Archaeological Research and Protection
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This study concludes that high-resolution SMCA is effective in detecting geophysical hazards and micro-scale urbanisation pressures; however, integration of socio-economic variables is required to produce a holistic risk assessment for sites situated in low-lying urban zones.
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The acceleration of urban development in Kendari City has placed archaeological remains at significant risk of both physical and anthropogenic degradation. However, no comprehensive spatial risk-mapping system has been established to serve as an evidence base for conservation decision-making. This study aims to construct a degradation risk prediction model for archaeological remains using cloud computing-based Geographic Information Systems (GIS) via the Google Earth Engine (GEE) platform. The methodology employs Spatial Multi-Criteria Analysis (SMCA) with a Weighted Overlay technique, integrating four environmental variables: slope (weight: 40%), land cover (30%), rainfall (20%), and vegetation index (NDVI, 10%). Input data were derived from Sentinel-2 imagery and Google Dynamic World V1 (10-metre resolution), NASADEM (30-metre resolution), and CHIRPS Daily precipitation data for the period 2020–2025. Field validation (ground truthing) was conducted at eight sample sites within Kendari City. The results indicate that 62.5% of sampled sites fall within the high-risk category, with the Baterai Mata site recording the highest score (0.873), driven predominantly by slope instability, whilst the Makam Raja Sao-Sao site exhibited an underestimation anomaly (0.607) attributable to the algorithm’s inability to detect non-physical threats such as land speculation and spatial planning pressures. This study concludes that high-resolution SMCA is effective in detecting geophysical hazards and micro-scale urbanisation pressures; however, integration of socio-economic variables is required to produce a holistic risk assessment for sites situated in low-lying urban zones.
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@article{Hadi2026Based,
title = {A GIS-Based Degradation Risk Prediction Model for Archaeological Remains in Kendari City and Its Surrounding Areas},
author = {Arie Toursino Hadi and Abdul Alim and Salniwati Salniwati and Bainudin Bainudin},
journal = {SANGIA JOURNAL OF ARCHAEOLOGY RESEARCH},
year = {2026},
doi = {10.33772/sangia.v10i1.3669},
url = {https://doi.org/10.33772/sangia.v10i1.3669}
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