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Q
1
Analysis definitions space
occupation
The EU objective of no net land take by 2050 (NNLT) has its origins in environmental policy and is
intended to protect agricultural and natural land from urbanization, as it is mostly an irreversible
process. Although there is no official definition yet, it is primarily about converting (natural or
agricultural) land use to (semi-)urban functions and, in particular, paving. If this becomes an
obligation under European law, an unambiguous definition must be established. And if this
obligation involves monitoring and reporting - it is expected that it will - then this definition must
also be able to be operationalized with quantifiable indicators that are preferably collected and
measured in the same way by all member states in order to make international comparisons.
1.1 Overview definitions
Over the years, various definitions of land take and related concepts have been given within
countries and in international forums (Marquard et al. 2020). It is clear from the definitions on land
take that there are broadly two different interpretations regarding this topic. In part, this is due to
the coincidence of the two related terms land and soil.
The most common definitions concern land and look purely at the quantitative change of land use
to urban or "artificial" functions. Land take or land take can thus be unambiguously expressed in
hectares. The same applies to the opposite process (e.g., letting an industrial site go wild). Another
term, land consumption, is usually understood as this quantitative/functional form of land take.
The differences between these definitions then lie mainly in what functions are meant by "urban"
or "artificial. Consensus exists on built-up areas such as residential and commercial areas, and
many definitions also explicitly mention (transportation) infrastructure. However, there are several
gray areas of human or urban use (think construction pits, landfills, greenhouse farming,
reclamation areas, wind turbines and solar arrays). A special category on which there is no
consensus is "urban green space," or parks, parklands, sports fields or recreational areas: these
places are usually considered urban, but are largely unpaved and may host natural functions. There
are also differences between definitions in terms of original function: nature, forest and agriculture
are often mentioned, but also 'semi-natural' land such as an unused pasture that is occasionally
mowed; EEA also mentions the loss of rural areas in general when describing land take.1 Following
the broad EEA definition of land consumption, in Flanders land take is described as follows: 'It is a
broader concept than building or paving, in fact it includes all parts of the settlement structure
including agricultural structures, industry and non-built parts such as gardens, parks and
recreational uses' (Building Shift 2021 Task Force, p. 5).
The second type of definition concerns 'soil' and here consideration is given to the future use and
ecological quality or fertility of the area. The most explicit proposition is in French environmental
law where land encroachment (or "artifice mitigation") involves the degradation of ecological
functions of soil. Because this implies a more qualitative approach (degradation suggests a sliding
scale), it is not clear whether gradations of land take are possible, e.g., that a hectare of land that
provides crucial ecosystem services should weigh more heavily than a hectare of land that does not
or less so. Binder et al. (2021) recommend that even nearby natural areas be included in the
calculation of additional land take to account for issues such as landscape fragmentation and noise
pollution (Schatz et al. 2021, p. 7). Linked to this is the discussion about the disappearance of fertile
agricultural land. Among other things, this requires knowledge about the type of agriculture (e.g.,
horticulture, arable, pasture) that will be converted to urban functions.
A related term is soil sealing. It may differ from land sealing for at least two reasons. First, there are
unpaved urban functions such as parks, public gardens and (some) sports grounds where there is
little or no sealing. Second, there are paved non-urban functions such as livestock housing and
greenhouse farming in agricultural areas and visitor centers in natural areas. Finally, the primary
concern is not soil quality but the quantity of cover. Important in measuring soil cover is the
accuracy of the analysis; at a higher resolution, paved roads and driveways come into focus, but
also (non-tiled) backyards. Thus, different values for soil cover can be calculated for the same area
depending on the resolution of the source data.
1.2 Analysis of quantitative definitions
1.2.1 Delineation and methods
The two types of definitions quantitative and qualitative require separate analyses. The first
concerns only the area of function change and can be calculated relatively easily. The second
requires more interpretation (of, for example, soil quality or ecosystem services).
All analyses primarily use Corine data (Corine Land Cover (CLC) for the existing situation and Corine
Land Cover Change (CHA) for changes). This is the only source that has both European coverage
and sufficient information on land use. A major drawback is that this dataset is coarse (25ha for CLC
1 One striking definition is the EEA's for
land consumption: it is so broad that it even includes agriculture
and forestry, that is, virtually any use for economic production (Marquard et al. 2020, p. 7). One
consequence of this is that building a housing development on a former orchard would not represent a
land take increase.
and 5ha for CHA) to properly recognize small-scale spatial developments. As a result, there is both
overestimation and underestimation of the extent of land take (see Section 3.5). Because of the
relatively large-scale project development in the Netherlands, these data are sufficient for a global
estimate (and hence this quick scan). The advantage is that it is possible to immediately calculate
how the Netherlands scores relative to other member states (bearing in mind that results
elsewhere may be less reliable).
Land take increase is calculated in this study for the period 2000-2018: the longest time series of
the Corine dataset; if necessary, the three sub-periods (2000-2006, 2007-2012, 2013-2018) can be
zoomed in. To simplify calculations and presentation, the 11-category grouping of Corine use
classes from the ESPON SUPER project is used. Again, the finer 44 Corine classes can be zoomed in
as needed.
1.2.2 Dutch land take in a European perspective
If the EEA's most extreme definition of land consumption (which includes intensive forestry and
agriculture) is excluded, the broadest definition of land take in the Netherlands adds up to about
70,000 hectares (gross) for the period 2000-2018, or about 10 hectares per day since the turn of
the century. By comparison, Germany has long had a goal of reducing urbanization to 30 hectares
per day and Flanders 3 hectares per day by 2025 (and zero by 2040) and Luxembourg 0.25 hectares
per day by 2035.
Table 1
Gross land take increase Netherlands by use class in 2000-2018 in ha
Use class
ha
Urban area (residential, retail, mixed)
10.685
Job sites (industry, business parks)
7.603
Infrastructure (including airports)
2.721
Reclamation (mining and quarrying).
2.143
Landfills
217
Construction sites
38.446
Urban green space and recreation
7.875
Total gross land take increase
Source: CHA 2000-2018, own edit
69.690
Figure 1
Source: CHA 2000-2018, own edit
Figure 1 shows the position of the Netherlands within Europe. The major EU countries have the
largest increase in land take in absolute terms in the period 2000-2018: The Netherlands occupies a
sixth position after Spain, France, Germany, Poland and Italy. This comparison should be taken with
a grain of salt because, as mentioned, the European data are not based on accurate measurements
so small-scale urban developments are not accurately reflected. As a result, figures for Belgium,
among others, must be considered unreliable. This problem is explained in more detail in section
3.5.
