Anang Dwi Purwanto, Anang Dwi
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TIME SERIES ANALYSIS OF TOTAL SUSPENDED SOLID (TSS) USING LANDSAT DATA IN BERAU COASTAL AREA, INDONESIA Parwati, Ety; Purwanto, Anang Dwi
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 1 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2017.v14.a2676

Abstract

Water quality information is usually used for the first examination of the pollution.  One of the parameters of water quality is Total Suspended Solid (TSS), which describes the amount of matter of particles suspended in the water. TSS information is also used as initial information about waters condition of a region. TSS could be derive from Landsat data with several combinations of spectral channels to evaluate the condition of the observation area for both the waters and the surrounding land. The study aimed to evaluate Berau waters condition in Kalimantan, Indonesia, by utilizing TSS dynamics extracted from Landsat data. Validated TSS extraction algorithm was obtained by choosing the best correlation between  field data and image data. Sixty pairs of points had been used to build validated TSS algorithms for the Berau Coastal area. The algorithm was TSS = 3.3238 * exp (34 099 * Red Band Reflectance). The data used for this study were Landsat 5 TM, Landsat 7 ETM and Landsat 8 data acquisition in 1994, 1996, 1998, 2002, 2004, 2006, 2008 and 2013. For detailed evaluation, 20 regions were created along the watershed up to the coast. The results showed the fluctuation of TSS values in each selected region. TSS value increased if there was a change of any kind of land cover/land used into bareland, ponds, settlements or shrubs. Conversely, TSS value decreased if there was a wide increase of mangrove area or its position was very closed to the ocean.
Pemanfaatan Data Penginderaan Jauh untuk Ekstraksi Habitat Perairan Laut Dangkal di Pantai Pemuteran, Bali, Indonesia Purwanto, Anang Dwi; Setiawan, Kuncoro Teguh; Ginting, Devica Natalia Br.
Jurnal Kelautan Tropis Vol 22, No 2 (2019): JURNAL KELAUTAN TROPIS
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.698 KB) | DOI: 10.14710/jkt.v22i2.5092

Abstract

Indonesia had a large diversity of coastal ecosystems. One part of the them is the coral reef. The concept of mapping coral reef ecosystems has been outlined in the RSNI document about the mapping of shallow marine waters. The aim of this study is to map shallow marine waters using the 1981 and 2006 lyzenga methods. The mapping was made based on three classes including coral reef, mixed seagrass and macroalgae, and substrate. The location of the study was conducted at Pemuteran Beach, Bali. The data used were Landsat 8 imagery acquisition on 14 April 2018. Stages of data processing include atmospheric correction, radiometric correction, pansharpening, masking, cropping, and water column correction and classification. Water column correction used the Lyzenga 1981 and 2006. Classification methods to distinguish objects of shallow marine waters using the unsupervised method. The results showed differences in the results of extraction of shallow marine waters information using the Lyzenga 1981 with the 2006 Lyzenga method. The extraction results with the Lyzenga 2006 method provide more detailed information in identifying the three classes of shallow marine waters. Indonesia memiliki keanekaragaman ekosistem pesisir yang cukup besar. Salah satu bagian dari ekosistem tersebut adalah ekosistem terumbu karang. Konsep pemetaan ekosistem terumbu karang telah dituangkan dalam RSNI tentang pemetaan habitat dasar perairan laut dangkal. Tujuan penelitian ini adalah untuk melakukan pemetaan habitat perairan laut dangkal dengan menggunakan metode lyzenga 1981 dan 2006.  Pemetaan tersebut dibuat berdasarkan tiga kelas diantaranya: kelas terumbu karang, kelas campuran padang lamun dan makro alga, serta kelas substrat dasar. Lokasi penelitian dilaksanakan di Pantai Pemuteran, Bali. Data yang digunakan adalah citra Landsat 8 akuisisi 14 April 2018. Tahapan pengolahan data meliputi, koreksi atmosferik, koreksi radiometrik, proses pansharpening, proses masking darat air, cropping, serta koreksi kolom air serta klasifikasi. Koreksi kolom air menggunakan metode Lyzenga 1981 dan 2006. Klasifikasi untuk membedakan obyek habitat perairan laut dangkal menggunakan metode unsupervised . Hasil penelitian menunjukkan adanya perbedaan hasil ekstraksi informasi habitat perairan laut dangkal menggunakan metode Lyzenga 1981 dengan metode Lyzenga 2006. Hasil ekstraksi dengan metode Lyzenga 2006 memberikan informasi yang lebih detail dalam mengidentifikasi tiga kelas habitat perairan laut dangkal tersebut.
DETEKSI AWAL HABITAT PERAIRAN LAUT DANGKAL MENGGUNAKAN TEKNIK OPTIMUM INDEX FACTOR PADA CITRA SPOT 7 DAN LANDSAT 8 Purwanto, Anang Dwi; Setiawan, Kuncoro Teguh
JURNAL ENGGANO Vol 4, No 2
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (934.567 KB) | DOI: 10.31186/jenggano.4.2.174-192

Abstract

Informasi 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 dimana lokasi keberadaan obyek habitat ini cenderung berdekatan. 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.DETECTION OF SHALLOW WATER HABITATS USING OPTIMUM INDEX FACTORS TECHNIQUE ON SPOT 7 AND LANDSAT 8 IMAGERY. Information 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 where the location of the existence of these relatively close together. 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).
IDENTIFICATION OF MANGROVE FORESTS USING MULTISPECTRAL SATELLITE IMAGERIES Purwanto, Anang Dwi; Asriningrum, Wikanti
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 | 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.