Klasifikasi Tutupan Lahan Multitemporal Menggunakan Metode Random Forest di Kota Bekasi

  • Fadhlul Razak Perencanaan Wilayah dan Kota, Fakultas Teknik, Universitas Islam Bandung
  • Irland Fardani Perencanaan Wilayah dan Kota, Fakultas Teknik, Universitas Islam Bandung
Keywords: Random Forest, Tutupan Lahan, Local Climate Zone

Abstract

Abstract. Bekasi City has experienced a very significant increase of built-up land expansion with the significant decrease proportion of the area of vegetation at once. This is due to its strategic location and directly adjacent to the capital, making Bekasi City a center of population settlement in Jabodetabek area. Remote sensing and Google Earth Engine software are used for the approach of this study. The aims of this study are to identify land cover expansion change in Bekasi City on 1988 - 2022. The data that used in this study consist of Landsat 5, Landsat 8, and Landsat 9 imagery. To identifying land cover, the random forest classification method was used, as well as the NDVI and NDBI methods to classify the level of vegetation density and built-up land density so the final result of land cover classification approaches the system of Local Climate Zone (LCZ) classification. The results showed that types of land cover that had a significant increase include high density built up land, medium & low density built up land. Whereas High density vegetation and shrubs had significant decrease in the last 34 years.

Abstrak. Kota Bekasi mengalami peningkatan perluasan lahan terbangun yang sangat signifikan yang selaras dengan penurunan proporsi luasan vegetasi yang signifikan. Hal ini disebabkan letaknya yang strategis karena berbatasan langsung dengan ibukota menjadikan Kota Bekasi sebagai pusat pemukiman penduduk pada area Jabodetabek. Penginderaan jauh dan perangkat lunak Google Earth Engine digunakan untuk pendekatan penelitian ini. Penelitian ini bertujuan untuk mengidentifikasi perubahan perluasan tutupan lahan di Kota Bekasi tahun 1988 - 2022. Data yang digunakan dalam penelitian ini terdiri dari citra Landsat 5, Landsat 8, dan Landsat 9. Untuk mengidentifikasi tutupan lahan digunakan metode klasifikasi hutan secara acak, serta metode NDVI dan NDBI untuk mengklasifikasikan tingkat kerapatan vegetasi dan kerapatan lahan terbangun sehingga hasil akhir klasifikasi tutupan lahan mendekati sistem klasifikasi Local Climate Zone (LCZ). Hasil penelitian menunjukkan bahwa jenis tutupan lahan yang mengalami peningkatan signifikan meliputi lahan terbangun dengan kepadatan tinggi, lahan terbangun dengan kepadatan sedang & rendah. Sedangkan vegetasi kerapatan tinggi dan semak belukar mengalami penurunan yang signifikan dalam 34 tahun terakhir.

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Published
2023-08-05