Land resources

Land and soil resources are essential components of the natural asset base of the economy and of ecosystems. They are both a private property and a (global and local) common; they are critical for the production of food and other biomass, support recreational activities and, more generally, provide a physical foundation for all economic activity. The way land is used and managed influences everything in the environment. This ranges from biodiversity and ecosystem services (including erosion risk, flood protection, etc.) to soil, water and air quality, and greenhouse gas (GHG) emissions.

The market value of land varies by location. Where demand is low, land is relatively abundant. Elsewhere, many competing demands on land lead to its relative scarcity and drive up its price. Unregulated development driven by the desire to maximise market value leads to conversion of land to the highest-value use. This process, however, fails to account for the ecological value of land. For instance, urban settlements historically developed along navigable streams, sacrificing riparian and wetland ecosystems. Nowadays, in many developed countries, urban expansion mainly occurs at the expense of farmland. Exploitation of natural resources (unsustainable logging, mineral extraction), construction of transport infrastructure, and agricultural expansion continue to be the main drivers of deforestation worldwide.

These underlying drivers and the resulting land cover change are leading contributors to the loss of biodiversity and ecosystem services globally (CBD, 2010). Land development and the resulting changes in land cover lead to habitat fragmentation and loss. They are thus associated with a decline in the populations of many species and reduced biodiversity (Karousakis, 2012). Conversions of agricultural land to artificial land (which include at least partial soil sealing) irreversibly degrade soil and lead to the cumulative loss of productive agricultural land.

The main challenge is to keep a balance between economic, social and environmental objectives. This includes managing land in a manner that directs development away from greenfield and biodiversity-sensitive locations. Land management should also preserve the essential ecosystem functions of the land and the soil, and integrate land-preservation considerations into sectoral policies. This can be achieved using regulation (e.g. spatial planning, land-use zoning, urban growth boundaries and protected area networks) or economic instruments (e.g. conservation easements or payments for ecosystem services, land taxes, biodiversity offsets, and the phasing out of environmentally harmful agricultural subsidies). However, the environmental effectiveness and cost-efficiency of these approaches may differ markedly.

Figure 6.1. Land cover and land cover conversion
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Note: Note (Panel A): Classes have been combined for presentation purposes. Grasslands include agricultural land use types like pasture. Reference period is 2008-12, however the underlying datasets are informed by sensor data from 2003-12. For detailed definitions, see ESA (2016).

Note (Panel B): Minimum change mapped in underlying datasets is 0.05 km2, smaller changes are not recorded and not included here. 0.05 km2 is approximately the size of a new housing development of 250 dwellings at medium housing density. It is therefore likely that these rates of change are considerably underestimated. For detailed definitions see EEA (2016).

Source: OECD calculations based on the CCI-LC datasets (ESA, 2016) and the CORINE-LCC datasets (EEA, 2016).

 http://dx.doi.org/10.1787/888933484623

This chapter focuses on land cover and land-cover change, drawing on information from global land monitoring that has become available only recently. Future editions will aim to address some of the other important issues such as status of soil resources and land degradation, changes in land use, habitat loss and fragmentation, and the impacts of land dynamics on human well-being, pending better availability of internationally harmonised indicators.

Main trends and recent developments

Across all the OECD, built-up areas now cover 30% more land than in 1990

In most OECD countries, natural and semi-natural vegetated land (forests, grasslands, wetlands, shrubland and other vegetated land) covers 30% to 80% of the area (Figure 6.1a, Figure 6.2). At the global scale, these land cover types are essential for provision of ecosystem services and conservation of biodiversity. In some countries such as Denmark and India, cropland is dominant (> 70%). Across all OECD countries, built-up areas now cover 1.11% of the total land area, a 30% increase since 1990.

Globally, an area the size of the United Kingdom has been converted to built-up areas since 1990 (244 000 km2) (Figure 6.4e). Note that “built-up” here refers only to buildings, excluding all other types of urban land such as paved surfaces (roads, parking lots), commercial and industrial sites (ports, landfills) and urban green spaces (parks, gardens); consequently, the share of “urban area” is much larger.

Urbanisation of agricultural and semi-natural land is the major driver of land-cover change in Europe

In Europe, urbanisation is the main driver of land-cover change (Figure 6.1b). Urban and other artificial development typically occurs on agricultural land (at least 796 km2 lost annually from 2006 to 2012, corresponding to approximately 100 000 football fields) and on forested and semi-natural land (280 km2). The second most common type of land cover change is conversion from forests and semi-natural land to agricultural land, and vice versa (e.g. afforestation). Forests and semi-natural land are now converted into agricultural land at a slower rate (from 289 to 144 km2/year between 2000-2006 and 2006-2012). During the same periods, the rate at which agricultural land was converted into artificial surfaces also declined (from 935 to 796 km2/year). However, conversions to artificial surfaces remain a serious concern given the existing level of urbanisation in these countries and its cumulative character. Moreover, these land-cover changes have increased the fragmentation of natural and semi-natural land in most European countries (EEA, 2015).

