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Chapter 9: Land Use Classification#

Welcome back! In our journey through spatial data concepts, we've explored how to identify specific points (UPRNs), physical features (TOIDs for Building Features and Building Parts), functional areas (Site Features), postcode areas (Postcode (Code-Point)), and official administrative zones like Wards.

Understanding these boundaries and identifiers is crucial, but what about knowing what the land within those boundaries is actually used for?

Imagine you're planning a new building in a specific area. You need to know if that area is zoned for residential buildings, commercial offices, parks, or something else entirely. Is the project you're proposing compatible with the surrounding area's designated purpose? This is vital for getting planning permission and understanding the context of your development.

This is where the concept of Land Use Classification comes in.

What is Land Use Classification?#

Think of Land Use Classification as assigning a specific label or category to an area of land based on its primary function or what's built on it. It's like giving a piece of land an official tag that says, "This area is primarily used for..."

Examples of land use categories include:

  • Residential (houses, flats)
  • Commercial (shops, offices)
  • Industrial (factories, warehouses)
  • Open Space/Green Space (parks, fields, forests)
  • Transport (railways, roads, airports)
  • Agricultural (farmland)

These classifications often follow official standards set at a national level, like the National Land Use Database (NLUD) classification in the UK, or specific tiers used by Ordnance Survey (OS), such as Tier A (broad categories) and Tier B (more detailed categories).

Land Use Classification data typically represents these classified areas as polygons – shapes on a map that show the boundary of each distinct land use zone. These polygons might come from datasets like the OS National Geographic Database (NGD), specifically the Land Use Features collection, as mentioned in the OS NGD Land Use Features Summary.

Why is Land Use Classification Important for BIM?#

For anyone involved in the built environment, understanding land use is fundamental, especially in a BIM workflow:

  1. Planning Validation: The most direct link is planning. Local planning authorities have rules about what types of development are allowed in areas with specific land use classifications. Knowing the official land use helps you validate whether your proposed BIM project aligns with these regulations before you submit a planning application.
  2. Context and Impact: Understanding the surrounding land use (is it next to a school, a noisy factory, or a quiet park?) is crucial for designing a building that fits its environment and assessing its potential impact (e.g., noise, traffic, privacy).
  3. Linking to Regulations: Many planning policies or environmental regulations are tied directly to land use categories. Having this data allows you to link your project location to the specific rules that apply based on how the land is classified.
  4. Site Analysis: When assessing potential development sites, land use data is a primary filter – you wouldn't typically build a factory on land classified as 'Protected Green Space', for example.
  5. Data Enrichment: You can add the official land use classification as an attribute to your BIM site or property data, enriching your model with crucial external context.

Land Use Classification provides the official label for the purpose of the land your project occupies or interacts with, which is critical for compliance and context.

Key Information in Land Use Classification Data#

Land Use Classification data, like other spatial datasets we've seen, combines geographic shapes with descriptive attributes. Based on sources like the OS NGD LandUseFeatures bSDD Data Dictionary and OS NGD Land Use Features Summary, the key pieces of information for each land use area typically include:

  1. Geometry: A polygon representing the boundary of the land area with this specific classification.
  2. Attributes: These describe the land use.
    • Identifier (osid, siteid): Unique identifier for the land use polygon or the site it belongs to.
    • Classification Codes/Names (nlud_code, nlud_groupdescription, oslandusetiera, oslandusetierb): The core land use classification itself, often provided using national standards (NLUD) or OS's own tiers.
    • Description (description): A plain language description of the land use (e.g., 'Parkland', 'Retail Area').
    • Status (status): For sites, indicating if it's active, planned, etc.

The crucial attributes are the classification codes and descriptions, which tell you what the land is classified as.

How Do You "Use" Land Use Classification Data?#

Typically, you use land use data by loading the polygons into a GIS or spatial analysis tool and then querying the area you're interested in based on its location.

  1. Start with a Location: You have a point location (e.g., coordinates from a UPRN lookup or the centroid of a Postcode) or the boundary of your project site (Site Feature).
  2. Load Land Use Data: Load the Land Use Classification dataset (often provided as polygons in formats like GeoPackage or GeoJSON).
  3. Perform a Spatial Query: Find the land use polygon(s) that contain your point location or overlap with your project boundary.
  4. Access Attributes: Once you've found the relevant polygon(s), read their attributes to get the land use classification codes and descriptions (e.g., nlud_code, oslandusetiera).
  • Example Input: The coordinates for your potential project site.
  • Process: Load the Land Use Classification polygons. Perform a spatial query to find which land use polygon(s) overlap with your site area or contain your location point.
  • Example Output: The tool returns the polygon representing the area, and its attributes include oslandusetiera: Residential, nlud_groupdescription: Dwellings.

You now know the official land use classification for your location, which you can use to check against planning regulations or add context to your BIM project.

The Data Structure#

Land Use Classification data is primarily spatial, consisting of polygon geometries and their descriptive attributes. When you load this data, you're working with shapes on a map, each with characteristics defining its use.

