Measuring urban footprint to understand city behavior
The cities where we live are in constant development and evolution. Over the last few centuries, they have seen how their size and capacity has increased in an accelerated way, hosting every year a bigger amount of population. According to global data from the UN World Urbanization Prospects, 55% of the population lived in urban areas by 2018 (74% in Europe), a rate that is expected to grow to 68% by 2050.
In this urban horizon of constant growth, it seems logical the need to promote an efficient and responsible management of the expansion of our cities, with the aim of mitigating the social, economic and environmental impact that derives of this development.
Thanks to the increase in the amount of georeferenced data and Open sources, we can design new tools that allow us to improve the knowledge that we have about cities behavior. One of these urban analysis new applications, is the one that we have developed in uDA, for the quantification and the qualification of the Spanish Urban Footprint. uDA Tech will present a series of articles around this concept, studying its different characteristics such as size, density, typology, etc. The main goal of this first section is to define the concept and quantify its dimension in main metropolitan areas with a simple visualization.
First steps: What is Urban Footprint and how to measure it
The urban footprint measures the expansion of a city in the territory. Cities are great sources of cultural and economic wealth as well as an optimal environment for people to develop their lives, but they also have a great impact on the environment due to the pollution that they cause, the consumption of natural and energy resources, as well as the construction of infrastructures (transport, communication, services) that they need for their correct operation.The analysis of the urban footprint allows us to quantify the degree of impact and soil consumption, as well as helping us to know the spatial distribution of people and services in a determined metropolitan area.
For a correct Urban Footprint evaluation, it is not only important to be able to quantify its dimension, but also how the density is distributed in its interior. It is possible to identify different types of cities according to their pressure on the territory, for example the models with a large urban footprint and low density are less efficient and they increase the territory impact compared to other cities where the urban density is bigger and the extension smaller.
For this reason, in the current context of constant urban growth,the study of the Urban Footprint helps us, assuming that cities are indeterminate and unpredictable organisms, to improve the urban knowledge to guide how to design future resilience strategies.
Spanish territory covers a 87,013,900 hectares, of which 2,846,400 hectares are urban area, representing just 3% of the total.
The tool that we have developed in uDA allows us to calculate the extension of the Urban Footprint at the present time from the Spanish Cadastre open data and to qualify its density from the data of the National Statistics Institute (INE) and National Register. It is constructed from the urban cadastral blocks of the whole country, quantifying the growth of cities in a synchronized way with the Cadastre.
The consideration or delimitation of urban area has been taken directly from the one determined in the Cadastre Law*, which includes not only land consolidated with building and services, but also incorporates all soils for urban development (future areas where cities will grow) and areas occupied by public areas and services.
* Real Decreto Legislativo 1/2004, Ley del Catastro Inmobiliario
The main goal will be to quantify the size of the expansion of Spain’s principal metropolitan areas. For that reason,we decided to do the analysis at Functional Urban Area (FUA) scale. The choice to select this scale compared to the municipality scale is due to the fact that municipality dimension scale is sometimes variable in the Spanish territory and in many cases there is no correlation between the importance of the urban area and its municipality extension (a clear example is Barcelona, with a very small municipal size for its great importance).On the other hand, the delimitation of the FUA covers not only the extension of the main city, but also its area of influence. According to the definition of the Urban Audit:
The Functional Urban Area (FUA) consists of the city and its commuting zone. Once all cities have been defined, a commuting zone can be identified based on commuting patterns using the following steps:
1: If 15 % of employed persons living in one city work in another city, these cities are treated as connected cities. In this case, the first city is a part of the Functional Urban Area of the second city and does not have its own FUA. (…)
2: All municipalities with at least 15 % of their employed residents working in a city are identified.
3: Municipalities surrounded by a single functional area are included and non-contiguous municipalities are dropped.
In Spain, there are 80 FUAs, representing a total of 1262 municipalities.
Let’s get down to business: a quick guide to urban footprint viz
The goal in this section will be to construct a visualization, which in a quick and simple way, can understand the extent of the urban footprint and the proportion of soil consumed for each of the FUAs in Spain. We will call it Urban Footprint Extension Atlas. In order to build this Atlas, the urban footprint layer has first been generated by transformation, cleaning and topological correction geoprocesses of the Cadastre urban blocks .
