Anang Dwi Purwanto
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ANALISIS ZONA POTENSI PENANGKAPAN IKAN (ZPPI) BERDASARKAN CITRA SATELIT SUOMI NPP-VIIRS (STUDI KASUS: LAUT ARAFURA) Anang Dwi Purwanto; Dhia Puspa Ramadhani
Jurnal Kelautan Vol 13, No 3: Desember (2020)
Publisher : Department of Marine Sciences, Trunojoyo University of Madura, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/jk.v13i3.8126

Abstract

ABSTRACTInformation on potential fishing zone (PFZ) is needed by fishermen to facilitate fishing operations and increase fish catch. The purpose of this study was to determine the distribution of sea surface temperature and to create maps of potential fishing zones in Arafura Sea (eastern Indonesia). Information on potential fishing zones was obtained base on thermal front events from sea surface temperature (SST). Satellite imagery data used was Suomi NPP-VIIRS image level 3 which recording period of one month SST, from August 1-31, 2018. SST was measured by using the statistical regression method with Non-Linear Multi Channel SST (NLSST) approach. The results showed that the average value of SST distribution in the Arafura Sea was relatively high with range of values of 26.68 - 31.79 °C, and produce around 70 points of potential fishing zones information. Only 12 days out of 31 days can produce the information needed for mapping the ZPPI. The ZPPI data is then divided into three groups based on the density of fish points, they are Zone 1, Zone 2, and Zone 3. Satellite imagery is very helpful in mapping ZPPI information in a water area.Keywords: SNPP-VIIRS, Thermal Front, Potential Fishing Zones, Arafura SeaABSTRAKInformasi mengenai zona potensi penangkapan ikan (ZPPI) sangat di butuhkan nelayan untuk memudahkan dalam operasi penangkapan ikan dan meningkatkan hasil tangkapan ikan. Tujuan penelitian ini adalah untuk mengetahui distribusi suhu permukaan laut dan membuat peta informasi zona potensi penangkapan ikan di Laut Arafura yang terletak di bagian timur Indonesia. Informasi zona potensi penangkapan ikan diperoleh berdasarkan kejadian termal front dari suhu permukaan laut. Data citra satelit yang digunakan adalah citra Suomi NPP-VIIRS level 3 untuk periode perekaman selama 1 (satu) bulan yaitu dari tanggal 1 Agustus 2018 sampai dengan 31 Agustus 2018 yang sudah berupa informasi suhu permukaan laut. Perhitungan suhu permukaan laut tersebut berdasarkan metode regresi statistik dengan pendekatan Non-Linear Multi Channel SST (NLSST). Hasil penelitian menunjukkan rata-rata nilai distribusi suhu permukaan laut di Laut Arafura relatif tinggi dengan kisaran nilai 26.68 0C - 31.79 0C dan informasi zona potensi penangkapan ikan yang dihasilkan sekitar 70 titik. Dari data selama 1 bulan (31 hari) hanya sekitar 12 tanggal yang mampu menghasilkan informasi ZPPI. Data ZPPI tersebut kemudian dibagi menjadi 3 (tiga) kelompok yaitu Zona 1, Zona 2 dan Zona 3 berdasarkan tingkat kerapatan titik ikannya. Penggunaan citra satelit sangat membantu dalam pemetaan informasi ZPPI di suatu wilayah perairan.Kata Kunci: SNPP-VIIRS, Termal Front, Zona Potensi Penangkapan Ikan, Laut Arafura
DETEKSI AWAL HABITAT PERAIRAN LAUT DANGKAL MENGGUNAKAN TEKNIK OPTIMUM INDEX FACTOR PADA CITRA SPOT 7 DAN LANDSAT 8 Anang Dwi Purwanto; Kuncoro Teguh Setiawan
Jurnal Kelautan Vol 12, No 2 (2019)
Publisher : Department of Marine Sciences, Trunojoyo University of Madura, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1490.837 KB) | DOI: 10.21107/jk.v12i2.5400