However, when the land take increase is plotted against the total area2 (an indicator of intensity),
the Netherlands is the European leader. In terms of relative growth (land take increase relative to
the size of urban area in 2000), the Netherlands ranks sixth, far behind Spain where extreme urban
area expansion has taken place.3
2 In this calculation, the territory of the Netherlands is taken
without inland water (IJsselmeer). If inland
water is included (4,154,300 hectares instead of 3,497,464 hectares) little changes in intensity except
that the Netherlands consistently ranks second, behind Cyprus.
3 These figures differ slightly from earlier PBL publications on the subject. The reason is that they follow
the most common definitions of land take that consider building sites as land take. In the ESPON
SUPER project, among others, building sites are seen as an intermediate category: only upon
completion was a development registered as urban. Moreover, Iceland, Norway, Switzerland and the
United Kingdom were also included in the analysis there.
Figure 2
Source: CHA 2000-2018, CLC2000, CLC2018, own editing
All figures so far refer to gross land take increase. To calculate the net increase in land take, we
must also look at the decrease in land take, functions converted from urban to non-urban in the
same period. For the most part, this involves abandoned building sites. To a lesser extent it involves
reclaimed land or landfills (such as Diemerpark in Amsterdam). Only 5 hectares concern the
disappearance of urban areas and 25 hectares for work sites. Altogether, the decreasing land take
was 5,833 hectares in the period 2000-2018. Together, for the Netherlands this means a net land
take of 63,857 hectares or around 9.7 hectares per day.
The increase in land take in the Netherlands is almost 14 times greater than the decrease in land
take, which is not exceptional in Europe. There is wide variation among member states. The Czech
Republic, Germany and Luxembourg have only four times as much positive land take, so the "net"
aspect is very important in meeting their target. In contrast, Slovenia, Romania and Malta have
relatively little declining land take.
Table 2
Declining land take in the Netherlands in 2000-2018 in ha
urban
agriculture
building
urban
area
purview
infrastructure
mining
landfill
site
greenery
5
22
35
57
33
885
13
nature
(vegetated)
191
2697
nature (bare)
wetlands
3
Total
5
25
Source: CHA 2000-2018, own edit
44
273
70
1505
79
521
103
5088
13
In the Netherlands, non-implementation of construction projects on building sites is the main cause
of decreasing land take. But within the EU27, the disappearance of reclaimed land is more
important. Indeed, a significant part of the declining land take in Austria, Estonia and Romania can
be explained by this. In absolute terms, Germany, Spain and Poland have 'returned' many hectares
of such 'artificial' land to agriculture and nature.
Incidentally, correcting gross land take increases does not change the relative position of the
Netherlands in Europe in terms of intensity and growth.
1.2.3 Sensitivity analysis definitions space occupation
The picture of the Netherlands as a country with relatively large land take changes with the
application of different categories in the definitions. Always subtracting categories from the
broadest definition reduces the gross increase in land take anyway, but also the possible decrease
in land take.
To calculate the gross land take increase when deleting a category, two steps are required. We take
the deletion of urban green space as an example. First, the number of acres from this category is
subtracted from the total gross land take increase, because all acres of rural functions developed to
urban green space no longer count as land take (69,690 - 7,875 = 61,815). But because urban green
space has now become a "rural" category, all change from it to the other urban functions such as
housing, work and infrastructure (this involves 1,123 acres) is now land take and must therefore be
added (61,815 + 1,123 = 62,938). Next, the net increase in land take must be calculated. As urban
green space is no longer considered urban/land use, any change from this to rural functions is no
longer a decreasing land take (5,833 - 13 = 5,820). The net land take increase for the first
alternative definition (without urban green space) is then: 57,118 hectares (62,938 - 5,820).
The results of this calculation are the starting point for calculating the next definition in the same
way. Table 3 shows the results for all definitions.
Table 3
Gross and net space take increase in 2000-2018 in the Netherlands by definition
Definition of land take
Gross
Net
Wide
69690
63857
- Urban greenery
62938
57118
- Urban greenery, artificial
60625
55429
- Urban green, artificial, construction site
47597
47488
- Urban green space, artificial, construction site, infrastructure
Source: CHA 2000-2018, own edit
45008
44978
The first alternative category involves removing urban green space and recreation from the broad
definition. One argument for this is the low percentage of urbanization of these functions; in fact,
the ground is hardly covered by buildings, if at all. Looking separately at these two Corine classes,
the Netherlands laid out the most urban green space (parks, public gardens, urban forests) - in
absolute terms - between 2000 and 2018, just slightly more than Spain. The Netherlands is then the
European leader. Recreational land (sports fields, golf course, allotments, race track) is a much
larger category and there the Netherlands scores somewhat lower in absolute terms, fifth in
Europe. Removing recreational areas would make the biggest difference in Austria where this
category represents one-third of the total land take increase. Removing both classes (urban green
space and recreation) from the definition would be relatively favorable for the Netherlands.
Because it is a relatively small category, however, not much changes. In the ranking, the
Netherlands remains first in terms of intensity and sixth in terms of growth.
Figure 3
The second definition involves excluding "artificial land" such as landfills and reclamation sites
(these categories are not always mentioned and are not urban). Because these categories occur
relatively infrequently in the Netherlands, they have little impact on the domestic land take
increase. They hardly change the ranking of the Netherlands within Europe. The situation is
different for other countries: clearing is an important component of additional land take in
Bulgaria, Estonia and Latvia. There, removing this category will significantly reduce their land take
increase. This places the Netherlands fifth in terms of growth (Greece is now sixth) and still ranks
first for intensity.
The third definition, which also removes the 'building sites' class, has a major impact on Dutch land
take increase. Building sites account for more than half of the Dutch land take increase; in fact, this
is also the case in Lithuania and Slovakia. In Spain (known for abandoned building sites) it accounts
for 48 percent of the additional land take. One argument for not including building sites is that it is
uncertain whether they are actually built on; they are an intermediate stage, which can complicate
monitoring. This also appears to be the case in the calculation: in some member states the increase
in land take becomes larger in this definition because there was more change from building land to
urban functions (realization) than building land added from rural functions. In terms of the ranking,
the Netherlands returns to sixth place, behind Portugal. For intensity, the Netherlands is at the top
as always.
