Land use and land cover

Background & relevance

Land use and land cover (LULC) are two overlapping concepts that describe the types of land features found on the Earth’s surface [Owers et al. 2021; Wulder et al. 2018]. The Earth’s surface is a mosaic of natural and non-natural land features, which land use and land cover classify into a pre-defined set of named classes [Grekousis et al. 2015].

Although theoretically similar, land use and land cover differ in the emphasis they place on different types of land features. Land cover emphasises physical features [FAO 2005], with classes typically including:

Land cover class

Notes

Coastline

A line feature, so not explicitly quantified by all data sources

Impervious surfaces

Includes paved surfaces and bare rock

Bare rock

May be a subclass within “Impervious surfaces”

Bare soil

May include subclasses for different soil types

Snow & Ice

May include subclasses (e.g. sea ice, glacier, snowbed)

Water bodies

May include subclasses (e.g. river, lake, pond)

Terrestrial vegetation

Always includes subclasses (e.g. forest, grassland, wetland, cropland)

Urban

May cover impervious (e.g. buildings) or green features (e.g. rooftop parks)

Land use emphasises how humans use the Earth’s surface. Land use classes are less consistent among data sources than land cover classes [Fritz et al. 2017], but can include:

Land use class

Notes

Agricultural

May include subclasses (e.g. cropland, rangeland)

Urban

May include subclasses (e.g. residential, commercial, industrial)

Protected area

May include subclasses (e.g. UNESCO, NNR, National Park)

Recreational

-

Land cover is a spatially explicit concept, meaning that a single point or pixel cannot be classified as more than one land cover class (e.g. water and forest). Land use also tends to be spatially explicit, although it is possible for there to be some overlap between land use classes (e.g. recreational and protected areas).

In combination, land use and land cover are not spatially explicit, in that it is usual for a point or pixel to have both a land use and land cover class. Some examples of this are protected forests (land use: protected area; land cover: forest), city parkland (land use: urban; land cover: rangeland), grazed peatlands (land use: agricultural; land cover: peatland), and developed coastline (land cover: coastline, land use: urban).

Areas containing multiple points or pixels are either represented as a grid of classes or aggregated to a relative fraction (%) of each class [Owers et al. 2021].

In practice, land use and land cover are usually combined into a single concept — here LULC — although some data sources only quantify one or other of them.

Importance

LULC is of foundational and direct importance to nature data teams, in that it contributes directly to business operations and regulatory compliance.

LULC is a basic identifier for what is present at a specific location at a given point in time. This makes LULC of direct value to strategic and operational workflows, including urban and regional planning, natural hazards monitoring, auditing natural assets (i.e. what is where), planning management interventions (e.g. new planting), and monitoring change over time (e.g. deforestation, infrastructure expansion).

LULC also supports other concepts by setting expectations about how a specific location should behave. Examples include using LULC classes to understand why species richness is low in certain areas (e.g. urban, cropland) and using LULC variation across a site to create a stratified sampling strategy for in situ measurements.

Finally, LULC is required for some regulatory compliance frameworks, such as the Taskforce for Nature Related Financial Disclosures (TNFD).

Dependencies & influences

Below are non-exhaustive lists of how LULC depends on and influences other concepts. Linked concepts can be existing or anticipated concepts, or may be concepts that are important but never actually operationalised.

LULC depends on

Concept

Details

Policy and regulation

Local, national and international policies shape how humans are permitted to use the landscape and at what intensity; affects land cover through realised land use activities

Human land use (conversion)

Human land use is a major determinant of land cover; logging converts land cover from forest to non-forest (vice versa for planting); urbanisation creates new urban land cover

Topography

Slope, elevation, and aspect affect where different vegetation types grow and how humans use the landscape

Erosion

Natural erosion caused by wind, water, or ice can shape land cover over long time periods; particularly obvious with soil erosion (e.g. exposure of bare rock) and retreating coastlines

Natural disasters

Natural disasters, such as hurricanes, floods, wildfires, volcanic eruptions, and landslides, can cause changes in land cover — sometimes over very large areas

Temperature

Temperature affects where different vegetation types grow and how humans use the landscape; climate warming can alter permanent ice extents (e.g. glacier retreat) and coastlines (i.e. sea level rise)

