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Ketut Wikantika

Centre for Remote Sensing, Bandung Institute of Technology (ITB) and Faculty of Earth Sciences and Technology, Bandung Institute of Technology (ITB)

Author-ID : 417867

Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mathematics Physics Social Sciences

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Green Open Space and Barren Land Mapping for Flood Mitigation in Jakarta, the Capital of Indonesia Retno Dammayatri; Tri Muji Susantoro; Ketut Wikantika
Indonesian Journal of Geography Vol 55, No 2 (2023): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.76452

High levels of rainfall, tidal flooding, land subsidence, intensified urban development, scarce barren land and a shortage of green open spaces (GOS) are contributing factors to the persistent flooding in Jakarta. Therefore, this study was conducted to map the GOS, built-up, and barren land in the city in order to calculate the biopore infiltration hole (LRB) potential for water infiltration as part of Jakarta's flood mitigation efforts using the Landsat 8 operational land imager (OLI). The Landsat data acquired on September 11, 2019, with path/row 122/064 were processed using the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) method for the radiometric correction, and geometric correction with a root mean square error (RMSE) of 7.57 meters. Moreover, the normalized difference vegetation index (NDVI) was applied to classify the GOS, the normalized difference built-up index (NDBI) for the built-up areas, and the normalized difference barren land index (NDBaI) for barren land areas which were further confirmed using NDBI to distinguish them from the built-up areas. It is also important to note that the LRB potential was calculated by adding the GOS and barren land, dividing the result by the ideal land area multiplied by the ideal number of holes. The results showed that the GOS, built-up area, and barren land were 8.34%, 85.29%, and 2.48%, respectively. Furthermore, the LRB potential through the optimization of GOS and barren land was found to be 70.06 km2 and produced 16,816,248 LRB (18.27% of total needed). The realization of this value is expected to reduce the potential inundation in Jakarta by 15.6%.

ANALYZING SURFACE ROUGHNESS MODELS DERIVED BY SAR AND DEM DATA AT GEOTHERMAL FIELDS Tahjudil Witra; Asep Saepuloh; Agung Budi Harto; Ketut Wikantika
Bulletin of Geology Vol 1 No 2 (2017): Bulletin of Geology
Publisher : Fakultas Ilmu dan Teknologi Kebumian (FITB), Institut Teknologi Bandung (ITB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/bull.geol.2017.1.2.1

Surface roughness is a physical property which is used in many applications such as hydrological analyses, erosivity of rocks, and identification of geothermal surface manifestations. In this study, the surface roughness was calculated by a pin-meter. This tool is expected be able to measure the fragmental size at ground surface. However, there is a possibility that the tool still has some errors from the effect of topography undulation. In previous research, detrending method was used to minimise the topographical effect in the measured surface roughness. In this paper, we used Synthetic Aperture Radar (SAR) data from Sentinel-1A, and Digital Elevation Model (DEM) SRTM to evaluate the effectiveness of detrending method of pin-meter. Therefore, the measured surface roughness originated solely from fragmental materials. The selected research areas were Wayang Windu and Patuha geothermal field in Indonesia. Modelling the surface roughness by Sentinel-1A image was conducted by utilising backscattering coefficient and local incidence angle. While surface roughness model from DEM is formed by the Root mean square (RMS) for each grid with the optimum size 19×19 pixels. Both models were compared to pin-meter data which have been detrended. Then, the comparison was analyzed based on determination correlation value (R2). Surface roughness model derived by Sentinel-1A produced R2 about 0.1130 higher than DEM about 0.060. It might indicate that the surface roughness measured by the pin-meter following detrending process is free from the effect of topography undulation. Then, surface roughness model derived by Sentinel-1A data was used to identify surface manifestation. Analysis was performed based on pH measurement at field and scatter plot pattern. According to the selected model, the surface roughness at geothermal surface manifestation zones are inversely proportional to the soil pH.

ANALISIS TRANSFORMASI INDEKS NDVI, NDWI DAN SAVI UNTUK IDENTIFIKASI KERAPATAN VEGETASI MANGROVE MENGGUNAKAN CITRA SENTINEL DI PESISIR TIMUR PROVINSI LAMPUNG Simarmata, Nirmawana; Wikantika, Ketut; Tarigan, Trika Agnestasia; Aldyansyah, Muhammad; Tohir, Rizki Kurnia; Fauziah, Afi; Purnama, Yustika
JURNAL GEOGRAFI Geografi dan Pengajarannya Vol 19 No 2 (2021): JURNAL GEOGRAFI Geografi dan Pengajarannya
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jggp.v19n2.p69-79