Less likely is the exclusion of infrastructure. One argument for this may be that it cannot be
accurately measured at a low(er) resolution (like Corine). Incidentally, this definition would mean
little for the Netherlands (less than 5 percent of total land take increase), but a lot for Croatia
(more than a third). Next come Greece, Malta and Portugal with just above 10 percent. This leaves
the Netherlands in sixth place in terms of growth. Interestingly, the Netherlands is just overtaken
by Cyprus (which has always ranked second) for intensity.
1.3 Analysis qualitative definitions
1.3.1 Methods
The best way to estimate how much valuable soil disappeared during the period 2000-2018 would
be to compare the land take increase cartographically with the local soil quality in 2000.
Unfortunately, such mapping material is not available, but 16 maps are available for the situation in
the present. This makes it technically possible to monitor qualitative land take increase from now
on and perform scenario analysis on future land take by testing the exact change to urban use in a
GIS system against the various ecosystem maps. In carrying out this analysis, it turned out that this
method required more computing power than was practically possible for this quick scan. As a
result, an alternative analysis was performed.
Maps on ecosystem services
1. The following 16 maps were read into a GIS.
 perc_service_1D_energy production_wood
 perc_service_1D_wood production_wood
 perc_service_1D_carbon storage_forest
 perc_service_2A_Fertility_hydrology
 perc_service_2D_refrigeration
 perc_service_2 _water treatment_retNE
 perc_service_2 _water treatment_retPE
 perc_service_2F_plague suppression
 perc_service_2G_pollination
 perc_service_2H4_CO2emissions peat
 perc_service_2J_AQ_conc
 perc_service_2J_AQ_pop




perc_service_2L_infiltration_mm
perc_service_2L_infiltration_pop
perc_service_3A_green_recreation
perc_service_3B_MNP
Note: These maps are normalized stocks (from 0-100 percent). They are always about the effect
of vegetation in providing an ecosystem service. Water purification is nitrate and phosphate. AQ
is Air Quality, which is determined as the percentage of particulate matter PM2.5 filtered to
bring exposure below the WHO standard. Both Air Quality and infiltration maps are included,
idem for air purification. MNP is a biodiversity indicator and is about the number of species for
which there are good conditions.
Figure 4
Impression composite ecosystem map
Source: PBL/WUR
The alternative analysis involves first assessing the 44 land use classes from Corine 2018 for their
current ecological values using the current map material. First, the legends of the 16 maps are
normalized and stacked on top of each other. The result is an aggregate map that represents an
index value of all 16 components (see Figure 4). Then, for each CLC land use class, the average
value is calculated. In principle, this average value can be multiplied by the increase in land take
over the period 2000-2018 to get an impression of the change in soil quality.
1.3.2 Dutch land take in European perspective
Agriculture provides most of the land for functions covered by land take in Europe. In contrast, the
share of wetlands is usually negligible: in only 10 countries does more than 1 percent of
urbanization take place on wetlands. The northern countries Estonia (8.5 percent), Latvia (4.7
percent) and Finland (3.7 percent) do the most (the Netherlands sits at 2.5 percent). There is wide
variation in the share of nature as a source of additional land take, however. Finland (82 percent),
Sweden (65 percent), Croatia (62 percent) and Portugal (61 percent) use natural areas the most for
(semi-)urban functions while the Netherlands (3 percent), Ireland (4 percent) and Denmark (5
percent) do so the least. At the EU27 level, the figure is 21 percent. The share of "barren nature"
hardly appears as a source of additional land take: only Portugal, Croatia and Spain have a share
greater than 1 percent (but still below 2 percent).
Figure 5
Source: CHA 2000-2018, own edit
In the subcategories of agriculture and nature, the differences between member states become
even greater. This is partly explained by territorial diversity: after all, there will be little or no land
take increase in the category of olive groves in Finland or beach areas in Slovakia, because Finland
has no olive groves and Slovakia has no beaches. From most agricultural categories, it is not
immediately clear whether that category would have high or low soil quality. The exception is code
243 (agriculture with natural vegetation); urbanization on this soil class is found mostly in Malta,
Bulgaria and Greece. For "bare" nature, a few classes probably have very low soil quality: 332 (bare
rock), 334 (burned areas) and 335 (permanently snow-covered). For Europe as a whole, this is less
than 1,000 hectares of land take increase in these categories.
The alternative analysis as described in 3.3.1 provides more insight into the relative value of soils
changed to (semi-)urban functions. This shows that indeed agricultural class 243 (agriculture with
natural planting) scores relatively high. Planted nature scores by far the best, as the most valuable
soil. After planted and unplanted nature, for example, urban green space remarkably scores
highest by far. Agriculture, on the other hand, scores relatively low on the composite ecosystem
services indicator: about the same as the urban area, landfills and construction sites. The categories
of industry, reclaimed land and infrastructure score the worst. Table 4 shows the results using the
SUPER classification.
Table 4
Gross land take increase Netherlands by use class in 2000-2018 in ha
Use class
Average sum*
Grade**
Urban area
245,4
5,6
Job sites (industry, business parks)
220,2
5,1
Infrastructure (including airports)
236,1
5,4
Reclamation (mining and quarrying).
221,9
5,1
Landfills
241,3
5,6
Construction sites
240,5
5,5
Urban green space and recreation
310,4
7,1
Agriculture
244,8
5,6
Nature - planted
434,4
10,0
Nature - bare
296,8
6,8
Water - marsh and water bodies
248,7
* Average sum is the total score on the 16 ecosystem services (on a scale of 0-1600)
** Figure is calculated as share of best scoring category (x10)
Source: CHA 2000-2018, own edit
5,7
This analysis should emphatically be considered a rough indication of soil quality, made in the
context of this quick scan. It requires further refinement and elaboration. Not all 16 maps are
(equally) relevant to soil quality and it is questionable how permissible the unweighted aggregation
of the maps is. Moreover, these results cannot be used for other European countries, because both
agriculture and nature are unique in the Netherlands and therefore incomparable with those in
other countries.
