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All Journal Geoplanning : Journal of Geomatics and Planning Majalah Geografi Indonesia Jurnal Geografi Jurnal Kelautan Nasional
Pramaditya Wicaksono
Universitas Gadjah Mada
Earth & Planetary Sciences Education Environmental Science Social Sciences Other

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Akurasi geometri garis pantai hasil transformasi indeks air pada berbagai penutup lahan di Kabupaten Jepara Arief Wicaksono; Pramaditya Wicaksono
Majalah Geografi Indonesia Vol 33, No 1 (2019): Majalah Geografi Indonesia
Publisher : Fakultas Geografi, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (759.323 KB) | DOI: 10.22146/mgi.36948

Abstract

Garis pantai merupakan salah satu data dasar dalam pemetaan yang harus dijamin ketersediaannya. Pesisir di Indonesia memiliki variasi penutup lahan sehingga karakteristik indeks air dalam memperoleh data garis pantai perlu diketahui agar pemanfaatan indeks air menjadi efektif. Tujuan penelitian ini adalah menghitung akurasi geometri garis pantai menggunakan transformasi NDWI, MNDWI, dan AWEI pada penutup lahan berbeda. Garis pantai hasil indeks air diperoleh dari citra Landsat 8 OLI, sedangkan garis pantai referensi untuk uji akurasi diperoleh dari interpretasi visual citra PlanetScope. Standar penilaian ketelitian horizontal garis pantai hasil indeks air menggunakan Perka BIG No 15 Tahun 2014. Hasil penelitian adalah pada nilai akurasi geometri garis pantai skala 1:100.000, tidak ada satu pun indeks air yang mampu mengakomodasi perolehan garis pantai pada semua kelas penutup lahan. Variasi nilai akurasi geometri setiap indeks air disebabkan oleh variasi kondisi citra, karakteristik saluran yang digunakan dalam formula indeks air, dan piksel campuran.
ACCURACY ASSESSMENTS OF PAN-SHARPENED IMAGE FOR BENTHIC HABITATS MAPPING Pramaditya Wicaksono; Faza Adhimah
Geoplanning: Journal of Geomatics and Planning Vol 4, No 1 (2017)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.4.1.27-40

Abstract

Image-sharpening process integrates lower spatial resolution multispectral bands with higher spatial resolution panchromatic band to produce multispectral bands with finer spatial detail called pan-sharpened image. Although the pan-sharpened image can greatly assist the process of information extraction using visual interpretation, the benefit and setback of using pan-sharpened image on the accuracy of digital classification for mapping remain unclear. This research aimed at 1) highlighting the issue of using pan-sharpened image to perform benthic habitats mapping and 2) comparing the accuracy of benthic habitats mapping using original and pan-sharpened bands. In this study, Quickbird image was used and Kemujan Island was selected as the study area. Two levels of hierarchical classification scheme of benthic habitats were constructed based on the composition of in situ benthic habitats. PC Spectral sharpening method was applied on Quickbird image. Image radiometric corrections, PCA transformation, and image classifications were performed on both original and pan-sharpened image. The results showed that the accuracy of benthic habitats classification of pan-sharpened image (maximum overall accuracy 64.28% and 73.30% for per-pixel and OBIA, respectively) was lower than the original image (73.46% and 73.10%, respectively). The main setback of using pan-sharpened image is the inability to correct the sunglint, hence adversely affects the process of water column correction, PCA transformation and image classification. This is mainly because sunglint do not only affect object’s spectral response but also the texture of the object. Nevertheless, the pan-sharpened image can still be used to map benthic habitats using visual interpretation and digital image processing. Pan-sharpened image will deliver better classification accuracy and visual appearance especially when the sunglint is low.
Geometric Accuracy Assessment for Shoreline Derived from NDWI, MNDWI, and AWEI Transformation on Various Coastal Physical Typology in Jepara Regency using Landsat 8 OLI Imagery in 2018 Arief Wicaksono; Pramaditya Wicaksono
Geoplanning: Journal of Geomatics and Planning Vol 6, No 1 (2019)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1996.46 KB) | DOI: 10.14710/geoplanning.6.1.55-72