Once we have a clean urban footprint geometry table, the Urban Footprint Extension Atlas can be constructed by following the steps below:
Step 1: Aggregate urban footprint extension data to FUA scale.
It consists in calculating the total area of the urban footprint, the extent of the FUA and the proportion it represents. In order to do this, it is necessary to know the set of municipalities that belong to each of the FUAs. This information is available in the Urban Audit download section.
The aggregated values table has the following fields:
- name: Name of the FUA.
- footprint: Extension of the urban footprint in hectares.
- area_auf: area of the FUA in hectares.
- percentage: proportion of the urban footprint in relation to the total FUA.
Step 2: Defining the style of the base diagram (for an unique FUA)
Once we have the clean data for each of the FUA (80 FUA/row), we will generate a diagram for one of it (i.e. FUA Madrid), to determine the style.
- We are going to draw two circles, each of them representing a area. On the one hand, the dark circle represents the complete FUA area, while the white represents the Urban Footprint area. To do this we will calculate the radius of each of the circles:
radio_auf = sqrt(auf_agg['area_auf'][0] / pi)
radio_hu = sqrt(auf_agg['footprint'][0] / pi)- Now let’s plot them. We need to create a canvas with the the diagram’s dimensions. We are going to represent both circles being tangent in the lower part, so that in this way both areas can be compared in a simple way.
fig, ax = plt.subplots()
fig.set_size_inches(4,8)ax.add_patch(plt.Circle((0, radio_auf),radio_auf , color='black'))
ax.add_patch(plt.Circle((0, radio_hu), radio_hu , color='white'))
- At last we introduce labels to see the FUA data associated.
ax.annotate(auf_agg['name'][0], (0, -0.5),ha='center', va='center', size=16,weight="bold",color='black')
ax.annotate('{} %'.format(round(auf_agg['percentage'][0]*100,2)), (0, -1),ha='center', va='center', size=12)
ax.annotate('HU: {} ha'.format(int(round(auf_agg['footprint'][0]*10**5))), (0, -1.4),ha='center', va='center', size=10)
ax.annotate('AUF: {} ha'.format(int(round(auf_agg['area_auf'][0]*10**5))), (0, -1.7),ha='center', va='center', size=10)
ax.set_aspect('equal', adjustable='datalim')
ax.set_axis_off()
fig.savefig('01_output/images/madrid_footprint.png', dpi=300)
plt.show()
Step 3: Generate a diagrams grid
Once we have defined the diagram style , in a simple way we can visualize a range of a set of FUA (i.e. the first 8).
In addition, to add information to the diagram, you can introduce a new plotting variable such as color. In the following example, a range of colors characterize the percentage of urban footprint with respect to the total FUA area. You just have to define the cmap at the beginning and then introduce it into a loop:
cmap = plt.cm.get_cmap('YlGnBu')for index in range(8):(…)color_map = auf_agg['percentage'][index]
rgba = cmap(color_map*5)
ax.add_patch(plt.Circle((0,radio_auf),radio_auf, color=rgba))
Step 4: Creation of the complete Atlas.
Once you have decided the style of the Atlas, the choice of colours and the size of the typography, you can launch the code for all the FUAs. There are 80 FUAs, so it is decided to order them in rows of 10. In the final result, furthermore, has been included a chart with the maps of the Spanish Urban Footprint to improve the complete understanding.
The Urban Footprint Extension Atlas that we have generated is a clear and simple representation of a complex and abstract concept such as the Urban Footprint. Now, we can easily compare the degree of urbanization of each Functional Urban Areas, and discover aspects more intuitively than looking at a simple table. For example:
- Madrid is the FUA with the largest footprint area, however it only represents 19% compared to 35% in Barcelona or 21% in Valencia.
- There are FUA of similar size, but with a very different urban footprint, such as the FUA of Barcelona and Zaragoza.
- There are FUA with a similar Urban Footprint but with a very different FUA dimension, such as Tarragona and Pamplona.
In the following articles related to the Urban Footprint, we will seek to qualify each of the footprints according to their density, looking for patterns according to their location or population size, so keep in touch!
Research Team: Alejandro Cantera
