🛰️ Space-Based Economic Intelligence

Bachelor Thesis Artifact: "Space-Based Economic Intelligence: Detecting Hidden Resource Anomalies Using Open Satellite APIs"

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🔗 Live Interactive Dashboard

👉 View the Live Satellite Anomaly Explorer

A futuristic, dark-space GIS monitoring console acting as the Decision Support System (DSS) and thesis presentation artifact, showcasing localized lithium, deforestation, and industrial night-light anomalies across 9 verified anomaly events in 3 study regions.

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📊 Key Results

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🏛️ Architecture Overview

[Satellite APIs]        [Economic APIs]
  GEE, CDSE, NASA         World Bank, IMF
       │                       │
[Ingestion Layer]         [Enrichment Layer]
  Rate-limiting,            Temporal alignment,
  retry logic,              GDP cross-reference
  mock-fallback                   │
       └────────────┬─────────────┘
               [AI/ML Engine]
                Isolation Forest (spatial)
                Z-score (temporal NTL)
                Bootstrap CI estimation
                       │
              [Export/Cache Layer]
               docs/data/anomalies.json
               docs/api/v1/ (REST endpoints)
                       │
          [Web Visualization Dashboard]
            Three.js Globe + Leaflet Map
            Spectral Radar + NTL Charts
            Before/After Image Slider
                       │
            [GitHub Pages Deployment]
              CI/CD: GitHub Actions

Repository Structure

tesis/
├── .github/
│   ├── workflows/
│   │   ├── deploy.yml          # GitHub Pages CI/CD
│   │   ├── test.yml            # Pytest (47 tests)
│   │   ├── security.yml        # CodeQL + pip-audit + Gitleaks + SBOM
│   │   ├── lint.yml            # Black + Flake8
│   │   └── data-refresh.yml    # Weekly satellite data update
│   ├── ISSUE_TEMPLATE/
│   ├── dependabot.yml          # Automated dependency updates
│   └── pull_request_template.md
│
├── docs/                       # GitHub Pages — Live Dashboard
│   ├── index.html              # Main SPA (V2: Glassmorphism)
│   ├── index3.html             # V3: Sci-Fi HUD Edition
│   ├── app.js / app3.js        # Dashboard controllers
│   ├── index.css               # Space design system
│   ├── sw.js                   # Service Worker (PWA)
│   ├── manifest.json           # PWA manifest
│   ├── api.html                # Redoc API documentation viewer
│   ├── openapi.yaml            # OpenAPI 3.0 specification
│   ├── robots.txt / sitemap.xml / 404.html
│   ├── locales/en.json         # English i18n strings
│   ├── locales/cs.json         # Czech i18n strings
│   ├── data/
│   │   ├── anomalies.json      # 9 verified anomaly events
│   │   └── regions.geojson     # Study area polygons
│   └── api/v1/                 # Static REST API endpoints
│       ├── anomalies/index.json
│       ├── anomalies/{id}/index.json (×9)
│       ├── datasets/index.json
│       └── status/index.json
│
├── pipeline/                   # Python Data Pipeline
│   ├── notebooks/              # 00_setup → 07_export
│   ├── src/
│   │   ├── ingestion.py        # GEE + CDSE + World Bank fetchers
│   │   ├── preprocessing.py    # Cloud masking, band normalization
│   │   ├── utils.py            # NDVI, NDWI, BSI, Z-score formulas
│   │   ├── models.py           # Isolation Forest wrapper
│   │   ├── anomaly_detector.py # End-to-end orchestrator + bootstrap CI
│   │   ├── economic_overlay.py # Pearson r, 8-point assessment
│   │   └── exporter.py         # GeoJSON / JSON export
│   ├── tests/
│   │   └── test_pipeline.py    # 47 tests across 12 test classes
│   ├── requirements.txt        # Production dependencies (pinned)
│   ├── requirements-dev.txt    # Development-only (pytest, black, flake8)
│   ├── Dockerfile              # Full pipeline reproducibility
│   └── run_pipeline.py         # Pipeline CLI orchestrator
│
├── thesis/
│   ├── chapters/               # Markdown source (Ch. 1–7 + Appendices A–F)
│   └── latex/                  # Compiled LaTeX (main.tex + chapters/*.tex)
│       ├── main.tex
│       ├── references.bib      # 40+ ISO 690 / BibTeX entries
│       └── chapters/*.tex
│
├── README.md                   # This file
├── REPRODUCE.md                # Step-by-step reproducibility guide
├── SECURITY.md                 # Security policy
├── CONTRIBUTING.md             # Contribution guidelines
├── CHANGELOG.md                # Keep-a-Changelog format
└── LICENSE                     # MIT License

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⚡ Quick Start

Prerequisites

• Python 3.12+
• Git

Installation

# Clone the repository
git clone https://github.com/hostilian/tesis.git
cd tesis

# Create and activate virtual environment
python -m venv .venv
.venv\Scripts\activate      # Windows
source .venv/bin/activate    # Linux/macOS

# Install pipeline dependencies
pip install -r pipeline/requirements.txt

# (Optional) Install development tools
pip install -r pipeline/requirements-dev.txt

Configure Environment (for real API access)

# Authenticate Google Earth Engine
earthengine authenticate

# Create .env file (already in .gitignore)
echo "GCP_PROJECT=your-google-cloud-project-id" > .env

For CI/CD and live provider access, configure these GitHub Actions secrets:

Run the Pipeline

python pipeline/run_pipeline.py

Demo Mode: If Earth Engine credentials are absent, the pipeline auto-switches to reproducible mock mode, producing valid JSON/GeoJSON outputs for verification.

Run Tests

pytest pipeline/tests/ -v
# Expected: 47 passed in ~25s

Docker (Full Reproducibility)

docker build -t space-econ-intelligence ./pipeline
docker run --rm space-econ-intelligence pytest pipeline/tests/ -v

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📖 API Documentation

The dashboard exposes a static REST API at /api/v1/:

Interactive API documentation: View API Docs

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📚 Academic Citation (BibTeX)

@thesis{ozturk2026space,
  author  = {Ozturk, Eren},
  title   = {Space-Based Economic Intelligence: Detecting Hidden Resource
             Anomalies Using Open Satellite APIs},
  school  = {Czech University of Life Sciences Prague (CZU PEF),
             Department of Informatics (KII)},
  year    = {2026},
  type    = {Bachelor Thesis},
  advisor = {Bro{\v{z}}ek, Ji{\v{r}}{\'\i}}
}

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🔒 Security

This project implements a full security pipeline:

• Dependency auditing: pip-audit on every push
• Static analysis: GitHub CodeQL (Python)
• Secrets scanning: Gitleaks on full git history
• SBOM: CycloneDX Software Bill of Materials generated per release
• DAST and API fuzzing: OWASP ZAP baseline plus OpenAPI fuzz tests in CI
• Dependabot: Automated weekly dependency updates

See SECURITY.md for the responsible disclosure policy.

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📜 License

Code: MIT License
Satellite data: Used under respective open licenses (Copernicus Open Licence, NASA/USGS Public Domain)
Thesis text: © Eren Ozturk 2026 — All rights reserved pending submission

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🙏 Acknowledgments

• Dr. Jiří Brožek — thesis supervisor, KII PEF CZU
• ESA Copernicus Programme — Sentinel-1/2 open data
• NASA / USGS — Landsat and VIIRS public domain datasets
• Google Earth Engine — Planetary-scale geospatial computing platform
• IBM + NASA — Prithvi foundation model for Earth observation