Continuous monitoring is crucial for identifying potential threats to cultural heritage sites and implementing timely maintenance and preventive interventions. Scheduled inspections and proactive maintenance strategies are essential to prevent degradation and ensure long-term preservation. This study explores the use of satellite data and remote sensing technologies to monitor and preserve cultural heritage, with a focus on an archaeological park. The use of remote sensing techniques is essential for effective cultural heritage management. Satellite data provides high-resolution imagery that is instrumental in tracking environmental changes and assessing the impacts of human activities. This research utilizes Google Earth Engine (GEE) to process and analyze large datasets, employing spectral indices such as NDVI, NDMI, and NDSI to evaluate vegetation health, soil moisture, and soil characteristics. The methodology involves trend analysis and change detection, highlighting the temporal variations in the study area. The use of cloud-based platforms like GEE facilitates efficient data processing and enhances the scalability of the methodology, making it applicable to various environmental contexts.

Satellite Data Analysis for the Observation and Monitoring of Cultural Heritage. The Case of the Archaeological Park of Metaponto, Italy

Fattore, Carmen
;
Priore, Arcangelo;Porcari, Sara;Porcari, Vito
2025-01-01

Abstract

Continuous monitoring is crucial for identifying potential threats to cultural heritage sites and implementing timely maintenance and preventive interventions. Scheduled inspections and proactive maintenance strategies are essential to prevent degradation and ensure long-term preservation. This study explores the use of satellite data and remote sensing technologies to monitor and preserve cultural heritage, with a focus on an archaeological park. The use of remote sensing techniques is essential for effective cultural heritage management. Satellite data provides high-resolution imagery that is instrumental in tracking environmental changes and assessing the impacts of human activities. This research utilizes Google Earth Engine (GEE) to process and analyze large datasets, employing spectral indices such as NDVI, NDMI, and NDSI to evaluate vegetation health, soil moisture, and soil characteristics. The methodology involves trend analysis and change detection, highlighting the temporal variations in the study area. The use of cloud-based platforms like GEE facilitates efficient data processing and enhances the scalability of the methodology, making it applicable to various environmental contexts.
2025
9783031834318
9783031834325
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/196935
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