.. _data-and-methods:

Data and Methods
================

.. _generative-ai-architecture:

Generative AI architecture
--------------------------

The core architecture for the Generative AI-powered demonstrator leverages a combination of key components, including AWS Bedrock, LLaMA 3, LangChain, Django, and datasets from OGC-compliant services. AWS Bedrock serves as the backbone of the system, providing the necessary infrastructure to host and deploy the LLaMA 3 language model (see Figure 2). This ensures the system can efficiently handle large datasets, perform model inference, and generate real-time responses. LLaMA 3 functions as the core Generative AI model, enhancing the demonstrator's ability to deliver context-aware and data-driven insights for coastal resilience applications.

.. image:: images/image2.png

**Figure 2:** Generative AI-powered demonstrator architecture

.. _coastal-vulnerability-index:

Coastal Vulnerability Index (CVI) calculations
------------------------------------------------

In detail, we followed a systematic approach to calculate the coastal vulnerability across Europe and Figure 3 presents a structured workflow for estimating the CVI by integrating multiple geospatial and environmental parameters as well as different spatial queries and AI-driven insights. Thus, a structured workflow for calculating the CVI through a multi-step geospatial analysis framework was developed and the process is divided into five key stages (A to E).

.. image:: images/image3.png

**Figure 3:** A workflow presenting all CVI calculation processes (Adapted by Theocharidis et al. 2024 [2]_).

Stage one (Process A) incorporates the study area selection, the bounding box extraction, and the coastline retrieval using the Overpass API of OpenStreetMap (OSM). Process B involves generating transects along the extracted coastline in .geojson format and assigning spatial data to each transect for CVI computation of Process C. All transects were overlayed with raster files (e.g., elevation, slope, landcover) at the intersecting cells and for all vectorized data (i.e. grid points of Copernicus Data), the closest grid point or feature centroid was joined to the transect and the attributes of the corresponding data.

The aforementioned criteria are sourced from different APIs, including OpenEO, Copernicus Marine Toolbox, and Deltares, ensuring comprehensive data integration. These datasets help in identifying key parameters across three major factor categories:

- **Geological Factors:** These factors describe the physical characteristics of the coastal region, influencing its susceptibility to erosion and geomorphological changes. The key parameters include:

  - *Coastal Slope:* Determines how steep or gradual the coastline is, affecting wave energy dissipation.
  - *Rate of Coastline Erosion:* Measures how quickly the coastline is retreating due to natural or anthropogenic influences.
  - *Coastal Elevation:* Influences the likelihood of coastal inundation and flood risk.

- **Hydro-physical Factors:** These factors represent dynamic oceanographic and climatic influences on coastal vulnerability. The key parameters include:

  - *Mean Tidal Range:* Affects water level fluctuations and coastal inundation risks.
  - *Mean Significant Wave Height:* Determines wave energy impact on coastal erosion.
  - *Relative Sea Level Rise:* Reflects long-term changes in sea levels due to climate change and land subsidence.

- **Socio-economic Factors:** These factors assess human activities and land use that influence coastal resilience. The main parameter considered is:

  - *Land Use/Land Cover:* Indicates human settlements and changes of the coastal environment, which can either mitigate or exacerbate vulnerability.

Having identified and extracted the criteria and all spatial datasets, the CVI is computed for each transect using the formula:

.. raw:: html

    <p style="display: flex; align-items: center; justify-content: center; gap: 1rem;">
      <span><strong>CVI =</strong></span>
      <img src="_images/image11.png">
    </p>

, where each variable represents a key coastal factor such as elevation,
slope, erosion rate, tidal range, wave height, and land use. This
formula integrates multiple environmental and socio-economic parameters
to quantify coastal vulnerability. The result helps identify high-risk
coastal areas for targeted resilience planning.

