SCOUT: An Open-Access Scenario-Oriented Urban Toolkit for Decision Support

SCOUT is a decision-support toolkit shaped by requirements from experts across multiple urban domains that operationalizes a decision-making framework through a dataflow model for combining urban data and models and a scenario-oriented visualization grammar that treats decision alternatives and outcomes as first-class objects

Creating a dataflow with SCOUT to explore flood projections.

Installation Guide

To setup SCOUT:

• Follow this guide to install Anaconda.
• Follow this link to install Node. Prebuilt binaries/installer is the easiest way to perform installation.

Data and Models

We added data and models for the three case studies showcased in the paper "backend/data" and "backend/models" folder to illustrate the usage of the system.

Project Setup

Clone the repository or download a zipped version of SCOUT from this page.

Run the following command in the terminal to install the necessary dependencies for the client side setup.

# Navigate to the frontend directory
cd frontend

# Install the necessary client side dependencies.
npm install

Now, run the following commands in the terminal to install the necessary dependencies for the server side, specifically for running the three case studies showcased in SCOUT.

# Navigate to the backend directory
cd backend

# Create a new conda in-folder environment
conda create --prefix ./envs python=3.9.23
conda config --set env_prompt '({name})'

# Activate the conda environment
conda activate ./envs

# Installing required dependencies
conda install -c conda-forge dask-core=2023.4.0 datashader=0.14.4 flask=2.2.3 geopandas=0.12.2 ipykernel=6.19.2 matplotlib=3.7.1 numpy=1.23.5 pandas=2.0.0 python=3.9.16 pygeos=0.14 flask-cors=6.0.1 geopy=2.4.1 osmnx=1.9.4 pyrosm=0.6.2 osmium-tool=1.16.0

# pip dependencies
pip install spatialpandas==0.4.7 opencv-python==4.7.0.72 pyarrow==11.0.0 osmium==3.6.0

Run the application

Open a terminal inside the SCOUT folder. Run the following commands in the terminal:

# Navigate to the backend directory
cd backend

# Activate the conda environment
conda activate ./envs

# Start the server
python server.py

Open another terminal inside the SCOUT folder. Run the following commands in the terminal:

# Navigate to the frontend directory
cd frontend

# Start the web application
npm start