That said, the results are very striking and thus important for policy discussion. For example, if land
take were to count only for soil quality of a grade 6 or higher (the values used from the method in
Table 4), total Dutch additional land take in the period 2000-2018 would be negative. This is a
substantial difference from the quantitative approach. In addition, this analysis provides
substantiation for the removal of urban green space from the definition of land take and to
strongly downplay the contribution of agriculture to land take.
1.3.3 Sensitivity analysis definitions space occupation
Because there is so much uncertainty about the qualitative approach, a sensitivity analysis is
premature. It is questionable whether this approach will be included at all in the final definition of
land take; therefore, so far most attention has focused on the quantitative approach. But if a
decision is nevertheless made to include soil quality in monitoring and reporting the increase in
land take, there are two points of interest: (1) what indicators are used to determine soil quality
and (2) whether and how soil quality is weighed against acres of additional land take. These two
points are briefly elaborated below without empirical analysis.
Soil quality is both a technical issue and a political one. The normative aspect is about the question:
soil quality for whom? If the soil is (made) very fertile, this can be detrimental to certain
ecosystems: for different types of nature, a different chemical composition of the soil will be
beneficial. This fact alone makes our composite map from this quick scan insufficient for policy
practice: political choices must first be made and environmental expertise consulted to arrive at a
set of indicators. Probably the choice will also have to be area-specific, because which soil quality
needs the most protection will vary from place to place. Perhaps the indicators can also change as
new issues arise or need to be resolved over time. Finally, both the method of measurement and
the weighting of indicators will have to be part of the discussion.
The second issue concerns how soil quality information is used in the NNLT target. Above, the
extreme example of removing agriculture as a category from the definition of land take has been
mentioned, so that the Netherlands automatically meets the target. It is more prudent to apply
weighting. Occupying natural land can be "penalized" by making it count twice and agriculture by
half. And transformation from agriculture to urban green space can then be considered neutral or
positive. Such a key works out favorably for the Netherlands, which uses relatively little natural
land for urban functions while also developing a relatively large amount of urban green space.
1.4 Soil sealing analysis
Although not strictly the same as land take, the degree of land cover is also important when
discussing NNLT. In contrast to the quantitative approach, it is not about the function of the area,
but only about paving or construction. This basically means that one hectare of private garden in
the urban area, if unpaved, is equivalent to one hectare of arable land or natural area. Important in
calculating soil cover is scale. Only with high-resolution data can backyards or roads, for example,
be accurately measured.
As with the other calculations, there is a preference to work with global or European data. Several
files are available in this context. The recently made available World Settlement Footprint (WSF)
from Evolution of the European Space Agency (ESA) has the advantage that a time series from 1986
to 2015 is available. Also, the even more accurate WSF2019 file is available for that year.
Unfortunately, the periods do not quite match Corine so a comparison of equal periods is
impossible.
Figure 6
Soil sealing in Randstad (1986-1999 and 2000-2015)
According to the WSF Evolution data, 102,365 hectares of soil cover were added in the Netherlands
in the period 2000-2015 (a 28 percent increase in area compared to 1999), see Figure 6. If the soil
cover is taken over the entire stock period (1986-2015), the amount of hardening in the
Netherlands increased by 211,666 hectares, so the degree of cover was more or less the same for
both 15-year periods. This is also the case for many EU27 countries, with some outliers such as
Ireland, Poland and Slovakia where there was a lot of urban development after the turn of the
century. In addition to this analysis, a calculation was also made based on CBS data (BBG: Soil Use
File). This shows a soil cover increase between 2000 and 2017 of 50,081 hectares (this is 10 percent
of the area compared to 2000). There is a big difference between the results of the two files (WSF
Evolution and BBG): WSF is almost twice as much as BBG. The exact reason for this is beyond the
scope of this quick scan, but does indicate that the choice of a particular data file can have a great
deal of influence on the results.
1.5 Side notes and reflection
There has been criticism of the use of CLC data to measure space occupancy. A major problem is
the relatively low resolution. As a result, two types of errors occur: (1) areas designated as urban
but with little or no built-up area and (2) small-scale built-up areas not recorded as urban. The
ESPON SUPER project investigated these two types of errors by comparing the Corine-2012 map
with a much more accurate built-up map (Global Urban Footprint) (Van Schie et al. 2020); see
Figures 7 and 8.
Figure 7
Urban area registered in CLC with hardly any construction near Liège
Source: CLC2012, GUF2012
Figure 8
Buildings not recorded in CLC near Warsaw
Source: CLC2012, GUF2012
If Corine is used for follow-up analyses, wrong conclusions may be drawn. In Flanders, for example,
many provincial roads with occasional houses are designated as urban areas in Corine 2000. As a
result, further ribbon development in the 2000-2018 period is considered densification and not
land take or land take contrary to own observations and policy.
The delineation of areas in Corine is not only problematic for development. Renewable energy
production is also a tricky category. A wind turbine takes up relatively little space on the ground,
but needs surrounding infrastructure that may require paving of the soil. There is also no separate
category for solar arrays, which can affect soil quality. Sometimes nearby trees need to be cut
down or other vegetation removed, which can affect soil (quality). If in CLC an area is designated as
'energy production' then the (relatively broadly defined) area changes function; this helps explain
the significant transformation from nature to industry in the UK (Cole et al. 2022), see Figure 9.
Figure 9
CLC Delineation of a wind farm in England
Source: Cole et al., 2022
Another difficult category in CLC is greenhouse farming. Corine registers this as ordinary agriculture
(non-irrigated arable land - see Figure 10 where this is indicated by a light yellow color, but is
sometimes also registered as industrial land (purple)). But greenhouse farming certainly has urban
aspects in terms of soil; it is covered and often (partially) paved. According to Corine and the most
common definitions, replacing greenhouse horticulture with a recreational area or a villa district
would be labeled as additional land take. But according to the key figures, the minimum unpaved
area of greenhouse horticulture is only 10 percent while for a villa district it is as much as 75
percent and 95 percent for recreational landscape (Ruimte met Toekomst - Area Typification,
2022). While converting greenhouse horticulture to a villa district would be considered land take.
Figure 10
Greenhouse agriculture invisible in CLC at Municipality of Westland
Source: Corine2018 (left) and Google Maps (right)
Apart from the data source, general comments can be made about the accounting offsetting
between gross and net land take increase, because the original land take (greenhouse cultivation)
may have caused a destruction of the natural substrate. A change in function does not mean that
the soil has been returned to its original condition. In that respect, it is not "fair" to count land take
decrease as much.
