Case Study of Spatial Planning Mismatch Against Geomorphology in Kampar Regency: Landslide Susceptibility Analysis
DOI:
https://doi.org/10.24036/sjdgge.v10i1.720Keywords:
Landslide Susceptibility Spatial Planning Mismatch Geomorphology Kampar Regency GIS Analysis Disaster MitigationAbstract
This research performs a comprehensive landslide hazard mapping in Kampar Regency by integrating Geographic Information System (GIS) technology with a weighted overlay modeling approach based on four critical physical parameters: slope gradient, rainfall intensity, soil type erodibility, and land use characteristics. Utilizing classification standards from BAPPEDA and weighting methods from Taufik Q, Firdaus et al. (2012) and BNPB Regulation No. 02 of 2012, the study identifies that the region is dominated by rainfall intensities of 2501–3000 mm/year and a significant distribution of Andosol soil types which contribute to soil instability. The spatial analysis results categorize the hazard levels into three classes—Safe, Moderately Prone, and Prone—revealing that XIII Koto Kampar Subdistrict faces the highest risk with a prone area of 88,008.48 hectares (92.36%), primarily due to steep topography and high runoff velocity, whereas Bangkinang Subdistrict is identified as the safest area with a low-risk coverage of 6,836.66 hectares (28.20%). These findings conclude that land use with high vegetation density, such as forests which cover 73,154.26 hectares, plays a vital role in reducing runoff, and the resulting hazard map serves as a crucial spatial decision-support tool for disaster mitigation and regional planning in Kampar Regency.
Downloads
References
[1]BAPPEDA Kabupaten Kampar. (2012). Rencana Tata Ruang Wilayah Kabupaten Kampar Tahun 2012-2032. Bangkinang: Pemerintah Kabupaten Kampar.
[2]BNPB. (2012). Peraturan Kepala Badan Nasional Penanggulangan Bencana Nomor 02 Tahun 2012 tentang Pedoman Umum Pengkajian Risiko Bencana. Jakarta
[3]Lembaga Penelitian Tanah (LPT). (1969). Klasifikasi Jenis Tanah di Indonesia. Bogor: Departemen Pertanian.
[4]Purnamasari, D. C., et al. (2007). Analisis Kerawanan Tanah Longsor Menggunakan Sistem Informasi Geografis. Jurnal Penginderaan Jauh, 4(1), 12-25.
[5]Taufik, Q., Firdaus, & Deniyatno. (2012). Pemodelan Spasial Bahaya Tanah Longsor Menggunakan Teknik Overlay di Wilayah Riau. Jurnal Geografi dan Lingkungan, 8(2), 145-160.
[6]Arsyad, S. (2010). Konservasi Tanah dan Air. Bogor: IPB Press.
[7]Hardiyatmo, H. C. (2012). Tanah Longsor dan Erodisi: Kejadian dan Penanganan. Yogyakarta: Gadjah Mada University Press.
[8]Karnawati, D. (2005). Bencana Alam Tanah Longsor: Penyebab dan Upaya Mitigasi. Yogyakarta: Jurusan Teknik Geologi Universitas Gadjah Mada.
[9]Nugroho, S. P. (2015). Karakteristik Bencana Tanah Longsor di Indonesia. Jakarta: BNPB.
[10]Sartohadi, J., et al. (2012). Pengantar Geografi Tanah. Yogyakarta: Pustaka Pelajar.
[11]Sutikno. (2011). Geomorfologi dan Mitigasi Bencana Tanah Longsor. Yogyakarta: Gadjah Mada University Press.
[12]Wahyunto, & Hikmatullah. (2011). Erodibilitas Tanah dan Faktor-faktor yang Mempengaruhinya. Jurnal Sumberdaya Lahan, 5(1), 33-46.
[13]Yusuf, M., et al. (2018). Aplikasi GIS untuk Pemetaan Wilayah Rawan Longsor di Kabupaten Kampar. Jurnal Fisika dan Aplikasinya, 14(3), 88-95.
[14]Ayala, I., et al. (2016). GIS-based Landslide Susceptibility Mapping using Overlay Methods. Geomorphology Journal, 267, 140-152.
[15]Carrara, A., et al. (1995). GIS Techniques for Landslide Hazard Assessment. Geomorphology, 12(4), 303-344.
[16]Chalkias, C., et al. (2014). Rainfall-induced Landslides: Modelling Susceptibility at Regional Scale. Open Geosciences, 6(2), 258-277.
[17]Dai, F. C., & Lee, C. F. (2002). Landslide Characteristics and Slope Instability Analysis using GIS. Engineering Geology, 64(1), 65-81.