Abstract

ABSTRACTInformation of the existence of the shallow water habitat  is required especially in environmental conservation and monitoring of activities in coastal areas. The component of the shallow water habitat including coral reefs and seagrass. Interpretation of the shallow water habitat is constrained by the location of ecosystem associated with other objects. The aim of study is to determine the best combination of band composites in identifying the shallow water habitat in Pemuteran Beach, Bali. The study used SPOT 7 imagery (acquisition on April 11, 2018) and Landsat 8  imagery (acquisition on April 14, 2018). The data of the shallow water habitat based on the result of field survey was conducted on 7-13 April 2018 at Pemuteran Beach, Bali.  Image data obtained from Remote Sensing Technology and Data Center of LAPAN. Determination of combination of 3 (three) bands the shallow water habitat using Optimum Index Factor (OIF) method where this method used standard deviation value and correlation coefficient from combination of 3 (three) bands. The results show the composite combinations of band 2 (green), band 3 (red) and band 4 (NIR) have the highest OIF values for SPOT 7 image, while the composite combinations of band 2 (blue), band 4 (red) and band 6 (SWIR 1) have the highest OIF values for Landsat 8 image. Interpretation of distribution of shallow water habitat can be done effectively using RGB 423 composite image (SPOT 7) and RGB 642 composite image (Landsat 8). Keywords: Shallow Water Habitat, OIF, SPOT 7, Landsat 8, PemuteranABSTRAKInformasi keberadaan habitat perairan laut dangkal semakin dibutuhkan terutama dalam kegiatan pelestarian lingkungan dan monitoring di wilayah pesisir. Komponen penyusun ekosistem habitat dasar perairan laut dangkal di antaranya terumbu karang dan lamun. Dalam interpretasi ekosistem habitat dasar perairan laut dangkal terkendala oleh lokasi keberadaan ekosistem yang berasosiasi dengan obyek lainnya. Tujuan penelitian ini adalah menentukan kombinasi komposit kanal terbaik dalam mengidentifikasi obyek habitat dasar perairan laut dangkal di Pantai Pemuteran, Bali. Data citra satelit yang digunakan dalam penelitian ini adalah citra SPOT 7 akuisisi tanggal 11 April 2018  dan citra Landsat 8 akuisisi tanggal 14 April 2018, sedangkan data terkait informasi sebaran habitat dasar perairan laut dangkal diperoleh berdasarkan hasil survei lapangan yang telah dilakukan pada tanggal 7-13 April 2018 di Pantai Pemuteran, Bali. Data citra satelit diperoleh dari Pusat Teknologi dan Data LAPAN. Untuk menentukan kombinasi dari 3 (tiga) kanal terbaik dalam interpretasi habitat dasar perairan laut dangkal digunakan metode Optimum Index Factor (OIF) dimana metode ini menggunakan nilai standar deviasi dan koefisien korelasi dari kombinasi 3 (tiga) kanal citra yang digunakan. Hasil penelitian menunjukkan kombinasi komposit 2 (hijau), 3 (merah) dan 4 (NIR) mempunyai nilai OIF tertinggi untuk citra SPOT 7, sedangkan kombinasi komposit 2 (biru), 4 (merah) dan 6 (SWIR 1) mempunyai nilai OIF tertinggi untuk citra Landsat 8. Interpretasi sebaran habitat dasar perairan laut dangkal dapat dilakukan secara efektif dengan menggunakan citra komposit RGB 423 untuk citra SPOT 7 dan RGB 642 untuk citra Landsat 8.Kata kunci: Habitat Dasar Perairan Dangkal, OIF, SPOT 7, Landsat 8, Pemuteran
IDENTIFICATION OF MANGROVE FORESTS USING MULTISPECTRAL SATELLITE IMAGERIES Anang Dwi Purwanto; Wikanti Asriningrum
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 16, No 1 (2019)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1900.958 KB) | DOI: 10.30536/j.ijreses.2019.v16.a3097

Abstract

The visual identification of mangrove forests is greatly constrained by combinations of RGB composite. This research aims to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using the Optimum Index Factor (OIF) method. The OIF method uses the standard deviation value and correlation coefficient from a combination of three image bands. The image data comprise Landsat 8 imagery acquired on 30 May 2013, Sentinel 2A imagery acquired on 18 March 2018 and images from SPOT 6 acquired on 10 January 2015. The results show that the band composites of 564 (NIR+SWIR+Red) from Landsat 8 and 8a114 (Vegetation Red Edge+SWIR+Red) from Sentinel 2A are the best RGB composites for identifying mangrove forest, in addition to those of 341 (Red+NIR+Blue) from SPOT 6. The near-infrared (NIR) and short-wave infrared (SWIR) bands play an important role in determining mangrove forests. The properties of vegetation are reflected strongly at the NIR wavelength and the SWIR band is very sensitive to evaporation and the identification of wetlands.