The qualitative approach can also be reflected upon. The makeshift analysis in this quick scan study
shows that including soil quality can have major implications for determining land take increase .
Despite the fact that the qualitative approach comes closest to the spirit of the NNLT objective (not
affecting the soil), this has hardly been elaborated on as yet.
2
Sustainable urbanization
The goal of reducing land take to zero (NNLT) is a good example of a generic measure that does not
take into account local and regional circumstances. Areas where the pressure to build is high will be
most affected by this policy: halting additional land take is easier in a shrinking region than in a
growing one. To shed some light on this, below we relate land take to demographic pressure.
Land take increase per capita is often used as an indicator when describing sustainable
urbanization under SDG 11.3 (UN Habitat 2021). Only urban developments (land consumption) are
mentioned in the description of this target, so functions such as mining, landfills, recreation and so
on may not count. In addition to population development, we can also calculate household
development. This has more influence on the real demand for housing than people: in fact, there
may be a stable population but increasing number of households (due to divorces, fewer children,
for example) the so-called "household thinning" (Hamers 2020).
A major objection to linking urbanization sec to demographics is that much building is being
erected for other reasons (see Colsaet et al. (2018) for a review). After all, the increase in logistics
centers in the Netherlands has little to do with population development. Ideally, a split should be
made between residential areas (with demographic drivers) and employment areas (with economic
drivers). An analysis conducted as part of the ESPON SUPER project finds that it is very difficult to
explain the land take of work locations by economic indicators (Van Schie et al. 2020). For example,
an office tower has a huge number of jobs per hectare compared to a data center or a distribution
center. Moreover, much economic activity takes place within the urban area (urban fabric)
category that is usually understood as residential. For these reasons, we refrain from refining the
analysis with economic drivers - the relationship is too insignificant to warrant scientific analysis.
2.1 Dynamic land take analysis increase
When calculating sustainable urbanization, a dynamic "relative land take" indicator is sometimes
proposed: the percentage growth rate of land take divided by the percentage growth rate of
population. The idea is that if the number is less than one, then the land take is sustainable
(Schiavina et al. 2019, p. 5).
In the broad definition of land take, the Netherlands scores 1.71 in the most common definition of
sustainable urbanization (14 percent net land take increase divided by 8 percent population
growth), so not exactly sustainable. But the Netherlands is far from the only problematic country in
Europe in this regard. At the top of the list is Portugal whose population barely grew from 20002018 but where 15 percent additional urban area was added. Slovakia, Germany and Spain also
rank above the Netherlands. On the other side is Greece which had just slightly more urban growth
than the Netherlands but also had negative population growth at the same time: not exactly
sustainable. Among the most "sustainable" countries are Belgium, Luxembourg, Sweden and
Austria. As mentioned above in section 3.5, these figures are not entirely reliable because of the
under- and overestimation of urban area in small-scale developments (especially in Belgium). But if
the number of households is used, the picture can be quite different: the area of (semi-)urban
functions is growing (much) slower than the number of households.
Table 5
Dynamic land take growth in the Netherlands per person and household by definition
Definition of land take
%R/%∆bev
%R/%∆hh
Wide
1.71
0.91
- Urban greenery
1.50
0.80
- Urban greenery, artificial
1.46
0.77
- Urban green, artificial, construction site
0.56
0.30
0.49
0.26
- Urban green space, artificial, construction site, infrastructure
Source: CHA 2000-2018, EUROSTAT, own editing
The table above shows that per capita, only two definitions of land take (i.e., those that do not
include building sites) are sustainable. Indeed, according to the broad definition of land take, the
"excess" land take increase is almost twice what is considered sustainable. However, all householdlevel calculations do fall within the sustainability boundary: even under the broadest definition, the
two variables are more or less equal.
This analysis is consistent with the findings of a similar, global study of densities based on Global
Human Settlement Layer data (Li et al. 2022)data (Li et al. 2022). There it can be seen for the
Netherlands that the population in some large cities grew faster than built-up areas (densification)
while immediately outside the Randstad the opposite happened (thinning). Incidentally, this fits the
global trend: except in the major cities, the increase in land take is not sustainable (Li et al. 2022, p.
9).
This indicator does have the problem of path dependence. A metropolitan region that is densely
populated and grows 1 percent in area and population gets the same score (1) as a suburban region
with lots of building per capita that also grows by 1 percent While both areas score very differently
on a number of sustainability indicators.
2.2 Analysis relative land take increase
As an alternative to dynamic land take increase, Schiavina et al. (2019) recommend the indicator
the marginal land take increase (MLCNI). The table below presents a calculation of MLCNI for both
per capita and per household (the latter being a better predictor of housing demand). Thus, this
indicator (MLCNI) indicates the number of acres of land take added per new resident or household.
Table 6
Relative land take increase in the Netherlands per person and household by definition
Definition of land take
Per person
Per household
Wide
0.0485
0.0601
- Urban greenery
0.0425
0.0527
- Urban greenery, artificial
0.0413
0.0513
- Urban green, artificial, construction site
0.0159
0.0197
- Urban greenery, artificial, construction site, infrastructure
0.0139
0.0172
Source: CHA 2000-2018, EUROSTAT, own editing
Converted to square meters, this analysis shows that almost 500 square meters per new resident
and over 600 square meters per new household were added to urban area in the period 20002018. Again, the building land category makes the main difference: about 300 square meters of the
land take increase per new resident and 400 square meters per household is explained by this land
use category. In the narrowest definition (the one that excludes urban green space, artificial,
building land and infrastructure, or just residential and commercial areas), it is 138 square meters
of additional land take per new resident and 172 square meters per new household. It is important
to note that this is land take (footprint) that does not include stacked buildings.
It is again possible to compare the Netherlands with other EU countries, with the same caveat
about the CLC file. First of all, there are nine member states experiencing negative population
growth, making any additional land take in those countries inherently unsustainable. This
imbalance is greatest in Greece, Poland and Estonia. The Netherlands also performs reasonably
well in positive terms, with Portugal topping the list with a marginal land take increase of about 1
hectare (10,000 square meters) per new resident. Slovakia and Cyprus score twice as high as the
Netherlands. The most "efficient" countries are Malta, Belgium, Ireland and Austria.
