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      • UT - Faculty of Forestry and Environment
      • UT - Forest Management
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      Identifikasi Perubahan Tutupan Lahan Menggunakan Citra Sentinel-2 dengan Metode Change Vector Analysis (CVA)

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      Date
      2023-08-24
      Author
      Pambudi, Galih Jati Setya
      Saleh, Muhammad Buce
      Santi, Nitya Ade
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      Abstract
      Tutupan lahan diartikan sebagai kenampakan komponen biofisik permukaan bumi serta dideskripsikan menjadi tingkatan kelas yang menunjukan kumpulan biotik maupun abiotik dominan pada suatu wilayah. Perubahan tutupan lahan terjadi seiring dengan perkembangan zaman. Change Vector Analysis (CVA) merupakan metode yang menggunakan Normalized Difference Vegetation Index (NDVI) dan Normalized Difference Bare Land Index (NDBI) yang merupakan pengembangan dari metode image differencing. Penginderaan jauh pada penelitian ini menggunakan citra Sentinel-2 untuk foto perekaman wilayah Kabupaten-Kota Bogor. Tujuan penelitian ini untuk menganalisis perubahan tutupan lahan di Kabupaten-Kota Bogor tahun 2017 sampai 2022, mengidentifikasi besaran dan arah perubahan, dan menentukan nilai ambang batas setiap kelas perubahan. Metode CVA dapat mendeteksi besar dan arah perubahan dengan nilai magnitude dibawah 0,193 adalah no changes. Dengan periode waktu pengamatan yang hanya 5 tahun, perubahan ke arah vegetasi tidak terlalu signifikan.
       
      Land cover is defined as the appearance of the biophysical components on the earth's surface and is described into class levels that indicate the dominant biotic and abiotic groups in an area. Land cover changes occur over time. Change Vector Analysis (CVA) is a method that uses Normalized Difference Vegetation Index (NDVI) and Normalized Difference Bare Land Index (NDBI) in detecting dynamic changes in multi-time images which are the development of the image differencing method. Remote sensing in this study used Sentinel-2 imagery for photos of the Bogor Regency and City area. The purpose of this study was to analyze land cover change in Bogor Regency-City from 2017 to 2022, identify the magnitude and direction of change, and determine the threshold value for each class of change. The CVA method can detect the magnitude and direction of changes with a magnitude value below 0,193 is no changes. With an observation period of only 5 years, the change towards vegetation is not too significant.
       
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      http://repository.ipb.ac.id/handle/123456789/124302
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      • UT - Forest Management [3203]

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      Copyright © 2020 Library of IPB University
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      Indonesia DSpace Group 
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