DOI: https://doi.org/10.14710/jil.23.3.820-829

Estimasi Populasi Terpapar pada Kejadian Banjir di Kecamatan Biringkanaya Kota Makassar

1Program Studi Ilmu Perencanaan Wilayah, Sekolah Pascasarjana, IPB University, Jl. Raya Dramaga, Kampus IPB Dramaga Bogor, 16680 Jawa Barat, Indonesia, Indonesia

2Departemen Ilmu Tanah dan Sumberdaya Lahan, Fakultas Pertanian, IPB University, Jl. Raya Dramaga, Kampus IPB Dramaga Bogor, 16680 Jawa Barat, Indonesia, Indonesia

Received: 26 Jul 2024; Revised: 10 Mar 2025; Accepted: 29 Apr 2025; Available online: 25 May 2025; Published: 31 May 2025.
Editor(s): Budi Warsito

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Abstract

Banjir merupakan ancaman serius bagi kawasan perkotaan, termasuk Kecamatan Biringkanaya, Kota Makassar, yang sering mengalami kejadian banjir dengan tingkat keparahan yang tinggi. Penelitian ini bertujuan untuk mengestimasi populasi yang terpapar banjir di Kecamatan Biringkanaya menggunakan pendekatan dasimetrik dengan integrasi data open source bersumber dari citra Sentinel-1 SAR dan data bangunan dari OpenStreetMap (OSM). Ekstraksi genangan banjir dilakukan dengan mengaplikasikan teknik change detection pada citra pra-banjir dan citra saat banjir terjadi pada Desember 2023, yang dianalisis pada platform Google Earth Engine (GEE). Hasil analisis menunjukkan luas area yang tergenang mencapai 160,60 ha, dengan Kelurahan Sudiang Raya sebagai wilayah dengan genangan terluas. Pengujian overall accuracy terhadap hasil klasifikasi kawasan tergenang menunjukkan tingkat akurasi sebesar 85,71%. Data bangunan dari OSM digunakan untuk memetakan distribusi populasi berdasarkan kepadatan bangunan di Kecamatan Biringkanaya. Distribusi populasi kemudian disinkronkan dengan data genangan banjir untuk mengestimasi jumlah penduduk yang terpapar. Hasil penelitian menunjukkan bahwa sebanyak 915 jiwa terpapar banjir di Kecamatan Biringkanaya. Sementara itu, terjadi anomali di Kelurahan Berua, di mana luas genangan banjir di wilayah ini lebih kecil dibandingkan wilayah lain, namun jumlah penduduk terdampak justru paling tinggi. Adanya underestimate dalam penelitian ini disebabkan oleh keterbatasan citra dalam menangkap nilai backscatter air pada kawasan dengan kepadatan bangunan tinggi, sebagaimana tercermin dari tingkat akurasi yang diperoleh. Penelitian ini memberi kontribusi penting dalam memahami risiko banjir perkotaan dan perencanaan mitigasi di wilayah yang rentan. Hasil penelitian ini dapat digunakan untuk memandu perumusan kebijakan publik dalam pengembangan infrastruktur drainase dan perlindungan banjir, serta mempersiapkan respon darurat yang lebih efektif guna melindungi populasi yang memiliki risiko terpapar banjir.

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Keywords: Banjir; Dasimetrik; Hujan; Populasi; Sentinel-1 SAR; OpenStreetMap

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