Step 4: Calculate material stock and spatialise it
Goal: Calculate the material stock and spatialise it.
Approach
In the last step of the stock accounting method, data from all the previous steps are employed:
- Link material intensities with buildings dataset:The data gathered in the previous steps need to be prepared and aligned. Ideally, you put them into one spreadsheet to link the information.
- You can export the attribute table of the building typologies and building year (that make a unique identifier) and link them to the material intensities.
- Once you have linked the material intensities, you can link this information back to the building dataset.
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Calculate Material Building Stock: Multiply the gross floor area (per typology) in m2 by the material composition (per typology) in t/m2 to determine the total quantity of materials in a typical building of each typology.
- The columns could look like in the table, where by adding up the material weight horizontally, the total weight of a single building can be derived, while the vertical summation reveals the total mass of one material (e.g steel) for all buildings and the entire “weight of the city’s buildings”.
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Spatialise the data: You can spatialise the results, by combining the material stock with the location and land use data to make choropleth maps. These results, can help with answering the question “where material stocks cause flows and [in what] volume?”
- For the spatialisation, the same data from the table is then linked to a GIS shapefile that also contains the ID number of the buildings and their locations. This allows for the generation of maps. In principle, this data can also be aggregated to a higher spatial scale, such as neighbourhoods or postcodes to produce other maps and obtain insights on a different level.
Spatialising the data - from data sheets to an online map
The following steps that are explained here have the aim to create a map that can be rendered by a web browser (and embedded as an interactive element in online reports). However, if you do not have access to this tool, you can also make a map in a GIS program and later share (an image of) that.
Step 1: Calculating material building stock and preparing the data
The first step in creating a web application using geospatial data involves calculating the Material Building Stock for each building using Google Sheets or Excel. This data can be based on a variety of factors, such as the building's size, age, and location, among others. The Material Building Stock represents the quantity of materials used in the construction of the building.
Once the data has been calculated and organised, it can be imported into QGIS. In QGIS, the data is joined with the building ID, which ensures that each building has its Material Stock calculated. This data can then be exported in .geojson format, which is ideal for web applications as it can be easily rendered by web browsers.
Step 2: Importing data to CARTO
The next step is to import the .geojson file into CARTO, a platform that allows for the visualisation and analysis of geospatial data. CARTO automatically converts the file into a BigQuery file, a cloud-based storage and processing system provided by Google Cloud.
This approach allows for the data to be stored on a server, where it can be easily accessed and manipulated. This is critical for creating a web application as it ensures that the data can be rendered quickly and easily, even when there are large amounts of data.
Step 3: Creating the map
After importing the data into CARTO, the next step is to create a map linked to the dataset. This is accomplished by clicking on "Create map" on the top right, which generates a new map linked to the dataset.
The map can be customised using a range of tools and features. This includes the ability to change the basemap, add layers, and create widgets and interactions. CARTO provides a range of tools and features that allow users to create a web application that is tailored to their specific needs.
Step 4: Customising the web application
Once the map is created, the final step is to customise the web application using the editor. The editor allows users to modify the legend, add layers, and change the appearance of the map. Widgets and interactions can also be added, allowing users to interact with the map and the data. For example, users can add filters, search functions, and pop-ups, among other features. This can make the web application more interactive and engaging, providing users with a more immersive experience.
Once the web application is customised to the user's satisfaction, it can be published and shared with others. The final result is a web application that allows users to interact with geospatial data in a meaningful way, providing insights and understanding that would not be possible with static maps.