Geospatial Change Detection of Mangrove Loss, Persistence, and Regeneration in Lombok Island, Indonesia (2019-2024) Using Geomatic Technologies

Andik Isdianto; Aulia Lanudia Fathah; Muhammad Naufal Eka Putra; Berlania Mahardika Putri

doi:10.48084/etasr.13896

Authors

Andik Isdianto Department of Marine Science, Brawijaya University, Indonesia https://orcid.org/0000-0002-4808-7868
Aulia Lanudia Fathah Master Program of Environmental Management & Development, Brawijaya University, Indonesia https://orcid.org/0009-0005-0443-5241
Muhammad Naufal Eka Putra Department of Marine Science, Brawijaya University, Indonesia
Berlania Mahardika Putri Master Program of Environmental Science, Universitas Gadjah Mada, Indonesia https://orcid.org/0009-0006-9898-3085

Volume: 16 | Issue: 2 | Pages: 34270-34275 | April 2026 | https://doi.org/10.48084/etasr.13896

Received: 6 August 2025 | Revised: 10 September 2025, 13 January 2026, and 19 January 2026 | Accepted: 21 January 2026 | Online: 4 April 2026

Corresponding author: Andik Isdianto

Abstract

This study quantitatively analyzed the spatial-temporal dynamics of mangroves on Lombok Island, Indonesia, by integrating Landsat 8 OLI imagery with GIS-based analysis for the years 2019 and 2024. The study area spans 4,738.14 square kilometers along Lombok Island's coast (center point: 116°19′29.7984″E; 8°39′3.5244″S). Landsat 8 scenes (20/11/2019 and 19/02/2024; 30 m) were preprocessed with radiometric correction (DN to reflectance) and atmospheric correction using Dark Object Subtraction (DOS), followed by band compositing (Bands 2–7) and cropping. Land-cover mapping was carried out using a supervised Maximum Likelihood Classifier (MLC) with Regions of Interest (ROIs) supported by high-resolution basemaps, and change detection was obtained through overlay analysis to identify persistence, loss, and regeneration. The extent of mangrove forests decreased from 1,570.27 hectares (ha) in 2019 to 1,439.94 ha in 2024, representing a net reduction of 130.33 ha (–8.3%). Transition mapping identified 1,059.34 ha of persistent mangroves, 511.13 ha converted from mangrove to non-mangrove, and 386.22 ha of regeneration (non-mangrove → mangrove), enabling the identification of priority zones for targeted conservation and restoration. Classification reliability was confirmed through an independent confusion-matrix-based accuracy assessment (N = 171 points/year), yielding Overall Accuracy (OA) of 95.91% (κ = 0.92) in 2019 and 95.32% (κ = 0.91) in 2024. A limitation is the lack of field-based ground-truth validation.

Keywords:

mangrove change detection, Landsat 8 OLI, supervised land cover classification, accuracy assessment (confusion matrix), mangrove regeneration mapping

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