**Table 1:** CVI Criteria Rankings

.. raw:: html

    <table style="border-collapse: collapse; width: 100%; text-align: center; border: 1px solid #000;">
      <thead>
        <tr>
          <th rowspan="1" style="border: 1px solid #000;"><strong></strong></th>
          <th colspan="6" style="border: 1px solid #000;"><strong>CVI Score</strong></th>
        </tr>
        <tr>
          <th style="border: 1px solid #000;">Factor</th>
	  <th style="border: 1px solid #000; background-color: #e06666;">Very Low (1)</th>
          <th style="border: 1px solid #000; background-color: #f6b26b;">Low (2)</th>
          <th style="border: 1px solid #000; background-color: #ffd966;">Moderate (3)</th>
          <th style="border: 1px solid #000; background-color: #93c47d;">High (4)</th>
          <th style="border: 1px solid #000; background-color: #76a5af;">Very High (5)</th>
	  <th style="border: 1px solid #000;">Availability</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <td style="border: 1px solid #000;"><strong>Coastal land cover</strong></td>
          <td style="border: 1px solid #000;">Tree/Forest</td>
          <td style="border: 1px solid #000;">Shrubland, bare soil</td>
          <td style="border: 1px solid #000;">Cropland, grassland</td>
          <td style="border: 1px solid #000;">Herbaceous wetland</td>
          <td style="border: 1px solid #000;">Urban</td>
          <td style="border: 1px solid #000;">✔</td>
        </tr>
        <tr>
          <td style="border: 1px solid #000;"><strong>Coastal slope (%)</strong></td>
          <td style="border: 1px solid #000;">&gt;12</td>
          <td style="border: 1px solid #000;">8 – 12</td>
          <td style="border: 1px solid #000;">4 – 8</td>
          <td style="border: 1px solid #000;">2 – 4</td>
          <td style="border: 1px solid #000;">&lt;2</td>
          <td style="border: 1px solid #000;">✔</td>
        </tr>
        <tr>
          <td style="border: 1px solid #000;"><strong>Rate of coastline erosion (m/year)</strong></td>
          <td style="border: 1px solid #000;">&gt;2</td>
          <td style="border: 1px solid #000;">(+1) – (+2)</td>
          <td style="border: 1px solid #000;">(–1) – (+1)</td>
          <td style="border: 1px solid #000;">(–1.1) – (–2)</td>
          <td style="border: 1px solid #000;">≤(–2)</td>
          <td style="border: 1px solid #000;">✔</td>
        </tr>
        <tr>
          <td style="border: 1px solid #000;"><strong>Mean tidal range (m)</strong></td>
          <td style="border: 1px solid #000;">&gt;6</td>
          <td style="border: 1px solid #000;">4 – 6</td>
          <td style="border: 1px solid #000;">2 – 4</td>
          <td style="border: 1px solid #000;">1 – 2</td>
          <td style="border: 1px solid #000;">&lt;1</td>
          <td style="border: 1px solid #000;"></td>
        </tr>
        <tr>
          <td style="border: 1px solid #000;"><strong>Mean significant wave height (m)</strong></td>
          <td style="border: 1px solid #000;">0 – 0.55</td>
          <td style="border: 1px solid #000;">0.55 – 0.85</td>
          <td style="border: 1px solid #000;">0.85 – 1.05</td>
          <td style="border: 1px solid #000;">1.05 – 1.25</td>
          <td style="border: 1px solid #000;">&gt;1.25</td>
          <td style="border: 1px solid #000;">✔</td>
        </tr>
        <tr>
          <td style="border: 1px solid #000;"><strong>Coastal elevation (m)</strong></td>
          <td style="border: 1px solid #000;">≥ 20</td>
          <td style="border: 1px solid #000;">10 – 20</td>
          <td style="border: 1px solid #000;">5 – 10</td>
          <td style="border: 1px solid #000;">2 – 5</td>
          <td style="border: 1px solid #000;">0 – 2</td>
          <td style="border: 1px solid #000;">✔</td>
        </tr>
        <tr>
          <td style="border: 1px solid #000;"><strong>Relative sea-level rise (mm/year)</strong></td>
          <td style="border: 1px solid #000;">&lt;1.8</td>
          <td style="border: 1px solid #000;">1.8 – 2.5</td>
          <td style="border: 1px solid #000;">2.5 – 3</td>
          <td style="border: 1px solid #000;">3 – 3.4</td>
          <td style="border: 1px solid #000;">&gt;3.4</td>
          <td style="border: 1px solid #000;">✔</td>
        </tr>
      </tbody>
    </table>

The final steps integrate the Raking Method (scale 0-5) applied to rank
vulnerability factors, visualizing all sub-criteria in LLaMA 3 and the
CVI results for the study area selected by the user (Process D). These
datasets were assigned to transects by overlaying raster data or linking
vector data to the closest points of each transect. Indicators of
vulnerability were then scored on a scale from 0 (low) to 5 (high) (see
Table 1). The CVI for each transect was calculated using a composite
formula and mapped to visualize vulnerability levels: low (green),
moderate (yellow), and high (red), In the last phase (Process E), the
CVI results are transferred to LLaMA 3 for accuracy analysis and
uncertainty assessment, ultimately providing feedback to the user.
   
References
----------

.. [2] Theocharidis, C., Doukanari, M., Kalogirou, E., Christofi, D., Mettas, C., Kontoes, C., Hadjimitsis, D., Argyriou, A. V., & Eliades, M. (2024). Coastal Vulnerability Index (CVI) Assessment: Evaluating Risks Associated with Human-Made Activities along the Limassol Coastline, Cyprus. In Remote Sensing (Vol. 16, Issue 19, p. 3688). MDPI AG. https://doi.org/10.3390/rs16193688