For any kind of morphometric analysis, data needs to be provided as
GeoDataFrames. Results of morphometric analysis from
momepy can be generally returned as pandas
Series to be added as
a column of existing
GeoDataFrame. All the detailes and attributes of each class are clearly described in the API.
Morphometric functions available in
momepy could be divided into four different groups based on their approach to data requirements and outputs.
Simple morphometric characters are using single
GeoDataFrameas a source of the data.
Relational characters are based on relations between two or more
GeoDataFrames. Typical example is
AreaRatio, which requires a) features to be covered (e.g. land unit) and b) features which are covering them (e.g. buildings).
Network analysis (
graphmodule) characters are based on
networkx.Graphwith additional node or edge attributes.
Additional modules (
utils) cover functions generating new morphological elements (like morphological tessellation) or links between them. For details, please refer to the API.
Majority of functions used within
momepy is not limited to one type of morphological elements. However, the whole package is built with a specific set of elements in mind, based on the research done at the University of Strathclyde by the Urban Design Studies Unit. This is true especially for morphological tessellation, partitioning of space based on building footprints. Morphological tessellation can substitute plots for certain types of analysis and provide additional information, like the adjacency, for the other. More information on tessellation is in dedicated section of this guide.
Generally, we can work with any kind of morphological element which fits selected function, there is no restriction. Sometimes, where documentation refers to buildings, other elements like blocks can be used as well as long as the principle remains the same.
For example, you can use
momepy to do morphometric analysis of:
- morphological cells,
When using more than one morphological element,
momepy needs to understand what is the relationship between them. For this, it relies on
unique_id attributes. It is expected, that every building lies on certain plot or morphological cell, on certain street or within certain block. To use
momepy, each feature of each layer needs its own
unique_id. Moreover, each feature also needs to bear
unique_id of related elements. Consider following sample rows of
Each building has its own unique
building_id, while more building share
block_id of block they belong to. In this sense, in
blocks_gdf each feature would have its own unique
block_id used as a reference for
buildings_gdf. In principle, elements on the smaller scale contains IDs of elements on the larger - blocks will not have building IDs.
Momepy can generate unique ID using
momepy.unique_id() and link certain types of elements together.
Unique IDs are also used as an ID within spatial weights matrices. Thanks to this, spatial weights generated on morphological tessellation (like Queen contiguity) can be directly used on buildings and vice versa. Detailed information on using spatial weights within momepy will be discussed later.