Day 4

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Paper title Innovative Services for Cultural Heritage Monitoring and Risk Prevention
  1. Iulia Dana Negula Romanian Space Agency (ROSA) Speaker
  2. Cristian Moise Romanian Space Agency (ROSA)
  3. Mihaela-Violeta Gheorghe GMV Innovating Solutions
  4. Fredrik Samuel Nistor GMV Innovating Solutions
  5. Andi Mihai Lazăr Romanian Space Agency (ROSA)
Form of presentation Poster
  • D2. Sustainable Development
    • D2.12 Cultural and Natural Heritage
Abstract text Considered by the United Nations Educational, Scientific and Cultural Organization (UNESCO) as being "irreplaceable sources of life and inspiration", cultural and natural heritage sites are essential for the local communities and worldwide, hence their safeguarding has a strategic importance for encouraging a sustainable exploitation of cultural properties and creating new social opportunities. Considering the large spectrum of threats (for example, climate change, natural and anthropogenic hazards, air pollution, urban development), cultural heritage requires uninterrupted monitoring based on a combination of satellite images having adequate spatial, spectral and temporal resolution, in-situ data and a broad-spectrum of ancillary data such as historical maps, digital elevation models and local knowledge. To date, Earth Observation (EO) data proved to be essential for the discovery, documentation, mapping, monitoring, management, risk estimation, preservation, visualization and promotion of cultural heritage. In-situ data are valuable for assessing the local conditions affecting the physical fabric (for example, wind, humidity, temperature, radiation, dust, micro-organisms), while ancillary data contribute to thorough analyses and support the correct interpretation of the results. Therefore, a reliable systematic monitoring system incorporates multiple types of data to generate exhaustive information about the cultural heritage sites.
EO also enables the unique analysis of the cultural heritage from the past (for example, by exploiting the declassified satellite imagery acquired in the 60's) until the present, in order to observe its evolution and explore the past and current human-environment interaction. Most of the scientific studies published on the topic of EO for cultural heritage are centered around the use of some remote sensing techniques for one or more similar cultural heritage sites. But considering the wealth of satellite data that is currently available, new research opportunities emerge in the area of advanced data fusion, big data analysis techniques based on Artificial Intelligence (AI) /Machine Learning (ML) and open collaborative platforms that are easy to use by the cultural heritage authorities. The current study showcases the integration of conventional methodologies such as automatic classification, change detection or multi-temporal interferometry with AI/ML algorithms for the provision of services for cultural heritage monitoring to support the effective resilience of cultural heritage sites against human or anthropogenic risks.
The complex characterization of the cultural heritage sites provided by these services represents is essential for the local and national cultural heritage management authorities due to the unparalleled knowledge provided, namely repeated, accurate and manifold information regarding, amongst others, the time evolution and the conservation state of the cultural heritage along with the early identification of potential threats and degradation risks. The proposed cultural heritage monitoring services will also facilitate the formulation and implementation of appropriate protection and conservation policies and strategies.
This work was supported by a grant of the Romanian Ministry of Education and Research, CCCDI – UEFISCDI, project number PN-III-P2-2.1-PTE-2019-0579, within PNCDI III (AIRFARE project).