Setianingrum, Sarah
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Pemanfaatan Citra Satelit Landsat untuk Analisis Kerapatan Vegetasi Menggunakan Metode NDVI di Kota Serang Tahun 2014 dan 2024 Ruuhulhaq, Muhammad Saiful; Setianingrum, Sarah
Jurnal Pendidikan Geografi Undiksha Vol. 12 No. 3 (2024): Jurnal Pendidikan Geografi Undiksha
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jjpg.v12i3.81193

Abstract

Analyzes vegetation density changes in Serang City (2014-2024) using Landsat satellite imagery and the Normalized Difference Vegetation Index (NDVI). The research aims to assess urban vegetation degradation patterns and compliance with Indonesia's 30% green space regulation (UU No. 26/2007). Results show significant vegetation loss, with high-density vegetation (NDVI ≥0.45) decreasing from 7,481 ha (2014) to 4,814 ha (2024), while non-vegetated areas increased from 1,331 ha to 3,642 ha. The NDVI analysis reveals a 35.6% reduction in high-density green areas, primarily due to urban expansion. Methodologically, the study employs radiometrically-corrected Landsat-8 OLI data (bands 4-Red and 5-NIR) processed in a GIS environment, validated through Google Earth. The findings highlight urgent needs for urban green space rehabilitation and stricter land-use policies. This research contributes to sustainable city planning by providing a decade-long vegetation change baseline using remote sensing technology. Future studies should incorporate ground-truth verification and climate variables for comprehensive analysis.
Utilization of Sentinel-2 Imagery for Water Quality Analysis: A Case Study of Saguling Reservoir Ruuhulhaq, Muhammad Saiful; Setianingrum, Sarah
International Journal for Disaster and Development Interface Vol. 5 No. 2 (2025): October 2025
Publisher : Amcolabora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53824/ijddi.v5i2.71

Abstract

Water resources are essential for human life and are one of the main indicators of regional development success. Saguling Reservoir is one of the reservoirs located in West Java that plays a crucial role in various aspects of the lives of the surrounding community. This study aims to determine the distribution of Total Suspended Solids in Saguling Reservoir and to assess turbidity levels using the Normalized Difference Turbidity Index. This study utilizes the Total Suspended Solids (TSS) model by Huizeng Liu using Sentinel-2 imagery data. Based on the research findings, Saguling Reservoir has three classes of Total Suspended Solids (TSS): low (902.91 hectares), moderate (1830.47 hectares), and high (592.78 hectares). Meanwhile, the turbidity levels in Saguling Reservoir are very low (212.84 hectares), moderate (2649.94 hectares), and high (457 hectares).