In the ESPON SUPER project, a similar analysis was made at the regional level for Europe. There, the
urban area (as this concerns mostly residential areas) was compared to the European average (Van
Schie et al. 2020, p. 60). Most regions in the Netherlands are in the relatively efficient category of
above-average population growth and below-average urbanization.
Figure 11
Average urban area growth per person in European regions
Source: Van Schie et al., 2020, p. 60
2.3 Side notes and reflection
NNLT appears to be the same as sustainable urbanization but there are important differences
between the two perspectives. One is that sustainable urbanization is not an absolute value but an
aspiration within current conditions. For example, a relative indicator is used in SDG 11.3:
urbanization per capita. This has the advantage that shrinking and growing areas are not lumped
together. In this respect, this approach is more similar to the ladder of sustainable development in
the Netherlands than to the NNLT target (Evers & Blom 2016).
As with different conceptions and operationalizations of land take, this can be problematic. For
example, it is implicitly assumed that urbanization occurs to accommodate population growth, but
there are many more factors (Colsaet et al. 2018). Household development appears to be a better
predictor of housing demand. Many urban functions (such as job sites) have very different drivers.
Also, different calculation methods offer different outcomes and insights. As with land take, the
inaccuracies in CLC data can lead to wrong conclusions: for example, Belgium seems very efficient
because the population grows faster than the (incorrectly) observed urbanization. In short: the
dynamic or relative approach is also an obvious panacea.
A second difference between additional land take and sustainable urbanization is that the latter
leaves more solution space open. NNLT implies that urbanization an sich is not sustainable.
Sustainable urbanization involves optimal combinations of functions, knowing that there are all
kinds of trade-offs. Sometimes it can actually be sustainable to develop urban functions in order to
address certain challenges, think of the nitrogen debate, renewable energy and making the housing
stock more sustainable. Moreover, there are also sustainability disadvantages to compaction; soil is
just one of many factors involved.
3
Future land take
3.1 Analysis plan stock to 2030
Many (hard) plans for urban functions are currently in place. Some are already far advanced (e.g.,
an adopted zoning plan or an issued permit) while others are relatively "soft. Thus the question
arises to what extent those plans in the pipeline will lead to new land take. Assuming that hard
plans are likely to be realized around 2030, an analysis of these plans dovetails with the
expectation of a European obligation to report progress by 2030.
The website ruimtelijkeplannen.nl contains all adopted spatial policies and plans, but does not
provide information on preliminary phases of plan making. In the past, the initiative 'De Nieuwe
Kaart van Nederland' collected plans and intentions and continuously put them on the map (and
removed cancelled plans from the map). This initiative was terminated in 2010 for financial
reasons. In 2018 an attempt was made to compile a (New) New Map again (CRa 2018) but that file
is also no longer maintained. Currently, there is no national registry of soft plans; some provinces
such as North Holland have published this information, but others have not because of perceived
secrecy or that it is seen as too sensitive information, among other reasons. In addition, there is
little regularity in how proposed plans are reported.4 This makes it difficult to calculate future land
take in the medium term.
At this time, provinces have received so-called starter packages that contain various living
environment tasks (De Jonge 2022). Provinces are expected to have their "spatial 'puzzles' ready
during 2023. If that result is reported in a consistent way with so-called geo-information, it should
be possible to make a calculation of the spatial impact for the medium term. Such an analysis can
probably be made only during 2024 . Another technical possibility is to make an additional land
4 Sometimes plan data were provided with precise geographic information, sometimes only tabular
(number of dwellings within a municipality) without an indication of density and whether the plans
involve infill or expansion (additional land take).
take analysis of the known hard plans and supplement it with a Space Scanner simulation based on
the targets per province. However, that is beyond the scope of this quick scan.
3.2 European scenarios for 2050
As for the longer term, the Joint Research Centre (JRC) has developed the LUISA model that, among
other things, can be used to estimate future land use, including outputs on (net) urbanization and
urbanization per capita. For the period 2010-2050, the baseline scenario calculated the average
urbanization intensity at 1.6 square meters per person per year at the EU28 level, with Ireland,
Finland, Belgium, Cyprus, Luxembourg and Sweden as high outliers and Bulgaria, Germany, Latvia,
Croatia and Greece as low outliers (Kompil et al. 2015, p. 30). For the average resident, the
perceived population density (weighted population density) in 2010 was 70 persons per hectare
and 95 for metropolitan areas. According to modeling, these densities will decrease slightly by
2050, but with many spatial differences. For example, people in Spanish metropolitan regions (278
residents per hectare) will experience a decrease of about a third, but will still live in densities
among the highest in Europe. The Dutch live in densities around the EU average and, according to
model calculations, will live just slightly more spaciously in 2050.
In the ESPON SUPER project, the open source version of the LUISA model was used to calculate
three urbanization scenarios. These were intended to simulate the spatial distribution of the urban
area under various assumptions. Here it is possible to understand what kind of areas would be
urbanized under each scenario (Evers et al. 2021). Because the emphasis was placed on mapping
the possible urban form, the total land take increase was made very large (for the sake of visibility
on the map) and the variation in additional land take between scenarios was made small. For this
reason, they are not suitable for making ex-ante analyses of quantitative land take increase.
However, an analysis of qualitative land take increase (in the same way as in Section 3.2) should in
principle be possible, as the exact areas of additional land take are known. It should also be
technically possible to draw up new scenarios with different assumptions. These options are also
beyond the scope of this quick scan.
Figure 12
Impression of the urbanization scenarios in the ESPON SUPER project
Source: PBL
3.3 Dutch scenarios for 2050
In the PBL Spatial Explorations 2019 project, six 2050 scenarios for urbanization were developed
and published in the PBL report Grote opgaven in een beperkte ruimte (Hamers et al. 2021). The
variables of the urbanization scenarios run along two axes. The first concerns the demand for urban
functions. The second axis deals with location choices: densification in and building near larger
cities (Near), building near ov stops (Connected) and car-related building (Spacious). The scenarios
are thus very similar in content to those of the SUPER project but the implementation is more
realistic because they take into account the current plan stock, have a higher resolution and
assume a less extreme demand for urbanization. A drawback is that they are only available for the
Netherlands making a European comparison impossible.