Conceptually, based on the OS NGD LandUseFeatures bSDD Data Dictionary, the structure looks like this (for individual Land Use Features):

Property Name Description Data Type Example Value
osid / siteid Unique identifier for the polygon / linked site String/UUID abc123...
geometry The polygon shape of the land use area Geometry POLYGON ((...))
description Plain language description of use String Parkland
nlud_code National Land Use Database classification code String 110
nlud_groupdescription NLUD classification label String Dwellings
oslandusetiera Broad OS land use classification (Tier A) String Residential
oslandusetierb Detailed OS land use classification (Tier B) String Private Residential
... (other attributes) ... ... ...

Each row or feature represents a defined area on the ground with a specific land use category assigned to it.

Behind the Scenes: Finding Land Use for a Location#

Here's a simplified workflow showing how you might find the land use classification for a specific point location (which you might have obtained from a UPRN lookup or site boundary):

sequenceDiagram
    participant YourSystem as Your BIM/GIS System
    participant LandUseData as Land Use Polygons Data (e.g., GeoPackage)

    YourSystem->>YourSystem: I have a point location (e.g., coordinates) or site boundary.
    YourSystem->>LandUseData: Query/Select polygon feature(s) that CONTAIN this point location OR OVERLAP with my boundary.
    LandUseData-->>YourSystem: Find the matching land use polygon record(s).
    LandUseData->>YourSystem: Return the Geometry (polygon) and all Attributes for that feature(s) (classification codes, descriptions, etc.).
    YourSystem->>YourSystem: I now know the land use classification for my location/site.

This diagram illustrates using a spatial query ("contains" or "overlaps") to identify which land use polygon(s) the point location or site boundary falls within.

Now, let's look at a simple conceptual Python example using the geopandas library to load land use data and find the classification for a specific point. Assume you have a GeoPackage file named land_use_features.gpkg containing the land use polygons.

First, loading the data:

# This is example conceptual Python code
import geopandas as gpd
from shapely.geometry import Point # Need this to define a point

# Load the land use classification data from a GeoPackage file
print("Loading land use classification data...")
landuse_gdf = gpd.read_file('land_use_features.gpkg')
print("Data loaded.")

# Display the first few rows to see columns like classifiers and geometry
print("\nFirst 5 rows of the data (showing key columns):")
print(landuse_gdf[['oslandusetiera', 'nlud_groupdescription', 'geometry']].head())

This code loads the land use polygons into a GeoDataFrame and shows you some key columns, including different classification types and the geometry.

Now, let's say you have the coordinates for a point (perhaps from a UPRN lookup) and want to find its land use classification:

# Suppose you have these coordinates for your location
# Using example coordinates (ensure CRS matches your data!)
my_easting, my_northing = 530100, 180450 # Example BNG coordinates

# Create a Shapely Point object
# IMPORTANT: Ensure this point uses the same Coordinate Reference System (CRS) as the landuse_gdf!
point_of_interest = Point(my_easting, my_northing)

# Find the land use polygon that contains this point
# Assuming landuse_gdf is in EPSG:27700 for this BNG point
containing_landuse = landuse_gdf[landuse_gdf.geometry.contains(point_of_interest)]

# Print the result (might be one or more rows if polygons overlap)
print(f"\nLand use classification(s) for point {my_easting}, {my_northing}:")
print(containing_landuse[['oslandusetiera', 'oslandusetierb', 'nlud_code', 'nlud_groupdescription']]) # Show classification columns

This code snippet demonstrates performing the core spatial operation: finding which polygon(s) from the landuse_gdf contain the point_of_interest. The output would show the row(s) for the Land Use Feature(s) whose boundary encompasses the given location, providing their detailed classification attributes. You can then use these attributes to inform your BIM design or check against regulations.

Land Use Classification vs. Building Use#

It's important to distinguish between Land Use Classification and Building Use (an attribute we saw in the Building Feature data).

  • Land Use Classification: Describes the primary function or purpose of an area of land, which may contain multiple buildings or open space. It follows official zoning or statistical categories (like NLUD). An area might be classified as 'Residential Land Use', even if it contains a small shop or a community hall within that area.
  • Building Use: Describes the specific primary function of an individual building itself (e.g., 'Dwelling', 'Office', 'Retail', 'Hospital'). A building within a 'Residential Land Use' area might have a 'Retail' Building Use if it's a corner shop.

While related, Land Use is about the area, and Building Use is about the structure. Land Use Classification is often a higher-level, regulatory concept.

Conclusion#

Land Use Classification is a vital concept for providing official context about the functional purpose of land areas in Great Britain. By representing these classifications as geographic polygons with attributes following standards like NLUD or OS Tiers, datasets provide the necessary information to validate planning compatibility, understand the site context, and link your BIM projects to location-specific regulations and policies. Using spatial queries to find the land use for your project location is a key step in integrating real-world planning constraints into your BIM workflow.

Now that we've covered how land is classified, let's look at specific, designated features on the landscape that require special consideration: heritage assets.

In the next chapter, we will explore Chapter 10: Heritage Asset (NHLE) and how to access data about listed buildings and other protected sites.

Next Chapter: Heritage Asset (NHLE)

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