DETEKSI PERUBAHAN ZONA AGROKLIMAT SCHMIDT-FERGUSON MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS DI KABUPATEN GORONTALO

Viky Vendy Moontuno, Sri Maryati, Syahrizal Koem

Abstract


Abstrak: Penelitian ini menggunakan SIG untuk menganalisis pergeseran zona agroklimat berdasarkan Klasifikasi Schmidt-Ferguson di Kabupaten Gorontalo. Klasifikasi iklim Schmidt-Ferguson diestimasi menggunakan data curah hujan bulanan. Untuk setiap stasiun hujan dari tahun 1981 sampai 2020 dihitung jumlah Bulan Basah (BB), Bulan Kering (BK), dan Bulan Lembab (BL) selama 10, 20, dan 40 tahun. Kabupaten Gorontalo terdeteksi memiliki lima tipe iklim, yaitu: B, C, D, E, dan F. Tipe C mendominasi di stasiun pengamatan selama periode pengamatan 10 dan 20 tahun. Ada kecenderungan luas tipe C menurun sedangkan luas tipe D bertambah, dan iklim kering tipe E dan F berpotensi meningkat. Pemetaan zonasi iklim mempengaruhi sosial ekonomi masyarakat dalam perencanaan pertanian, khususnya pengelolaan lahan dan jenis tanaman. Hasil zonasi iklim yang terdeteksi perlu diverifikasi dengan teknologi penginderaan jauh menggunakan data citra satelit. Hal ini diperlukan karena kelemahan mendasar klasifikasi iklim adalah batas tipe iklim tidak sesuai dengan batas lanskap.

 

Abstract:  This study uses GIS to analyze shifts in agro-climatic zones based on the Schmidt-Ferguson Classification in Gorontalo District. The Schmidt-Ferguson climate classification is estimated using monthly rainfall data. For each rain station from 1981 to 2020, the number of wet months (BB), dry months (BK), and humid months (BL) is calculated for 10, 20, and 40 years. Gorontalo District was detected to have five climate types, namely: B, C, D, E, and F. Type C dominated at observation stations during the 10 and 20-year observation period. There is a tendency for the area of type C to decrease while the area of type D increases, and the dry climate types E and F have the potential to increase. Climate zoning mapping affects the socio-economic community in agricultural planning, especially land management and plant types. The detected climate zoning results need to be verified with remote sensing technology using satellite imagery data. This is necessary because the fundamental weakness of climate classification is that the climate-type boundaries do not match the landscape boundaries.


Keywords


Schmidt-Ferguson Classification; Rainfall; Agroclimate Zone

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DOI: https://doi.org/10.31764/geography.v11i2.15821

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