Intense urban growth occurs in many already highly urbanised countries

There are large variations in built-up area share, ranging from 0.04% of total land area in Iceland to almost 17% in the Netherlands (Figure 6.4a). In most countries built-up area growth slowed from 2000 onwards. The Slovak Republic and the United Kingdom were among the few exceptions (Figure 6.4b). There are also large differences in the amount of built-up area per capita both within and between countries. In most countries, the amount of built-up area per capita is increasing (Figure 6.3, Figure 6.4c and Figure 6.5a). Some countries, including Portugal, Belgium and the Netherlands, have high built-up area growth rates, high rates of conversion as a share of total land, a high (and increasing) ratio of built-up area per capita and a relatively large share of land area already built-up. This indicates that urbanisation pressures in these countries are particularly intense.

Figure 6.2. Share of natural and semi-natural vegetated land, circa 2010
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Note: Natural and semi-natural vegetated land includes land cover types such as pasture, orchards and commercial forestry. Cropland, permanent snow and ice and bare land are excluded. Reference period is 2008-12. However, the underlying datasets are informed by sensor data from 2003-12.

Source: OECD calculations based on the CCI-LC datasets (ESA, 2016). Administrative boundaries: FAO (2015).

 http://dx.doi.org/10.1787/888933484637

Figure 6.3. Built-up area per capita, circa 2014
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Note: “Built-up” refers only to buildings, excluding all other types of urban land such as paved surfaces (roads, parking lots), commercial and industrial sites (ports, landfills) and urban green spaces (parks, gardens). In some countries, there is large uncertainty in sub-national population estimates due to unavailability of reliable census data.

Source: OECD calculations using JRC (2016) “Global Human Settlement Layer” (38m resolution multi-temporal built-up-area dataset) and CIESIN (2016) “Gridded Population of the World, version 4”. Administrative boundaries: FAO (2015).

 http://dx.doi.org/10.1787/888933484647

Figure 6.4. Urban growth occurs in many already highly urbanised countries
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Note: “Built-up” refers only to buildings, excluding all other types of urban land such as paved surfaces (roads, parking lots), commercial and industrial sites (ports, landfills) and urban green spaces (parks, gardens).

Source: OECD calculations using JRC (2016), “Global Human Settlement Layer”.

 http://dx.doi.org/10.1787/888933484652

Figure 6.5. Built-up area growth surpassed population growth in most countries
OECD and G20
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Note: “Built-up” refers only to buildings, excluding all other types of urban land such as paved surfaces (roads, parking lots), commercial and industrial sites (ports, landfills) and urban green spaces (parks, gardens).

How to read this graph (panel A): Countries where the built-up area has grown proportionally more slowly than the population are located in Zone 2: Relative Decoupling. It is more likely that these countries have responded to population increases though densification (i.e. more compact and densely populated urban development relative to their 1990 levels) or the re-zoning of industrial and commercial built-up land.

Countries where the built-up area has grown proportionally more quickly than the population are located in Zone 1: No decoupling. It is more likely these countries have been less successful at dealing with urban sprawl or have seen extensive industrial and commercial development. Countries that saw little, or even negative population growth, all nevertheless saw modest levels of ultimately unsustainable built-up area growth. That is especially true of many Central and Eastern European countries. It is also perhaps surprising that some countries with relatively intense urbanisation rates and pressure such as Portugal and the Netherlands have not densified whereas others countries with less intense pressures have densified.

As noted above, describing the changing urban form is important to better understanding these changes in built-up areas (i.e. compact versus fragmented urban development).

Source: OECD calculations using JRC (2016), “Global Human Settlement Layer”.

 http://dx.doi.org/10.1787/888933484664

The disconnect between built-up area growth and population growth may be explained by societal changes (e.g. growth in single-person households due to higher divorce rates, ageing population), lifestyle changes (e.g. increasing demand for larger, detached homes in the urban periphery), the construction of commercial and industrial buildings, and the changing urban form (e.g. compact high-density development along the urban fringe versus fragmented low-density development scattered throughout the suburbs).

Historically, land development has played an important role in economic growth. Recent data suggest a positive correlation between growth in built-up areas and GDP (r = 0.56). However, similar levels of built-up growth are associated with vastly different GDP growth rates (Figure 6.5b). For instance, while Korea, Chile, Finland, France and Italy have all seen about a 30-40% increase in built up areas, their GDP growth rates have been very different. The challenge is to shift to a more sustainable growth model that relies less on built-up area growth.

Box 6.1. Tropical forest loss continues at alarmingly high rates

Globally, tropical forests have experienced the greatest tree cover change and the greatest tree cover loss (Hansen et al., 2013). Among OECD and G20 countries, Argentina, Brazil and Indonesia have seen the highest rates of tropical forest loss (11.8%, 6.4% and 10%, respectively) during 2000-12 (measured as greater than 50% tree cover loss in land with at least 50% tree cover in 2000).

Subtropical forests such as those in South Africa, Chile, the People’s Republic of China, Australia and New Zealand tend to see high rates of tree cover change due to short-cycle intensive forestry, but with more equal ratios of tree cover loss to gain. On average, temperate forests such as those in Europe and Canada see similar dynamics to subtropical forests. However, they have slightly greater relative tree cover loss, in part because of natural, stand-replacing disturbance regimes.

