Geo-TIDE Inputs from Encode Artifacts

This code transforms output artifacts from Encode Energy's BEV (Battery Electric Vehicle) route simulations into geospatial formats compatible with Geo-TIDE, an interactive platform for freight decarbonization planning. It produces enriched GeoJSON layers that include segmented routes, charger locations, and state-level emission intensities.

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Features

• Parses BEV simulation CSV outputs from Encode Energy
• Segments vehicle routes into discrete LineStrings with cumulative metrics
• Annotates segments with state-level electricity emission intensities (e.g., CO₂ rate in g/kWh)
• Extracts charger locations from route configuration files
• Outputs:
  • Route segments GeoJSON
  • Charger points GeoJSON
  • Human-readable simulation summaries (TXT)

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Input Files

Each route must reside in its own folder under encode_artifacts/{ROUTE_NAME}/, and include:

• bev_simulation.csv – the route-level BEV simulation output
• base_config.yaml – simulation configuration with charger locations, vehicle types, and routing metadata

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Installation

Clone the repository and install required packages:

git clone git@github.com:mcsc-impact-climate/encode_geotide.git
cd encode-geotide
pip install -r requirements.txt

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Usage

python source/make_geojsons.py

Outputs will be written to:

encode_artifacts/geojsons/
  ├── I-80_route_segments.geojson
  ├── I-80_chargers.geojson
  ├── I-80_simulation_summary.txt
  └── ...

Emissions Data Source

State-level electricity emissions are loaded from a public S3 bucket:

s3://mcsc-datahub-public/geojsons_simplified/grid_emission_intensity/eia2022_state_merged.geojson

This dataset contains 2022 CO₂ intensity values from the EIA (in lb/MWh) for each U.S. state.