Ground Clutter Filtering Pada Radar Cuaca Manado

Utama, Dhira (2025) Ground Clutter Filtering Pada Radar Cuaca Manado. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Radar cuaca memainkan peran penting dalam memantau dan menganalisis fenomena atmosfer, terutama dalam mitigasi risiko bencana alam dan kegiatan operasional di sektor penerbangan, maritim, dan pertanian. Estimasi curah hujan berbasis radar dipengaruhi oleh beberapa faktor, seperti ground clutter, yang memengaruhi efektivitas pengamatan. Oleh karena itu, penting untuk mengurangi echo non-presipitasi (ground clutter) yang dapat menyebabkan kesalahan dalam interpretasi estimasi curah hujan (Nur Riska Lukita, dkk, 2019). Peningkatan kualitas data radar cuaca dapat dilakukan dengan menggunakan peta clutter pada pemrosesan awal (Muhammad Panji Rosyady, dkk, 2019).
Pada penelitian ini berfokus pada pengembangan dan penerapan teknik pemfilteran ground clutter pada data radar cuaca di Manado, Sulawesi Utara. Penelitian ini bertujuan untuk mengidentifikasi, mengurangi, dan memfilter sinyal ground clutter tanpa mengurangi sensitivitas deteksi fenomena cuaca yang signifikan pada radar tipe Gematronik dengan frekuensi C-Band. Hasil dari penelitian ini diharapkan mampu meningkatkan akurasi informasi cuaca yang diberikan oleh radar cuaca, memfasilitasi peringatan dini yang lebih tepat, serta mengoptimalkan kinerja radar dalam pemantauan kondisi cuaca di wilayah Sulawesi Utara. Teknik pemfilteran yang digunakan dalam penelitian ini adalah pendekatan thresholding untuk membuat peta clutter sehingga meningkatkan kecepatan waktu pengolahan data dan penyampaian informasi pemetaan citra radar cuaca kepada prakirawan dan publik. Untuk meningkatkan kemudahan penyampaian informasi spasial radar cuaca terkoreksi, peta ditampilkan dengan sistem web-GIS. Hasil filtering kemudian digunakan untuk mengestimasi curah hujan. Persamaan linier didapat secara empiris pada kondisi hujan lebat hingga sangat lebat berdasarkan data AWS (pengukuran interval 10 menit). Hasil persamaan diuji pada kondisi hujan lebat di Manado pada tanggal 30 Agustus 2024 dan menghasilkan korelasi 0.859 dan MAE dan RMSE sebesar 0.306 mm/10mnt dan 1.283 mm/10mnt.
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Weather radar plays a crucial role in monitoring and analyzing atmospheric phenomena, particularly in disaster risk mitigation and operational activities in the aviation, maritime, and agricultural sectors. Radar-based rainfall estimation is influenced by several factors, such as ground clutter, which affects the effectiveness of observations. Therefore, it is essential to reduce non-precipitation echoes (ground clutter) that can lead to errors in interpreting rainfall estimates (Nur Riska Lukita et al., 2019). Improving the quality of weather radar data can be achieved by using clutter maps in the initial processing stage (Muhammad Panji Rosyady et al., 2019). This study focuses on the development and implementation of ground clutter filtering techniques on weather radar data in Manado, North Sulawesi. The research aims to identify, reduce, and filter ground clutter signals without compromising the sensitivity of significant weather phenomenon detection on a Gematronik-type radar operating at C-Band frequency. The results of this study are expected to improve the accuracy of weather information provided by the weather radar, facilitate more accurate early warnings, and optimize radar performance in monitoring weather conditions in the North Sulawesi region. The filtering technique used in this study is a thresholding approach to generate a clutter map, thereby improving data processing speed and the delivery of weather radar imagery information to forecasters and the public. To enhance the accessibility of corrected spatial weather radar information, the map is displayed using a web-GIS system. The filtering results are then used to estimate rainfall. A linear equation was empirically derived under heavy to very heavy rain conditions based on AWS data (measured at 10-minute intervals). The equation was tested under heavy rain conditions in Manado on August 30, 2024, and resulted in a correlation of 0.859, with a Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 0.306 mm/10 minutes and 1.283 mm/10 minutes, respectively.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Ground Clutter, Radar Cuaca, web-GIS, Weather Radar
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User:	Dhira Utama
Date Deposited:	14 Jul 2025 08:08
Last Modified:	14 Jul 2025 08:08
URI:	http://repository.its.ac.id/id/eprint/119216

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