Abstrak: Perolehan informasi keberadaan hutan mangrove yang memiliki potensi, peran dan fungsi besar dalam kehidupan, dapat diperoleh melalui data penginderaan jauh. Teknologi penginderaan jauh memiliki efisien tinggi dan banyak kelebihan untuk keperluan monitoring hutan mangrove. Penelitian ini bertujuan untuk mengidentifikasi kerapatan ekosistem mangrove dengan menggunakan transformasi indeks vegetasi serta menguji efektivitas beberapa indeks vegetasi dalam hal ini NDVI, NDWI dan SAVI untuk identifikasi jenis dan kerapatan mengrove. Berdasarkan hasil analisis citra Sentinel dengan menggunakan transformasi indeks NDVI, SAVI, dan NDWI untuk identifikasi kerapatan vegetasi pada transformasi NDVI didominasi kelas kerapatan tinggi yaitu pada rentang nilai 0,67 – 1 yaitu seluas 46975,96 Ha, pada transformasi SAVI didominasi kelas kerapatan sangat jarang yaitu pada rentang nilai 0,99 – 1,38 yaitu seluas 48775,18 Ha, pada transformasi NDWI didominasi kelas kerapatan rendah yaitu pada rentang nilai 0,1 – 0,17 yaitu seluas 27442,26 Ha. Hasil uji akurasi yang dilakukan menggunakan 30 sampel uji diperoleh akurasi sebesar 83,33%. Kata kunci: mangrove, Sentinel, NDVI, NDWI, SAVI

IDENTIFIKASI POTENSI REMBESAN MIKRO DI LAPANGAN MIGAS MELALUI DETEKSI MINERAL LEMPUNG MENGGUNAKAN CITRA LANDSAT 8 OLI/TIRS, STUDI KASUS LAPANGAN MIGAS CEKUNGAN JAWA BARAT BAGIAN UTARA Susantoro, Tri Muji; Wikantika, Ketut; Saepuloh, Asep; Harsolumakso, Agus Handoyo
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 1 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2018.v15.a2779

Clay minerals in the oil and gas field have changed with an increase of the quantities in the middle of the oil and gas field and reduction in the edges. This reduction is the effect of micro seepage from oil and gas from the subsurface. The aims of the research is to identify the potential oil and gas seepage through clay mineral mapping. The data used where Landsat 8 OLI/TIRS with recording dated September 25, 2015. The method used in the mapping of clay minerals using the ratio of 1.55-1.75 µm (Short Wave Infrared 1) and 2.08-2.35 µm (Short Wave Infrared 2). The result of Landsat 8 OLI/TIRS data processing shows the potential of anomalies in edges of the oil and gas field. The anomaly is a change in the index value of clay minerals that tend to be lower with values 1.0 to 1.5 than the middle of oil and gas field with values 1.5 to 2.0. The potential pattern of the anomaly follows the border of the oil and gas field. Field surveys show that oil and gas field based on grain size analysis is dominated by clay-sized soil. The dominant clay minerals from X-Ray Diffraction analysis are smectite (56%) and kaolinite (6%).

Co-Authors Abd. Rasyid Syamsuri Adhi Wibowo Adriana Hiariej, Adriana Agung B. Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agus Handoyo Harsolumakso Agus Handoyo Harsolumakso, Agus Handoyo Agus Sutanto Agus Sutanto Ahmad Luthfi Hadiyanto Akihiko Kondoh Aldyansyah, Muhammad Aminah Kastuari Anesta, Aqilla Fitdhea Anggun Tridawati Aqilla Fitdhea Anesta Armi Susandi Armi Susandi Ary Setijadi Prihatmanto Asep Saepuloh Asep Saepuloh Asep Yusup Saptari Asep Yusup Saptari, Asep Yusup Asmi M. Napitu Asmi M. Napitu Aswin Rahadian Bambang Widarsono Bobby S. Dipokusumo Dandy A. Novresiandi Darmawan S Darmawan S, Darmawan Dedi Irawadi Deni Suwardi Desti Ayunda Dudung M Hakim Dudung Muhally Hakim Dudung Muhally Hakim Fahmi, Muhammad Nurul Farah Nafisa Ariadji Fauziah, Afi Fenny M. Dwivany FENNY MARTHA DWIVANY Ghazali, Mochamad Firman Ghozali, M. Firman Giasintha Stefani Hary Nugroho Herru Lastiadi Setiawan Himasari Hanan Husna Nugrahapraja I Nyoman Dibia I NYOMAN RAI I Wayan Nuarsa Imam A. Sadisun Intan Fatmawati Irland Fardani Ishak H. Ismullah Jaya, La Ode Muhammad Golok Jevon A. Telaumbanua Karlia Meitha Katmoko Ari Sambodo Katmoko Ari Sambodo, Katmoko Ari Laode Muhammad Golok Jaya LILIK BUDIPRASETYO Lissa F. Yayusman Luky Adrianto Lumbantobing, Marlonroi Mamad Sugandi Marlonroi Lumbantobing Mila Olivia Trianaputri Mirelva, Prima Rizky Mochamad Firman Ghazali Mochamad Firman Ghazali Nengah Widiadnyana Nengah Widiadnyana Nisrina Sukriandi Nurjanna Joko Trilaksono Prihanggo, Maundri Prila Ayu Dwi Prastiwi Purnama, Yustika Retno Dammayatri Rian Nurtyawan Riantini Virtriana S. Suliantara Satria Bijaksana Shafarina Wahyu Trisyanti Sigit Nur Pratama Simarmata, nirmawana Soni Darmawan Sony Darmawan, Sony Sugandi, Mamad Sukristiyanti Sukristiyanti Supriadi A Supriadi A, Supriadi Susantoro, Tri Muji Suwardhi, Deni Tahjudil Witra Tan, Alex Tohir, Rizki Kurnia Tombayu A. Hidayat Topik Hidayat Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro, Tri Muji Trianaputri, Mila Olivia Tridawati, Anggun Trika Agnestasia Tarigan Yayusman, Lissa Fajri Yudi Setiawan

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