Abstract

Landsat 8 OLI imagery and water index utilization is expected to be able to complete the shoreline data that is difficult to obtain by using terrestrial and hydrographic surveys. In fact, coastal areas in Indonesia have a variety of coastal physical typology so that each water index characteristic in obtaining shoreline data needs to be understood in order to use water index method effectively. The objectives of this study are to map the shoreline using NDWI, MNDWI, and AWEI transformations and assess the shoreline geometric accuracy on various coastal physical typology. The shoreline derived from water index is obtained from Landsat 8 OLI imagery, while the reference shoreline for accuracy assessment is obtained from visual interpretation on Planet Scope imagery. Threshold 0 and subjective threshold based on per coastal physical typology sample experiments are used to separate land-sea. The horizontal accuracy standard of the shoreline derived from water index uses the regulation from Geospatial Information Agency of Indonesia No.15 in 2014 on technical guidelines for basic map accuracy. The results consisted of 1:100,000 scale shoreline map and shoreline geometric accuracy per coastal physical typology. Based on the shoreline geometry accuracy assessment, NDWI has the lowest shoreline geometry accuracy on artificial coast (RMSE=24.13 m). MNDWI has the lowest shoreline geometry accuracy on land deposition coast (RMSE=15.84 m), marine deposition coast (RMSE=29.53 m), and volcanic coast (RMSE=10 m). AWEIsh has the lowest shoreline geometry accuracy on the organic coast (RMSE=13.47 m), while AWEI does not superior to any coastal physical typology.
Identifikasi Tumpahan Minyak di Laut Akibat Tank Cleaning Menggunakan Metode Tidak Terselia Rizky Faristyawan; Pramaditya Wicaksono; Sanjiwana Arjasakusuma; Restu Wardani
Jurnal Kelautan Nasional Vol 18, No 1 (2023): APRIL
Publisher : Pusat Riset Kelautan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/jkn.v18i1.12404

Abstract

Tumpahan minyak di laut dapat terdeteksi oleh citra satelit dengan sensor Synthetic Aperture Eadar (SAR) dan memungkinkan untuk diidentifikasi menggunakan berbagai macam metode baik terselia maupun tidak terselia. Salah satu metode terselia yang biasa digunakan adalah digitasi visual, namun metode ini sangat subjektif pada kapasitas interpreter. Untuk meminimalisasi subjektifitas interpreter maka metode tidak terselia perlu dikaji lebih lanjut. Tujuan dari penelitian ini adalah mengkaji algoritma tidak terselia untuk identifikasi tumpahan minyak yang diakibatkan oleh tank cleaning. Citra satelit yang digunakan dalam penelitian ini adalah citra Sentinel-1 di wilayah perairan utara Pulau Bintan. Proses identifikasi dilakukan menggunakan metode tidak terselia, dan penelitian ini membandingkan dua algoritma dalam proses identifikasi, yaitu K-Means dan CLARA. Dapat disimpulkan bahwa dalam melakukan identifikasi perlu diketahui terlebih dahulu kondisi perairan terutama kecepatan angin dan arus laut sebelum memasuki tahap komputasi. Hasil identifikasi menggunakan kedua algoritma ini dibandingkan dengan data referensi dari LAPAN sebagai instansi yang melakukan diseminasi terkait tumpahan minyak di laut. Jika dibandingkan dengan data referensi tersebut, algoritma K-Means memiliki persentase hasil yang lebih baik dalam mendeteksi luasan tumpahan minyak, namun algoritma CLARA mampu memberikan hasil identifikasi dengan look-alike tumpahan minyak yang lebih sedikit sehingga kesalahan identifikasi menjadi minimal.
Random Forests Algorithm for Two Levels of Coral Reef Ecosystem Mapping Using Planetscope Image in Malalayang Beach, Manado Fela Pritian Cera; Projo Danoedoro; Pramaditya Wicaksono; Moh Yasir
JURNAL GEOGRAFI Vol 15, No 2 (2023): JURNAL GEOGRAFI
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jg.v15i2.30795

Abstract

The coral reef ecosystem has a significant physical and biological function and is also one of the coastal ecosystem components apart from the seagrass and mangrove ecosystem. Besides their ecological function, the coral reef also has an economic function. The condition of the coral reef ecosystem in Malalayang Beach has been changing for years. The utilization of remote sensing images can monitor current conditions. This research aims to map the coral reef ecosystem mapping in Malalayang Beach, Manado and conduct a test for the accuracy of coral reef ecosystem mapping using field survey data as a classification and validation sample. PlanetScope multispectral image has four channels to detect underwater objects: red, green, blue and near infrared. PlanetScope level 3B image for the research has a surface reflectance value for its pixel. The image processing stages of this research consist of sunglint correction, water column correction, and then continue to classify the coral reef ecosystem using random forests algorithm. Classification and accuracy training sample data were obtained using the photo transect technique. The sunglint correction regression equation is between 0.27 – 0.38. The coefficient of attenuation ratio in B1 is 0.927797938, B2 is 0.168841585, and B3 is 0.29033029. This value then becomes the input for the Lyzenga formula. The classification accuracy for level one using random forests is 72,54%, and the accuracy for level two mapping is 37,61%.Keywords: Coral Reef Ecosystem, Planetscope, Random Forests
Co-Authors Arief Wicaksono Faza Adhimah Fela Pritian Cera Moh Yasir Projo Danoedoro Restu Wardani Rizky Faristyawan Sanjiwana Arjasakusuma