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https://github.com/urbanmorph/notf

Neighbourhoods of the Future
https://github.com/urbanmorph/notf

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Neighbourhoods of the Future

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README 

          
# NOTF - Neighbourhoods of the Future



**Live site:** https://urbanmorph.github.io/notf/



A collaborative platform for building inclusive, resilient, and people-first neighbourhoods through systems thinking, community engagement, and data-driven insights.



## Structure



- `docs/` - GitHub Pages website (built from website/)

- `data/` - Network data (members, communities, asks/offers)

- `scripts/` - Automation scripts

- `website/` - Website source files

- `website/public/assets/data/climate/` - Ward-level climate data (Bengaluru)

- `supporting documents/` - Project documentation and data processing scripts



## Local Development



```bash

# Install dependencies

cd website

npm install



# Run development server

npm start



# Build for production

npm run build



# Copy to docs for GitHub Pages

cp -r _site/* ../docs/

```



## Data Management



```bash

# Add new member

cp data/members/organizations/_TEMPLATE.yaml data/members/organizations/new-org.yaml



# Validate data

python3 scripts/validate_data.py data/



# Find matches

python3 scripts/match_asks_offers.py



# Generate weekly digest

python3 scripts/weekly_digest.py

```



## GitHub Pages Setup



1. Go to repository Settings > Pages

2. Set Source to "Deploy from a branch"

3. Select branch: `main` and folder: `/docs`

4. Save



---



## πŸ“Š Ward-Level Climate Data



### Overview



NOTF provides open ward-level climate baseline data for Indian cities, starting with **Bengaluru (369 wards)** and **Mumbai (227 wards)**. This granular data enables communities, policymakers, and researchers to track climate action progress at the neighbourhood level.



**Coverage:**

- **Bengaluru:** 7 climate sectors Γ— 369 wards = 2,583 data points

  - βœ… Energy & Buildings (100% coverage)

  - βœ… Waste Management (100% coverage)

  - ⚠️ Transportation (partial data)

  - ⚠️ Air Quality (16 monitoring stations)

  - ⚠️ Water Resources (zone-level)

  - βœ… Urban Greening (100% coverage)

  - ⚠️ Disaster Resilience (flood risk 100%, heat partial)



- **Mumbai:** 2 climate sectors Γ— 227 wards = 454 data points

  - βœ… Energy & Buildings (100% coverage)

  - βœ… Waste Management (100% coverage)

  - ⏳ Transportation (pending)

  - ⏳ Air Quality (pending)

  - ⏳ Water Resources (pending)

  - ⏳ Urban Greening (pending)

  - ⏳ Disaster Resilience (pending)



**Data Quality:**

- Bengaluru: β˜…β˜…β˜…β˜†β˜† (63%) - See [`DATA_SOURCES_AND_CREDITS.md`](supporting%20documents/DATA_SOURCES_AND_CREDITS.md)

- Mumbai: β˜…β˜…β˜…β˜†β˜† (60%) - See [`MUMBAI_DATA_SOURCES_AND_CREDITS.md`](supporting%20documents/MUMBAI_DATA_SOURCES_AND_CREDITS.md)



---



### πŸ“₯ Download Climate Datasets



#### Bengaluru (369 Wards)



**Option 1: Full Dataset (3.8 MB)**

```bash

# Clone repository

git clone https://github.com/urbanmorph/notf.git

cd notf/website/public/assets/data/climate/bengaluru/



# All files:

# - city_climate.json (10 KB) - City-level aggregates

# - ward_index.json (96 KB) - Ward metadata

# - climate_central.json (621 KB) - 63 wards

# - climate_east.json (492 KB) - 50 wards

# - climate_west.json (1.1 MB) - 112 wards

# - climate_north.json (709 KB) - 72 wards

# - climate_south.json (709 KB) - 72 wards

```



**Option 2: Direct Download Links**

```bash

# City summary (10 KB)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/city_climate.json



# Ward index (96 KB)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/ward_index.json



# Corporation data (download specific corporation or all 5)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/climate_central.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/climate_east.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/climate_west.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/climate_north.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/climate_south.json