3.3.1 Methods
To estimate the demand for urban functions in the future, the Space Scanner model used the
updated Welvaart en Leefomgeving (WLO) scenario study (CPB/PBL 2015, pp. 29-30). There, two
scenarios are described in which the development of the number of people, households and jobs is
calculated through to 2050 in a 'high' and a 'low' variant. In general, the greatest pressure for urban
functions is expected to occur in and around the Randstad and least in the border areas.
To calculate the quantitative land take increase, the output of the Spatial Scanner outputs by
summing the size of all new urban functions. A GIS is then used to look at the original function of
the urbanized area in the Corine2018 database to see which CLC class the land take falls into (e.g.
agriculture or nature).
3.3.2 Dutch land take in 2050
In the PBL urbanization scenarios, only new residential and commercial sites are modeled. Other
categories usually included in land take (infrastructure, reclamation, landfills, and urban green
space) are excluded. The output of the Space Scanner (see Table 7) is then similar to the narrowest
definition of land take.
Table 7
Additional land take in the Netherlands in 2050 by scenario
Scenario
Close to
Connected
Large
High
21.616
40.217
67.650
5.168
42.230
26.293
Low
Source: PBL
This table shows that the range is very wide both in terms of external pressure (high versus low)
and urbanization variance. There is more than a factor of 10 difference between extremes. Since
demand (low/high) cannot be effectively controlled through spatial planning, it is about the choice
of urban form (shown in the columns). There, too, the scenarios differ quite a bit: in the lowpressure scenario, Spacious has three times more land take increase than Near, while this
difference is five times greater in the high-pressure scenario.
The major differences become apparent when the original function is considered. Figure 13 shows
the number of hectares in which the function has changed in all scenarios (only agriculture and
nature count as land take). Thus it is clear that in Nearby there are still many housing and
employment areas being added, but mainly within the existing urban area. It is also striking how
little nature disappears in all scenarios. New land take occurs almost exclusively on agricultural
land: this also occurred in the 2000-2018 period, but the Netherlands does so exceptionally much
by European standards. It should be emphasized that these results were largely a conscious choice
within the scenario design: for example, in Near, the Space Scanner actively tries to find space in
the existing urban area, while this is not the case in Spacious. In any case, the main message of Big
tasks in a limited space also applies to future land use: there is much to choose from.
Figure 13
Source: PBL
3.4 Side notes and reflection
According to the National Environmental Vision, the Netherlands is on the eve of a major
transformation. Many functions will have to change between now and 2050 to provide a solution
for the major spatial tasks of our time. It seems inevitable that this will involve new land take. How
much land take there will be depends on the choices that are made now, for example about where
which housing locations are envisioned.
To support political decision-making, scenarios are an appropriate tool. They can provide direction
and insight into possible consequences of policy choices, but they are not predictions. Indeed, the
outcomes are largely embedded in the model inputs and serve as a basis for further discussion. For
example, both the SUPER scenarios and PBL's assume a situation where top-down control is
possible. Ultimately, planning decisions are political decisions where local factors play a major role
(Mazzoleni 2022).
4
Monitoring space occupation
Regardless of the exact details of the European Commission's proposal to introduce the no net land
take target, it is expected that there will be an obligation to monitor and report (change in) land
take (European Commission 2021b). In response, some member states have already established
monitoring systems, including France and Italy. Member States that already had their own national
targets (Flanders/Walloon, Germany, Luxembourg) have been monitoring for some time. The
question is what kind of monitoring system will (or should) be established at the European level
and to what extent the Netherlands is able to set up its own system to measure domestic land take.
4.1 Quantitative land take
An important issue when measuring quantitative land take is the data. For the sake of
comparability and verifiability, there should preferably be one data source for the whole of Europe.
At present, land take in Europe is mostly calculated using Corine data, including by the European
Environment Agency (EEA). On the other hand, there are a number of already known problems
with the Corine database . The main objection, elaborated in Section 3.4, is that the resolution is
too coarse to accurately observe small-scale urbanization. Because urbanization in the Netherlands
usually occurs through relatively large projects (large areas), the problem is less acute for the
Netherlands with Corine. GIS analyses performed as part of this study show that national land take
figures according to Corine and national (CBS) data do not differ much.5 But a European
comparison based on these data could be detrimental to the Netherlands.
Work is underway to improve the Corine2018 file by increasing the resolution (to 0.5 hectares) and
refining the classification (Cole et al. 2022, p. 22). A relevant change for land use monitoring
concerns the recreational area category: it is refined into built-up and unbuilt-up areas. In addition,
the division of urban area into four different density categories can help with land take monitoring,
especially in a qualitative sense (Rosina & Vizcaino-Martinez 2018). It seems that the European
Commission sees bread in such activities. The 2030 Soil Strategy states, "Enhance the use of digital
tools and Copernicus and rely on the JRC to further develop the European Soil Observatory (EUSO)
and the EEA to develop the Land Information System for Europe (LISE), supported by geospatial analytical products" (European Commission 2021b, p. 20).
There are several EU-coverage alternatives to Corine, but all have their own drawbacks. The Global
Urban Footprint (GUF) and World Settlement Footprint (WSF) provide accurate data on built-up
areas, for example. The Global Human Settlement Layer (GHSL) does distinguish between
residential and commercial areas (by linking to population density), but offers nothing else. Data
derived from the Sentinel-2 satellite with ten (mostly natural) land use classes are available in highresolution tiff files (10x10 meters). While the Urban Atlas and LUCAS sources both have higher
resolution than Corine and also contain many use classes, both do not cover the entire European
territory (Decoville & Schneider 2015). In addition, there are initiatives such as the Atlas of Urban
Expansion that randomly analyzes the urbanization of various urban areas for a variety of indicators
(Angel 2016).
National sources may be used for monitoring and reporting. The Soil Use File (BBG) is a digital map
by land use function of the Netherlands published by CBS. It shows the dominant land use function
at ground level. It uses a classification with 38 land-use categories (e.g. residential area, business
park and forest) which are in turn divided into nine main groups. For most categories, this uses a
lower limit of one hectare (sometimes 0.5 hectares) in terms of the degree of "contiguity. When
producing the BBG, various sources are used: the previous version of the BBG, aerial photos, BRT,
5 This does not necessarily mean that the data are the same, it may be that overestimates in one area
are offset by underestimates elsewhere; further research should confirm this.
