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🌿 Climatic Resilience and Fragility Analysis (CRAF)

🇮🇹 Versione in italiano qui

This repository contains the analytical workflow, datasets, and processing scripts used to develop the climatic fragility and resilience assessment for the Bologna metropolitan area.
The work integrates thermal, land-cover, morphological, and socio-environmental indicators to identify areas exposed to heat and to support evidence-based climate adaptation planning.


🧭 Scope

The analysis combines:

  • land surface temperature (LST) data,
  • vegetation and land-cover metrics,
  • accessibility and structural components,
  • socio-environmental indicators,

to produce the Climatic Fragility Index (CFI) and related metrics for climate-resilient urban planning.

Methodological reference:

Investigating Social Vulnerability to Extreme Heat: Heat Islands and Climate Shelters in Urban Contexts: The Case of Bologna
ISPRS International Journal of Geo-Information (2024)
📄 https://tustorage.ulb.tu-darmstadt.de/server/api/core/bitstreams/5655dda2-e4a6-47c5-861a-4aa6102fe31d/content


📁 Repository Structure

craf/
│
├── notebooks/                      # Jupyter notebooks for each analytical step
│   ├── 01_clip_gdal.ipynb 
│   ├── 02_resampling.ipynb  
│   ├── 03_hot_and_cold_spot.ipynb  
│   ├── 04_NDVI_for_CSI.ipynb  
│   ├── 05_bus_stop.ipynb  
│   ├── 06_disabled_parking.ipynb 
│   ├── 07_accessibility.ipynb  
│   └── ...
│
├── data/                        # Input and processed datasets
│   ├── Climatic_fragility/
│   └── ...
│
├── docs/                        # web mapping
├── requirements.txt             # Python dependencies
└── README.md

📊 Data Sources

Category Source Purpose
Thermal ECOSTRESS LST (NASA JPL) Hot/cold spot detection
Land Cover Sentinel-2, Copernicus Urban Atlas Vegetation and blue-space extraction
Topography Copernicus DEM Slope and morphology
Socio-Environmental ISTAT Census, Climate Shelter Index Sensitivity and adaptive capacity
Administrative Comune di Bologna – Statistical Areas Spatial zoning for analysis
Meteorological Meteoblue, ERA5 Reanalysis LST pattern validation

Large raster and vector files are hosted externally.


🧮 Processing Workflow

The workflow is executed through a sequence of Jupyter notebooks.
Each step integrates a thematic dataset, leading to the final climatic fragility output.

📘 Processing Chain

Clip/Resample → 03_hot_and_cold_spot.ipynb
           ↓
NDVI computation → 04_NDVI_for_CSI.ipynb
           ↓
Accessibility + Structures → 08_identify_structures_for_CSI.ipynb
           ↓
Combine indicators → 09_new_CSI.ipynb
           ↓
Integrate all components → 10_climatic_fragility.ipynb
           ↓
Final index → 11_fragility.ipynb

📔 Notebook Execution Order

  1. 01_clip_gdal.ipynb
  2. 02_resampling.ipynb
  3. 03_hot_and_cold_spot.ipynb
  4. 04_NDVI_for_CSI.ipynb
  5. 05_bus_stop.ipynb
  6. 06_disabled_parking.ipynb
  7. 07_accessibility.ipynb
  8. 08_identify_structures_for_CSI.ipynb
  9. 09_new_CSI.ipynb
  10. 10_climatic_fragility.ipynb
  11. 11_fragility.ipynb

📊 Climatic Fragility Index (CFI) – Summary

The index ranges from 0.0 to 1.0, with higher values indicating higher fragility.

Range Level Description
0.00–0.25 Very Low Strong vegetation and cooling capacity
0.26–0.45 Low Balanced exposure and resilience
0.46–0.60 Moderate Intermediate fragility
0.61–0.75 High Heat-exposed areas with limited mitigation
0.76–1.00 Very High Dense or industrial urban areas

Observed range in Bologna:

0.18 ≤ CFI ≤ 0.81

Examples:

  • Moderate: Triumvirato–Pietra, Casteldebole
  • High: Piazza dell’Unità, Villaggio della Barca
  • Very Low: Osservanza, San Michele in Bosco

⚙️ How to Use

  1. Clone the repository

    git clone https://github.com/TALEA-platform/craf.git
    cd craf
  2. Install dependencies

    pip install -r requirements.txt
  3. Run notebooks from the source/ folder.

  4. Outputs are saved in:

    data/Climatic_fragility/outputs/
    

📍 Study Area

Bologna, Italy — area for climatic fragility validation.