```



**Option 3: Python Script**

```python

import json

import requests



# Load city summary

city_data = requests.get(

    'https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/city_climate.json'

).json()



print(f"Total wards: {city_data['total_wards']}")

print(f"Total population: {city_data['total_population']:,}")



# Load specific corporation

central_wards = requests.get(

    'https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/bengaluru/climate_central.json'

).json()



for ward in central_wards['wards']:

    print(f"{ward['ward_name']}: {ward['population']:,} people")

```



#### Mumbai (227 Wards)



**Option 1: Full Dataset (2.4 MB)**

```bash

# Clone repository

git clone https://github.com/urbanmorph/notf.git

cd notf/website/public/assets/data/climate/mumbai/



# All files:

# - city_climate.json (10 KB) - City-level aggregates

# - ward_index.json (60 KB) - Ward metadata

# - climate_south.json (221 KB) - 21 wards

# - climate_central.json (369 KB) - 35 wards

# - climate_western.json (463 KB) - 44 wards

# - climate_eastern.json (515 KB) - 49 wards

# - climate_northern.json (820 KB) - 78 wards

```



**Option 2: Direct Download Links**

```bash

# City summary (10 KB)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/city_climate.json



# Ward index (60 KB)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/ward_index.json



# Zone data (download specific zone or all 5)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/climate_south.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/climate_central.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/climate_western.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/climate_eastern.json

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/climate_northern.json

```



**Option 3: Python Script**

```python

import json

import requests



# Load city summary

city_data = requests.get(

    'https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/city_climate.json'

).json()



print(f"Total wards: {city_data['total_wards']}")

print(f"Total population: {city_data['total_population']:,}")



# Load specific zone

south_wards = requests.get(

    'https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/climate/mumbai/climate_south.json'

).json()



for ward in south_wards['wards']:

    print(f"{ward['ward_name']}: {ward['population']:,} people")

```



**Documentation:**

- [`MUMBAI_DATA_SOURCES_AND_CREDITS.md`](supporting%20documents/MUMBAI_DATA_SOURCES_AND_CREDITS.md) - Comprehensive data source documentation

- [`MUMBAI_227_WARDS_DATA_RESEARCH.md`](supporting%20documents/MUMBAI_227_WARDS_DATA_RESEARCH.md) - Ward data research findings



---



### πŸ“„ License: CC BY-NC-SA 4.0





    CC BY-NC-SA 4.0




**You are free to:**

- βœ… **Share** β€” copy and redistribute the material in any medium or format

- βœ… **Adapt** β€” remix, transform, and build upon the material



**Under the following terms:**

- **Attribution (BY)** β€” You must give appropriate credit, provide a link to the license, and indicate if changes were made

- **NonCommercial (NC)** β€” You may not use the material for commercial purposes

- **ShareAlike (SA)** β€” If you remix, transform, or build upon the material, you must distribute your contributions under the same license



**Full License:** https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode



---



### πŸ“ How to Cite



#### Academic Citation (APA)

```

Neighbourhoods of the Future. (2026). Ward-Level Climate Baseline Data for Bengaluru.

Retrieved from https://github.com/urbanmorph/notf/tree/main/website/public/assets/data/climate/bengaluru

Licensed under CC BY-NC-SA 4.0.

```



#### Data Attribution (Required)

When using this data in reports, visualizations, or derivative works, include:



```

Data Source: Neighbourhoods of the Future (NOTF)

GitHub: https://github.com/urbanmorph/notf

License: CC BY-NC-SA 4.0

Original Sources: Census of India 2011, OpenCity.in, BBMP, KSPCB

```



#### BibTeX

```bibtex

@dataset{notf_bengaluru_climate_2026,

  author = {{Neighbourhoods of the Future}},

  title = {Ward-Level Climate Baseline Data for Bengaluru},

  year = {2026},

  publisher = {GitHub},

  url = {https://github.com/urbanmorph/notf},

  license = {CC-BY-NC-SA-4.0}

}

```



---



### πŸ“š Data Sources & Credits



All data compiled from authoritative government and research sources. Full documentation available in [`DATA_SOURCES_AND_CREDITS.md`](supporting%20documents/DATA_SOURCES_AND_CREDITS.md).



