Najwa Nabila Amanda Siswoyo, - and Endah Setyowati, - and Hafiyyan Putra Pratama, - (2025) ANALISIS SPASIO-TEMPORAL PERMUKAAN AIR BERDASARKAN CITRA SENTINEL-2A DENGAN PENDEKATAN DEEP LEARNING (STUDI KASUS: KABUPATEN BANDUNG BARAT). S1 thesis, Universitas Pendidikan Indonesia.
Abstract
Permukaan air di Kabupaten Bandung Barat merupakan salah satu elemen penting yang mendukung kebutuhan masyarakat, pertanian, dan ekosistem. Penelitian ini menganalisis variasi spasio-temporal permukaan air dari tahun 2016 hingga 2024 menggunakan data citra satelit Sentinel-2A dengan pendekatan deep learning model WatNet. Analisis dilakukan dengan pendekatan spasio-temporal untuk memantau perubahan distribusi permukaan air, serta menguji keterkaitan antara luas permukaan air dengan variabel-variabel klimatologis seperti curah hujan, suhu, dan kelembapan udara. Hasil penelitian menunjukkan bahwa periode musim hujan (DJF dan MAM) memiliki luas permukaan air yang lebih besar dibandingkan dengan musim kemarau (JJA dan SON). Total luas permukaan air yang teridentifikasi selama periode penelitian adalah 13.601,82 hektare, dengan 98,5% di antaranya merupakan permukaan air musiman. Hasil analisis menunjukkan adanya variasi signifikan dalam luas permukaan air berdasarkan musim, di mana periode musim hujan (DJF dan MAM) memiliki area permukaan air yang lebih besar dibandingkan dengan musim kemarau (JJA dan SON). Uji korelasi menunjukkan hubungan positif antara luas permukaan air dengan kelembapan udara (p-value = 0,0166) dan curah hujan (p-value = 0,006008), sementara suhu tidak menunjukkan hubungan signifikan. Penelitian ini memberikan wawasan penting terhadap perubahan permukaan air dan variabel-variabel yang mempengaruhinya, serta dapat digunakan sebagai dasar bagi pengelolaan sumber daya air di Kabupaten Bandung Barat. ----- Surface water in West Bandung Regency is one of the important elements that support the needs of society, agriculture, and ecosystems. This research analyzes the spatio-temporal variation of water surface from 2016 to 2024 using Sentinel-2A satellite image data with the WatNet deep learning model approach. The analysis was conducted using a spatio-temporal approach to monitor changes in water table distribution, as well as to examine the relationship between water table area and climatological variables such as rainfall, temperature, and air humidity. The results showed that the wet season (DJF and MAM) had a larger surface water area compared to the dry season (JJA and SON). The total surface water area identified during the study period was 13,601.82 hectares, of which 98.5% was seasonal surface water. The analysis showed significant variation in surface water area by season, with the wet season (DJF and MAM) having a larger surface water area compared to the dry season (JJA and SON).Correlation tests showed a positive relationship between water surface area and air humidity (p-value = 0.0166) and rainfall (p-value = 0.006008), while temperature showed no significant relationship. This study provides important insights into water table changes and their influencing variables, and can be used as a basis for water resources management West Bandung Regency.
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| Item Type: | Thesis (S1) |
|---|---|
| Additional Information: | https://scholar.google.com/citations?user=RLHFzHQAAAAJ&hl=en ID SINTA Dosen Pembimbing: Endah Setyowati: 6681149 Hafiyyan Putra Pratama: 6681148 |
| Uncontrolled Keywords: | Spasio-temporal, Permukaan Air, penginderaan jarak jauh, Sentinel-2A, Segmentasi, Deep Learning, WatNet, korelasi, variabel klimatologis, Kabupaten Bandung Barat. Spatio-temporal, surface water, remote sensing, Sentinel-2A, segmentation, Deep Learning, WatNet, correlation, climatological factor, West Bandung Regency |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | UPI Kampus Purwakarta > S1 Sistem Telekomunikasi |
| Depositing User: | Najwa Nabila Amanda Siswoyo |
| Date Deposited: | 16 Jul 2025 07:34 |
| Last Modified: | 16 Jul 2025 07:34 |
| URI: | http://repository.upi.edu/id/eprint/134500 |
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