Investigating the Land Cover Characteristics of the Kesongo Mud Volcano Complex, Java Island, Indonesia: Surface Analysis and Visual Interpretation through Harmonized Sentinel-2A MSI Imagery

Abstract The Kesongo Mud Volcano Complex on Java Island, Indonesia, is a distinctive geological feature that necessitates further study of its land cover to understand potential successions. This research examines the land cover characteristics using satellite imagery to investigate surface and visual features. Employing Harmonized Sentinel-2A MSI imagery analysis, coupled with field observations, we uncovered the complexity of the land cover, including variations in vegetation and substrate characteristics. Remote sensing techniques identified the mud volcano land-cover traits based on the normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI), both of which exhibited a linear regression trend with a coefficient of determination (R²) of 0.6184. The findings reveal contrasting patterns between the central, inner, and outer rim regions, distinguishable by specific band combinations, notably [B8, B4, B3] and [B11, B8, B12]. Furthermore, moisture and vegetation around the mud volcano indicate characteristics of recently active mudflow areas, particularly where Typhaceae, Cyperaceae, Poaceae, and Euphorbiaceae are present. This study enhances our understanding of the dynamic land cover of this mud volcano complex and provides insights into its geological and ecological features, offering valuable perspectives for geoconservation.

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Publication Details

Journal
IOP Conference Series Earth and Environmental Science
Published
2025-02-01
DOI
https://doi.org/10.1088/1755-1315/1451/1/012040
Citations
1
Primary Topic
Geological and Geophysical Studies
Type
article
Field-Weighted Citation Impact
1.17
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article

Investigating the Land Cover Characteristics of the Kesongo Mud Volcano Complex, Java Island, Indonesia: Surface Analysis and Visual Interpretation through Harmonized Sentinel-2A MSI Imagery

Eri Sarmantua Sitinjak, Danni Gathot Harbowo
1 citations
IOP Conference Series Earth and Environmental Science
Geological and Geophysical Studies
1.17
article

Investigating the Land Cover Characteristics of the Kesongo Mud Volcano Complex, Java Island, Indonesia: Surface Analysis and Visual Interpretation through Harmonized Sentinel-2A MSI Imagery

Eri Sarmantua Sitinjak, Danni Gathot Harbowo
article en
1 citations

Abstract

Abstract The Kesongo Mud Volcano Complex on Java Island, Indonesia, is a distinctive geological feature that necessitates further study of its land cover to understand potential successions. This research examines the land cover characteristics using satellite imagery to investigate surface and visual features. Employing Harmonized Sentinel-2A MSI imagery analysis, coupled with field observations, we uncovered the complexity of the land cover, including variations in vegetation and substrate characteristics. Remote sensing techniques identified the mud volcano land-cover traits based on the normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI), both of which exhibited a linear regression trend with a coefficient of determination (R²) of 0.6184. The findings reveal contrasting patterns between the central, inner, and outer rim regions, distinguishable by specific band combinations, notably [B8, B4, B3] and [B11, B8, B12]. Furthermore, moisture and vegetation around the mud volcano indicate characteristics of recently active mudflow areas, particularly where Typhaceae, Cyperaceae, Poaceae, and Euphorbiaceae are present. This study enhances our understanding of the dynamic land cover of this mud volcano complex and provides insights into its geological and ecological features, offering valuable perspectives for geoconservation.

IOP Conference Series Earth and Environmental ScienceVol. 1451(1)
Bandung Institute of Technology (ID), Sumatera Institute of Technology (ID), Geological Institute (RU)
Openalex Percentile: Top 14%
Geological and Geophysical Studies
1.17
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