The above conclusions from Hansen et al. (2013) refer to a biophysical description of tree cover, defined as vegetation at least 5 metres in height and with canopy cover greater than 50%. This type of methodology using remote sensing data can provide harmonised, entirely biophysical land cover information, separate from any consideration of land use. As one advantage, this approach can potentially record all changes, including temporary changes, regardless of how anthropogenic or natural the cause. This can complement standard reporting-based statistics on forest land (see chapter on Forest resources). Remaining challenges include the following: robustly estimating net tree cover gain or loss, identifying policy-relevant information that accounts for the naturally large differences in forest dynamics across different ecological zones, and distinguishing plantation crops and trees in some regions (which might be included as tree cover per the above definition).

Measurability and interpretation

The indicators presented in this chapter relate to:

  • Land cover proportions, by primary land cover type using data from ESA (2016).

  • Land cover conversions, quantifying the conversions between the primary land-cover types with particular focus on conversions of natural ecosystems to anthropogenic ones. The indicator is constructed for Europe (EEA, 2016). Similar datasets exist for a few other OECD countries (for a review, see e.g. Diogo and Koomen, 2016), but assessment across a range of cover types at a more global scale is currently not possible due to the considerable technical challenges in producing these kinds of datasets.

    It is however possible to assess the extent of change in built-up areas (JRC, 2016) consistently at the global scale. This is presented here for OECD and G20 countries. It is likely that similar datasets with a specific focus on a single land cover class (e.g. forest land, wetlands or permanent water bodies) will yield the most usable information globally in the medium term.

The example indicators presented here are based on several very different land cover and land cover change mapping projects. Each of these has distinct limitations, caveats and classification systems.

Recent efforts to strengthen the global land monitoring capacities (e.g. using remote sensing) now provide a wealth of data. These can play an important role in quantifying global land cover change and related environmental phenomena. Earth observation data are a useful complement to administrative and statistical data and an underexploited resource for monitoring natural assets. It allows the production of internationally comparable indicators with the largest possible coverage of countries.

These improvements increasingly allow identifying where changes such as deforestation or urbanisation are most intense. However, land cover changes are the outcome of complex and connected natural and anthropogenic processes that are challenging to characterise; therefore, data gaps remain about the drivers of these changes and their impacts (e.g. quantifying the causes of deforestation or the social, demographic and economic trends that promote urban sprawl).

Sources

CBD (2010), Global Biodiversity Outlook 3, Convention on Biological Diversity, www.cbd.int/gbo3.

CIESIN (2016), Gridded Population of the World, version 4 (GPWv4), Center for International Earth Science Information Network, http://dx.doi.org/10.7927/H4X63JVC.

Diogo, V. and E. Koomen (2016), “Land cover and Land Use Indicators: Review of available data”, OECD Green Growth Papers, No. 2016/03, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jlr2z86r5xw-en.

EEA (2016), CORINE Land Cover Change (2000-06 and 2006-12 datasets), European Environment Agency, http://land.copernicus.eu/pan-european/corine-land-cover.

EEA (2015), Fragmentation of natural and semi-natural areas, European Environment Agency, Brussels, www.eea.europa.eu/data-and-maps/indicators/fragmentation-of-natural-and-semi-1/assessment-1.

ESA (2016), Climate Change Initiative Land Cover (2010 dataset), European Space Agency, www.esa-landcover-cci.org/.

FAO (2015), Global Administrative Unit Layers (GAUL) 2014 version, FAO-GeoNetwork, Food and Agriculture Organization of the United Nations, www.fao.org/geonetwork/srv/en/metadata.show?id=12691 (accessed in March 2016.)

Hansen, M. et al. (2013), “High-resolution global maps of 21st-century forest cover change”, Science, Vol. 342/6160, American Association for the Advancement of Science, New York, pp. 850-853, 10.1126/science.1244693.

JRC (2016), Global Human Settlement Layer (GHS_BUILT_LDSMT_GLOBE_R2015B_3857_38_v1_0 dataset), Joint Research Centre, http://publications.jrc.ec.europa.eu/repository/handle/JRC97705.

Karousakis, K. et al. (2012), “Biodiversity”, in OECD Environmental Outlook to 2050: The Consequences of Inaction, OECD Publishing, Paris, http://dx.doi.org/10.1787/env_outlook-2012-7-en.

OECD (2017), “Green growth indicators”, OECD Environment Statistics (database), http://dx.doi.org/10.1787/data-00665-en (accessed in March 2017).

Further reading

EEA (2016), Urban Sprawl in Europe, European Environment Agency, www.eea.europa.eu/publications/urban-sprawl-in-europe.

OECD (2016), Biodiversity Offsets: Effective Design and Implementation, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264222519-en.

OECD (2013), Scaling-up Finance Mechanisms for Biodiversity, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264193833-en.

UNCCD (2016), A Natural Fix: A Joined-up Approach for Delivering the Global Goals for Sustainable Development, UN Convention to Combat Desertification, www2.unccd.int/sites/default/files/documents/22042016_A %20Natural%20Fix_ENG.pdf.