#### Primary Data Providers



**Government Agencies:**

- **Census of India 2011** - Population, households, demographics (β˜…β˜…β˜…β˜…β˜† 75%)

- **BBMP (Bruhat Bengaluru Mahanagara Palike)** - Waste management, tree census, ward boundaries (β˜…β˜…β˜…β˜†β˜† 65%)

- **KSPCB (Karnataka State Pollution Control Board)** - Air quality monitoring network (β˜…β˜…β˜…β˜…β˜† 80%)

- **BESCOM** - Electricity consumption estimates (β˜…β˜…β˜†β˜†β˜† 50%)

- **KREDL (Karnataka Renewable Energy Development Limited)** - Renewable energy data (β˜…β˜…β˜…β˜…β˜† 85%)

- **BWSSB (Bangalore Water Supply and Sewerage Board)** - Water supply data (β˜…β˜…β˜…β˜†β˜† 60%)

- **BMTC (Bangalore Metropolitan Transport Corporation)** - Public transport coverage (β˜…β˜…β˜…β˜…β˜† 75%)



**Research & Data Portals:**

- **OpenCity.in** - Urban data portal aggregating official government datasets

  - [Bengaluru Household Consumption Expenditure Survey 2022-23](https://data.opencity.in/dataset/bengaluru-household-consumption-expenditure-survey-2022-23)

  - [Karnataka Renewable Energy Data](https://data.opencity.in/dataset/karnataka-renewable-energy-data)

  - [Solid Waste Management](https://data.opencity.in/dataset/solid-waste-management)

  - [List of Dry Waste Collection Centres](https://data.opencity.in/dataset/list-of-dry-waste-collection-centres-in-bengaluru)

  - [Bengaluru Air Quality Data (2017-2023)](https://data.opencity.in/dataset/bengaluru-air-quality-data)

  - [BMTC Bus Stops and Routes by Ward](https://data.opencity.in/dataset/bus-stops-and-routes-map-by-ward)

- **IISc (Indian Institute of Science)** - Urban research, water resources, urban heat studies

- **Praja Foundation** - Civic data analysis, waste management monitoring

- **IGBC/GRIHA** - Green building certifications



**Data Licensing:**

- OpenCity.in: Open Database License (ODbL)

- Government data: Government Open Data License - India (GODL)

- Census data: Public domain



**Confidence Scores:**

- β˜…β˜…β˜…β˜…β˜… (85-100%) - High quality, verified, recent data

- β˜…β˜…β˜…β˜…β˜† (70-84%) - Good quality, some limitations

- β˜…β˜…β˜…β˜†β˜† (55-69%) - Medium quality, estimates or proxy data

- β˜…β˜…β˜†β˜†β˜† (40-54%) - Limited quality, significant gaps

- β˜…β˜†β˜†β˜†β˜† (25-39%) - Low quality, placeholder estimates



---



### πŸ”§ Data Processing Scripts



Python scripts for generating ward-level climate data are available in [`supporting documents/scripts/processing/`](supporting%20documents/scripts/processing/):



1. **`split_corporation_data.py`** - Split 3.5 MB baseline JSON into 5 corporation files

2. **`generate_ward_index.py`** - Extract ward metadata for routing

3. **`generate_city_summary.py`** - Calculate city-level aggregates and rankings

4. **`generate_ward_pages.py`** - Generate 738 static HTML ward pages

5. **`add_source_metadata.py`** - Add OpenCity.in source attributions



```bash

# Run data pipeline

cd "supporting documents/scripts/processing"

python3 split_corporation_data.py

python3 generate_ward_index.py

python3 generate_city_summary.py

python3 add_source_metadata.py

python3 generate_ward_pages.py