Water availability

Water availability through groundwater, surface water, and precipitation affects where different vegetation types grow, how ice features and water bodies expand and contract, and how humans use the landscape

Seasonal cycles

Seasonal cycles in temperature and precipitation expand and contract water bodies and seasonal ice; most relevant to temperate, polar, and mountainous regions

Herbivory

Herbivores shape land cover mosaics by having preferences for certain vegetation types (e.g. tree saplings); herbivore population booms can convert land cover from one class to another

Species migrations

Plant migrations into new areas can create a new LULC class (e.g. tree encroachment into tundra); animal migrations into new areas can alter existing land cover mosaics through herbivory

LULC influences

LULC influences other scientific concepts directly and indirectly:

  • Direct [covered here]: LULC affects concepts that depend on the identity, abundance, or spatial patterns of specific LULC classes in a given area

  • Indirect [not covered here]: by describing land features with distinct characteristics, LULC can be used as an indirect indicator of the characteristics themselves (e.g. forest usually contains more plant biomass than cropland)

Concept

Details

Topography

Human land use, including urban development and agriculture, alters topography

Avalanche risk

Avalanche risk is higher where there is abundant snow and ice cover; vegetated land cover classes can act as physical avalanche barriers

Landslide risk

Plant roots anchor soil to the ground and limit soil movement, making vegetated land cover classes less prone to landslides

Fire risk

Vegetated land cover classes are fuel for fire, making wildfires more likely and intense where vegetated land cover classes are present; some land use practices alter the quantity and distribution of fuel in a landscape; particularly relevant to forests; spatial patterns of land cover in a landscape affect fire spread (e.g. firebreaks)

Flood risk

Lateral water flow is faster across bare rock and urban areas, increasing flash flood risk in non-vegetated land cover classes; upland forests slow catchment discharge; land use practices that compact, remove, or alter soil (e.g. intense grazing) accelerate water discharge

Soil erosion

Plant roots anchor soil to the ground and create a physical barrier to lateral water flow, making vegetated land cover classes more resistant to soil erosion; land use practices that compact, remove, or alter soil (e.g. intense grazing) accelerate rates of soil erosion

Soil carbon stock

Land use designations (e.g. nature reserves) and conversion (e.g. from forest to cropland) affect the amount and spatial distribution of soil carbon

Soil nutrient stock

Land use designations (e.g. nature reserves) and conversion (e.g. from forest to cropland) affect the amount and spatial distribution of soil nutrients

Plant biomass

Land use designations (e.g. nature reserves) and conversion (e.g. from forest to cropland) affect the amount and spatial distribution of plant biomass

Plant biodiversity

Land use designations (e.g. nature reserves) and conversion (e.g. from forest to cropland) affect the amount and spatial distribution of plant biodiversity; connected patches of natural land cover classes help to sustain plant diversity in managed landscapes

Animal biodiversity

Land use designations (e.g. nature reserves) and conversion (e.g. from forest to cropland) affect the amount and spatial distribution of animal biodiversity; connected patches of natural land cover classes help to sustain animal diversity in managed landscapes

Soil biodiversity

Land use designations (e.g. nature reserves) and conversion (e.g. from forest to cropland) affect the amount and spatial distribution of soil biodiversity

Data requirements

The data that is used to quantify LULC. Variables come from three sources: (i) market demand; (ii) what science tells us is important; and (iii) what regulatory frameworks use.

  • Relevance: ability of variable to represent the concept of LULC

  • Scientific use: usage of variable in academic research

  • Regulatory use: usage of variable in regulatory nature frameworks

Name

Unit

Relevance

Scientific use

Regulatory use

Notes

Consensus LULC class

Categorical

Direct measure

Ubiquitous

Regularly used

Consensus is the best LULC class assignment

Presence/absence of LULC class

Categorical

Direct measure

Sometimes used

Regularly used

Separate variables for each LULC class; pivoted version of consensus LULC class

Probability of LULC class occurrence

%

Direct measure

Sometimes used

Rarely used

Separate variables for each LULC class; relative likelihood of a pixel being that class

LULC class fractional cover

%

Direct measure

Sometimes used

Rarely used

Separate variables for each LULC class; fractional cover of that class within that pixel

LULC change

Categorical

Direct measure

Rarely used

Sometimes used

Change in a pixel/point LULC class over time; definitions of change and time vary