Top25raster, BAG, ABR and Locatus (retail data). A so-called mutation series (years 1996, 2000,
2003, 2006, 2008, 2010, 2012, 2015, 2017) is also published by CBS for the purpose of comparisons
over longer periods.
The BBG is currently being updated. This will involve as much automation as possible using
available (open source) sources. The automation will also make it possible to increase the
frequency of publication. Because of the long lead time and set-up of a renewed BBG, a gap in the
BBG series of at least 5 years has currently arisen (the last BBG dates from 2017). This may pose a
problem for past land use analyses.
Other land use records in the Netherlands are:


Landelijk Grondgebruiksbestand Nederland (LGN): this is a (semi-)commercial file
produced by the WUR with an update frequency of 3 to 6 years. The emphasis is on rural
areas, nature and agriculture and then in particular on crop type. It consists of 48 land use
classes with a resolution of 5x5 meters. The file is created on the basis of the Basic
Registration of Plots (BRP) and the Basic Registration of Topography (BRT-Top10NL). The
urban area is virtually undifferentiated.
Basic Registration Topography (BRT): also called Top10NL from the Land Registry with an
update frequency of around two years (the ambition is to appear annually). This is
primarily a topographic file and not a land use file. The expansion of buildings can be
monitored well with it, but the classification into different classes is limited (a lot falls in
the class 'other').
In the Netherlands there is no data deficit but - as at the European level - there are choices to be
made in terms of accuracy, consistency through time and land use classes. Currently, there is no
formal land use monitor. This will have to be set up.
4.2 Qualitative land take
Monitoring qualitative land take is less straightforward, as there is so much ambiguity about
definition and operationalization, in addition to the choice yet to be made about whether and how
to combine this with quantitative land take. Here again, for the sake of comparability, it is good to
look at European sources first.
Work on a monitor for ecosystems in Europe has been underway since 2013. Two recent initiatives
are of interest: the Integrated system for Natural Capital and ecosystem services Accounting (INCA)
and the Mapping and Assessment of Ecosystems and their Services (MAES). A joint report on
possible methodologies and existing technical and political bottlenecks was published in 2018
(Maes et al. 2020). Currently, all member states are mapping their ecosystem services. A European
Soil Observatory has now been established and is in the process of setting up a monitoring system.
As with Corine's improvements, the ambition seems to be to make monitoring EU-wide. The mission of the ESO is to develop into: 'the principal provider of reference data and knowledge at EUlevel for all matters relating to soil' (Maréchal et al. 2022). This also in anticipation of the proposal
for a European soil health law in 2023, the same one that gives rise to this quick scan (European
Commission 2022).
National data sources may also be chosen. Which geographic information is then needed will
depend on further elaboration. It is not yet clear to what extent the necessary data are already
available. The degradation of soil quality is often calculated based on drought, reduction of
planting, erosion, salinization and carbon removal (Prăvălie et al. 2021) so these could be
requested indicators. In any case, the 16 ecosystem services maps are available that were also used
in this study. As discussed in Section 3.3, there is currently only information on the current
situation. This makes it possible to assess the impact of future land take, but not the evolution of
additional land take in the past.
4.3 Other points of interest
Setting up a space occupation monitoring system is technically possible. There are still many
unanswered questions and potential bottlenecks. Some are of a technical nature while others
involve more of a policy choice. In summary:
Data and expertise





It is recommended to ensure uniform and equal classification over time. Interim changes in
classification definitions make monitoring more complex and more difficult to compare
with previous monitoring years.
If national data sources are chosen, the update frequency must be taken into account.
Monitoring should not take place more frequently than data updates: if an indicator is
updated once every two years, there is little point in reporting annually. With composite
indicators with multiple update frequencies, this can become complex.
Working with composite indicators from multiple sources means a loss to the lowest
common denominator. If you average raster files from a higher resolution (to a lower
resolution), information will be lost. This happens because when averaging the file, the
pixels become larger and the number of pixels per square meter decreases. This makes the
image coarser and grainier, and small details that were visible on the original file are lost.
Some member states including the Netherlands have very high resolution data on, for
example, ecosystem services. As a result, editing this GIS data can be technically
challenging and require a lot of computing power.
A monitor requires the necessary substantive knowledge about both land use changes
(understanding increasing and decreasing land take) and GIS technical knowledge.
Preferably, this knowledge will have to be present within the same institute or group of
people.
Definitions






There needs to be clarity on some land uses that are not well defined in Corine. These are
sometimes difficult because they are temporary and/or multifunctional. These include
renewable energy production (wind farms and solar arrays), housing (private green space)
and agriculture (stables and greenhouse farming).
A choice must be made whether paving should also be calculated in land take. For
example, a distinction must be made between a fully built-up residential area and a
spacious residential area with lots of greenery between the houses. And whether nonurban buildings (e.g. glasshouses or livestock housing) should be included as land take.
Choices must be made about land take reduction (recultivation). It may take a long time to
recover soil. Is a change of function sufficient to consider the area non-urban?
A choice must be made about the extent to which soil quality should be part of the
monitor. This requires different data sources and clear choices about which indicators to
use and how to apply them.
What role does land reclamation (natural or otherwise) or coastal erosion play in
calculating additional land take? Does encroachment on (inland) water count as additional
land take, or does this only concern soil?
At what level of scale should NNLT take place? Is the goal to be achieved by each state, or
can land use increases in one country be offset by greening elsewhere? The same is true
within countries: should states, provinces or municipalities all pursue NNLT (as is often
done now with CO2 ) or not?
Organization and Policy



Land and soil have been a mandatory part of environmental impact assessments since
2014 but national practices differ (Vargas 2019). Is land use monitoring intended to bring
more unity to this?
Urban form is not taken into account in land take increases; only acres (quantitative
approach) or soil characteristics (qualitative approach) count. However, urban morphology
has many implications for related issues such as landscape fragmentation. Moreover, there
is a link here to sustainable urbanization.
Land use planning consists of several phases. For project decisions, the location has usually
already been determined. It is then recommended that land take increase be taken into
account at an earlier stage (for example, in the preparation of visions). Thus, it makes more
sense to conduct the environmental impact assessment at plan-mer level (SEA) rather than
mer level (EIA).