🧩 Project Status

Ongoing (2025) — continuous updates expected.


🇮🇹 Versione Italiana {#versione-italiana}

Questo repository contiene il workflow analitico, i dataset e gli script utilizzati per sviluppare l’analisi della fragilità e resilienza climatica per l’area metropolitana di Bologna.
L’analisi integra indicatori termici, di uso del suolo, morfologici e socio-ambientali per identificare le aree esposte al calore e supportare la pianificazione climatica basata sull’evidenza.


🧭 Obiettivo

L’analisi combina:

  • dati di temperatura superficiale (LST),
  • metriche di vegetazione e copertura del suolo,
  • componenti strutturali e di accessibilità,
  • indicatori socio-ambientali,

per produrre il Climatic Fragility Index (CFI) e indicatori correlati.

Riferimento metodologico:

Investigating Social Vulnerability to Extreme Heat: Heat Islands and Climate Shelters in Urban Contexts: The Case of Bologna
ISPRS International Journal of Geo-Information (2024)


📁 Struttura del Repository

craf/
│
├── notebooks/                      # Jupyter notebooks for each analytical step
│   ├── 01_clip_gdal.ipynb 
│   ├── 02_resampling.ipynb  
│   ├── 03_hot_and_cold_spot.ipynb  
│   ├── 04_NDVI_for_CSI.ipynb  
│   ├── 05_bus_stop.ipynb  
│   ├── 06_disabled_parking.ipynb 
│   ├── 07_accessibility.ipynb  
│   └── ...
│
├── data/                        # Input and processed datasets
│   ├── Climatic_fragility/
│   └── ...
│
├── docs/                        # web mapping
├── requirements.txt             # Python dependencies
└── README.md

📊 Fonti Dati

Categoria Fonte Uso
Termici ECOSTRESS LST (NASA JPL) Rilevamento hotspot e coldspot
Uso del suolo Sentinel-2, Copernicus Urban Atlas Estrazione aree verdi e blu
Topografia Copernicus DEM Morfologia e pendenza
Socio-ambientali ISTAT, Climate Shelter Index Sensibilità e capacità adattiva
Amministrative Aree statistiche Comune di Bologna Unità di analisi
Meteorologiche ERA5 Validazione dei pattern termici

File raster e vector molto grandi sono disponibili su altre sorgenti


🧮 Flusso di lavoro

La pipeline si sviluppa attraverso una sequenza di notebook dedicati a singoli set di dati tematici.
Ogni fase integra un set di dati tematici, che porta al risultato finale sulla fragilità climatica.

📘 Catena di esecuzione

Clip/Resample → 03_hot_and_cold_spot.ipynb
           ↓
NDVI computation → 04_NDVI_for_CSI.ipynb
           ↓
Accessibility + Structures → 08_identify_structures_for_CSI.ipynb
           ↓
Combine indicators → 09_new_CSI.ipynb
           ↓
Integrate all components → 10_climatic_fragility.ipynb
           ↓
Final index → 11_fragility.ipynb

📔 ordine di esecuzione dei notebook

  1. 01_clip_gdal.ipynb
  2. 02_resampling.ipynb
  3. 03_hot_and_cold_spot.ipynb
  4. 04_NDVI_for_CSI.ipynb
  5. 05_bus_stop.ipynb
  6. 06_disabled_parking.ipynb
  7. 07_accessibility.ipynb
  8. 08_identify_structures_for_CSI.ipynb
  9. 09_new_CSI.ipynb
  10. 10_climatic_fragility.ipynb
  11. 11_fragility.ipynb

📊 Sintesi CFI

Indice compreso tra 0.0 e 1.0.
Valori osservati a Bologna: 0.18 ≤ CFI ≤ 0.81.


Esempi:

  • Moderato: Triumvirato–Pietra, Casteldebole
  • Alto: Piazza dell’Unità, Villaggio della Barca
  • Molto Basso: Osservanza, San Michele in Bosco

⚙️ Come si usa

  1. Clona il repository

    git clone https://github.com/TALEA-platform/craf.git
    cd craf
  2. Installa le dipendenze

    pip install -r requirements.txt
  3. Esegui i notebook dalla cartella notebooks/.

  4. I risultati sono salvati in:

    data/Climatic_fragility/outputs/
    

📍 Area di Studio

Bologna, Itala - area per la convalida della fragilità climatica.

About

CRAF contains the analytical workflow, data, and metrics used to develop the General Fragility, Climate Fragility, and Climate Shelter Indexes, offering tools to evaluate exposure to extreme heat and support assessments of urban climate resilience.

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