```



---



### πŸ—ΊοΈ Ward Boundaries (GeoJSON)



```bash

# Bengaluru ward boundaries

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/boundaries/bengaluru-wards.geojson



# Mumbai ward boundaries (227 electoral wards)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/boundaries/mumbai-electoral-wards.geojson



# Mumbai administrative wards (24 wards - legacy)

wget https://raw.githubusercontent.com/urbanmorph/notf/main/website/public/assets/data/boundaries/mumbai-wards.geojson

```



**Format:** GeoJSON (RFC 7946)

**Projection:** WGS84 (EPSG:4326)

**Sources:**

- Bengaluru: OpenCity.in + BBMP official boundaries

- Mumbai: DataMeet Municipal Spatial Data (CC BY-SA 2.5 India) + MCGM



---



### πŸ“Š Data Structure



#### City Summary (`city_climate.json`)

```json

{

  "city": "Bengaluru",

  "total_wards": 369,

  "total_population": 8402887,

  "last_updated": "2026-01-23",

  "sectors": {

    "energy_buildings": {

      "clean_cooking": {

        "average": 16.2,

        "distribution": {"high": 0, "medium": 38, "low": 331},

        "top_5": [...],

        "bottom_5": [...],

        "data_source": {

          "provider": "Census 2011 + OpenCity.in",

          "url": "https://data.opencity.in/dataset/...",

          "confidence_score": 0.64,

          "confidence_stars": "β˜…β˜…β˜…β˜†β˜†",

          "methodology": "...",

          "limitations": [...]

        }

      }

    }

  }

}

```



#### Ward Data (`climate_*.json`)

```json

{

  "corporation": "South",

  "ward_count": 72,

  "wards": [

    {

      "ward_id": 42,

      "ward_name": "Jayanagar 4th Block",

      "ward_name_local": "ΰ²œΰ²―ΰ²¨ΰ²—ΰ²° 4ನೇ ಬ್ಲಾಕ್",

      "slug": "jayanagar-4th-block",

      "corporation": "South",

      "population": 18542,

      "energy_buildings": {

        "solid_fuel_households": {

          "value": 12.5,

          "percentage": 12.5,

          "confidence": 0.64,

          "source": "Census 2011",

          "data_source": {

            "provider": "Census 2011 + OpenCity.in",

            "url": "...",

            "confidence_score": 0.64,

            "methodology": "...",

            "limitations": [...]

          }

        }

      }

    }

  ]

}

```



---



### πŸš€ Future Cities



**Planned for 2026:**

- Delhi (272 wards)

- Chennai (200 wards)

- Hyderabad (150 wards)

- Pune (144 wards)



**Contribute:** If you have ward-level climate data for other Indian cities, please open an issue or submit a pull request.



---



### ⚠️ Data Limitations & Validation



**Known Limitations:**

1. **Data Age** - Census 2011 is 15 years old; population estimates extrapolated

2. **Ward Boundaries** - Some wards reorganized since 2011

3. **Incomplete Coverage** - Only Energy & Waste sectors have 100% ward-level data

4. **Estimates** - Many metrics use city averages applied uniformly (electricity, renewable energy)

5. **Informal Sector** - Waste segregation by informal workers not captured



**Validation Process:**

- Cross-referenced with official government portals

- Spot checks on 10% random sample

- Peer review by urban planning researchers

- BBMP/KSPCB officials consulted



**Report Data Issues:**

- GitHub Issues: https://github.com/urbanmorph/notf/issues

- Email: data@neighbourhoodsofthefuture.org



---



### πŸ“– Additional Documentation



- **Full Methodology:** [`DATA_SOURCES_AND_CREDITS.md`](supporting%20documents/DATA_SOURCES_AND_CREDITS.md)

- **Mumbai Data Sources:** [`MUMBAI_DATA_SOURCES_AND_CREDITS.md`](supporting%20documents/MUMBAI_DATA_SOURCES_AND_CREDITS.md)

- **Implementation Progress:** [`WARD_DASHBOARD_FINAL_SUMMARY.md`](supporting%20documents/WARD_DASHBOARD_FINAL_SUMMARY.md)

- **Architecture:** [`ARCHITECTURE.md`](ARCHITECTURE.md)



---



## Contact



Nudge Unit: nudge-unit@notf.in