Pemanfaatan Algoritma NDVI dan SAVI untuk Identifikasi Perubahan Kerapatan Vegetasi di Kabupaten Toraja Utara Menggunakan Citra Landsat 8 Tahun 2019 dan 2023

This research is motivated by the rapid growth and development of infrastructure and tourism in North Toraja Regency. This has an impact on the closure of green land or vegetation areas and a decrease in environmental quality. Vegetation is a collection of several types of plants that grow together in one place to form a unity where individuals depend on each other. Vegetation has a major influence on all aspects of life, one of which is changes in forest land cover. If the vegetation has a low level of density, it will cause a reduction in forest litter, because there is no longer any part of forest vegetation on the land. Based on this information, it is necessary to conduct research on the level of vegetation density in North Toraja as a reference to see the condition of vegetation density and changes in vegetation density. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) algorithms are applied to Landsat 8 imagery. Then the data is processed using GIS software. Based on the NDVI algorithm, the vegetation density that decreased in the high-medium class was 11,484.32 Ha; high-low 2,718.90 Ha; medium-low 7,107.67 Ha; and there was an increase in the low-medium class of 4,741.15 Ha; low-high 1,090.48 Ha; and medium-high 16,540.27 Ha. Meanwhile, based on the SAVI algorithm, vegetation density decreased in the high-medium class 11,484.31 Ha; high-low 3,791.33 Ha; medium-low 1,121.40 Ha; and there was an increase in the low-medium class 1,428.21 Ha; low-high 2,055.49; and medium-high 2,762.21 Ha.

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Journal
Journal of Geomatics Engineering, Technology, and Sciences
Published
2024-09-30
DOI
https://doi.org/10.51967/gets.v3i1.44
Citations
1
Primary Topic
Data Mining and Machine Learning Applications
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article
Field-Weighted Citation Impact
0.78
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article

Pemanfaatan Algoritma NDVI dan SAVI untuk Identifikasi Perubahan Kerapatan Vegetasi di Kabupaten Toraja Utara Menggunakan Citra Landsat 8 Tahun 2019 dan 2023

Dyah Widyasasi, Nia Kurniadin, Andi Baso Sofyan A. P., Austro Yoris Padatuan
1 citations
Journal of Geomatics Engineering, Technology, and Sciences
Data Mining and Machine Learning Applications
0.78
article

Pemanfaatan Algoritma NDVI dan SAVI untuk Identifikasi Perubahan Kerapatan Vegetasi di Kabupaten Toraja Utara Menggunakan Citra Landsat 8 Tahun 2019 dan 2023

Dyah Widyasasi, Nia Kurniadin, Andi Baso Sofyan A. P., Austro Yoris Padatuan
article en
1 citations

Abstract

This research is motivated by the rapid growth and development of infrastructure and tourism in North Toraja Regency. This has an impact on the closure of green land or vegetation areas and a decrease in environmental quality. Vegetation is a collection of several types of plants that grow together in one place to form a unity where individuals depend on each other. Vegetation has a major influence on all aspects of life, one of which is changes in forest land cover. If the vegetation has a low level of density, it will cause a reduction in forest litter, because there is no longer any part of forest vegetation on the land. Based on this information, it is necessary to conduct research on the level of vegetation density in North Toraja as a reference to see the condition of vegetation density and changes in vegetation density. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) algorithms are applied to Landsat 8 imagery. Then the data is processed using GIS software. Based on the NDVI algorithm, the vegetation density that decreased in the high-medium class was 11,484.32 Ha; high-low 2,718.90 Ha; medium-low 7,107.67 Ha; and there was an increase in the low-medium class of 4,741.15 Ha; low-high 1,090.48 Ha; and medium-high 16,540.27 Ha. Meanwhile, based on the SAVI algorithm, vegetation density decreased in the high-medium class 11,484.31 Ha; high-low 3,791.33 Ha; medium-low 1,121.40 Ha; and there was an increase in the low-medium class 1,428.21 Ha; low-high 2,055.49; and medium-high 2,762.21 Ha.

Journal of Geomatics Engineering, Technology, and SciencesVol. 3(1)
Universitas 17 Agustus 1945 Samarinda (ID)
Openalex Percentile: Top 16%
Data Mining and Machine Learning Applications
0.78
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Pemanfaatan Algoritma NDVI dan SAVI untuk Identifikasi Perubahan Kerapatan Vegetasi di Kabupaten Toraja Utara Menggunakan Citra Landsat 8 Tahun 2019 dan 2023 — Dyah Widyasasi, Nia Kurniadin, et al. · Journal of Geomatics Engineering, Technology, and Sciences (2024) | TGRS Research Map | TGRS