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Welcome to the cityMetrix wiki!

CityMetrix is a framework for calculating geospatial sustainability indicators for urban environments. The process of calculating the indicators is based on two steps:

• collecting the necessary datasets and layers based on the geometry of the city of interest to calculate the indicators
• applying necessary statistics to generate indicators' values

The structure of the framework is following this logic:

• city_metrix directory contains the main package
• layers sub-directory contains the different scripts for extracting the data layers needed for calculating the indicators. Every data layer is defined as a separate python class with the associated parameters that might be needed to extract the layer. One mandatory parameter is the geometry bounding box to use for extracting the layer.
• metrics.py file contains the list of indicators implemented in the framework. Every indicator is defined as a sperate python function that requires to load one or multiple layers.

Types of users

There are two modes for using this framework:

• If you are an indicator user and you want either to extract a layer or calculate one of the implemented indicator for any GeoPandasDataframe you should explore this wiki space: https://github.com/wri/cities-cif/wiki/For-indicator-users
• If you are an indicator developer and you want to contribute by extracting a new layer extraction or developing a new indicator, you should explore this wiki page: https://github.com/wri/cities-cif/wiki/For-indicators-developers

Layers

Every layer is defined as separate python class:

Layer name	class name	Parameters	Layer metadata
Tropical Tree Cover	TreeCover()	min_tree_cover: a threshold to use to filter the minimum percent of tree cover
High Land Surface Temeprature	HighLandSurfaceTemperature()

Indicators