampel [11]. Terdapat empat metode interpolasi yang umum digunakan yakni Kriging, NNI, Spline, dan IDW [12]. IDW merupakan metode interpolasi yang paling baik jika dibandingkan dengan EBK, Kriging, GBI, dan LPI [12] [13].…”

Section: Pendahuluanunclassified

“…Terdapat empat metode interpolasi yang umum digunakan yakni Kriging, NNI, Spline, dan IDW [12]. IDW merupakan metode interpolasi yang paling baik jika dibandingkan dengan EBK, Kriging, GBI, dan LPI [12] [13]. Pada penelitian ini yang digunakan adalah Inverse Distance Weighting (IDW).…”

Section: Pendahuluanunclassified

Sistem Informasi Pendugaan Kekerasan Terhadap Perempuan dan Anak Menggunakan Metode Small Area Estimation

Mutiah²,

Rahmayudha³

et al. 2022

mib

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Based on data obtained from the SIMFONI-PPA Application, the Office of Women's Empowerment, Child Protection, Population Control and Family Planning (DP3AP2KB) Sambas Regency, in 2017 there were 95 cases of violence against women and children in Sambas Regency, then in 2018 there were 43 cases, followed by in 2019 as many as 49 cases, and in 2020 as many as 64 cases. This shows an increasing trend in the number of cases of violence that occur from year to year. The increasing trend is caused by the lack of access to information to make complaints, the processing of data on areas of violence that has not been integrated, so that the government does not have up-to-date data to anticipate. To support DP3AP2KB in handling and preventing violence, this research builds a system based on the estimation of violence against women and children by utilizing the Small Area Estimation Method, especially the IDW interpolation technique. This research was carried out by processing data through the ArcGIS application to determine the pattern of areas prone to violence, using interpolation techniques to predict unmeasured variables at various locations, with IDW assuming that the closer a point is to an unknown point, the greater the effect. . IDW uses the values measured at points around the location, to estimate the value of the variable at the location in question. Then the results of data processing is implemented in a web-based geographic information system. The system that has been built has been tested using the black box method and calculated using a Likert scale, obtaining a value of 86.20% which is included in the Very Good category.

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“…Sedangkan metode interpolasi dilakukan untuk mendapatkan data satelit bebas awan dengan input berupa data satelit pada satu kali perekaman. Data yang tertutup awan akan diisi dengan mempertimbangkan data di sekitarnya [21]. Di sisi lain validasi data satelit terhadap kondisi sebenarnya di perairan Indonesia perlu dilakukan, sehingga dapat diketahui akurasi antara data satelit dengan data insitu [22].…”

Section: Akurasi Ppdpiunclassified

Pengembangan Peta Prakiraan Daerah Penangkapan Ikan

Sukresno¹,

Kusuma²

2021

jfmr

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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.

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Comparison of interpolation methods for sea surface temperature data D

Cited by 15 publications

References 7 publications

Analysis of Terrain Modelling Methods in the Coastal Zone

Analysis of Terrain Modelling Methods in the Coastal Zone

Sistem Informasi Pendugaan Kekerasan Terhadap Perempuan dan Anak Menggunakan Metode Small Area Estimation

Pengembangan Peta Prakiraan Daerah Penangkapan Ikan

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