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Institutional causes of urban and rural sprawl in Switzerland
Land Use Policy 26 (2009) 919–924
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Land Use Policy journal homepage: www.elsevier.com/locate/landusepol
Institutional causes of urban and rural sprawl in Switzerland Stefan Mann ∗ Federal Research Station Agroscope Reckenholz Tänikon, Tänikon 8356, Ettenhausen, Switzerland
a r t i c l e
i n f o
Article history: Received 23 April 2008 Received in revised form 8 September 2008 Accepted 19 November 2008 Keywords: Urban sprawl Housing Rural development Settlement area Land degradation
a b s t r a c t Open space is a very scarce resource in Switzerland. The Federal Government aims to stabilize the use of settlement area per resident at 400 m2 . This paper starts by outlining the institutional system of spatial planning in Switzerland. Regressions then explain both the current level of land use per resident as well as the development of this indicator. Factors like cars per resident, the proportion of old people and the rural character of the municipality do increase land use per resident. Case studies show that there are currently hardly any instruments available with which to steer land use beyond the local level. It is concluded that incentives for local administrations should be introduced in order to limit urban and rural sprawl. © 2008 Elsevier Ltd. All rights reserved.
Introduction Where high population density and wealth come together, open space often becomes a scarce resource and upcoming construction projects start to appear as “urban sprawl” (Whyte, 1958; Clawson, 1962; Real Estate Research Corporation, 1974; Brueckner, 2000; Frenkel, 2004). This is the case in large parts of the United States, where the American Farmland Trust (2004, 2005) names 27 State and many more local “conservation easement programs” to regulate new housing activities. The problem is even more serious in Western Europe, where the average population density is above 100 persons/km2 and therefore three times the US level. In Switzerland a population density of 180 persons/km2 , large uninhabitable Alpine areas and an income level far above even the European average lead to a rapid aggravation of the problem. Rodewald (2007) estimates that 22% of all possible land for construction is already used for housing or traffic. This means that the housing and traffic sprawl is not restricted to urban areas any more, so that it seems appropriate to define something like “rural sprawl”. For want of a better term, this describes building activities in rural landscapes that degrade the scenic and/or environmental quality of the area (for similar issues, see Long et al., 2007). The stated objective of the Swiss Federal Government is to stabilize land use patterns. In 2002 (Schweizerischer Bundesrat, 2002), it was proposed to keep the current settlement area at about 400 m2 per head. Recent statistics completed for West-
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ern Switzerland indicate that the number there has grown from 400 m2 /head in the 1990s to 409 m2 /head now. It is therefore worthwhile analysing the factors which drive construction activities and developing suggestions on how to steer the process in a more effective way. This paper thus claims to bridge a gap between normative and descriptive research in the field of urban sprawl. Researchers who have analysed cases of farmland loss and urban sprawl have usually not spent a lot of effort developing suggestions on how to regulate urban sprawl (Levia, 1999; Arlt et al., 2003; Deilmann, 2004; Mei et al., 2005). On the other hand, economists suggesting marketbased instruments to reflect the scarcity of open space have rarely thought through their suggestions properly in terms of real-world conditions (Bizer, 1996; Weise, 2000; Meurer, 2001; Weber, 2001). In linking these two levels, the positive analysis starts by briefly outlining the institutional framework of building activities in Switzerland (The institutional framework of spatial development in Switzerland). In Method, the methodology for determining the main influencing factors of urban and rural sprawl is outlined. Quantitative results and case studies are presented in Results. Conclusions on how to adapt legal conditions for construction activities are developed in Conclusions. The institutional framework of spatial development in Switzerland Responsibilities relating to the development of new residential or industrial areas and traffic routes are clearly shared between the federal level, the 26 cantons as the most important regional entities, and municipal administrations.
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Federal law defines three important different categories of space. In construction zones, building activities are generally allowed as long as some architectural rules specific to the area are complied with. In agricultural zones, only farm buildings may be constructed. In the forest, no construction activities whatsoever are allowed. Federal law also defines the way zones can be converted. This is most difficult in the case of forests, which only may be cleared and converted to construction zones if there is no other chance of realizing the relevant project. In 1996 the Federal Government defined a quota of arable land (“crop rotation area”) to be maintained for each canton. This land may not, in general, be converted to construction zones after the canton reaches its defined minimum level. However, experience has shown that there are only a few cases where the status of crop rotation area has actually prevented construction projects (Bundesamt für Raumentwicklung, 2006). The cantonal administration has a duty to check the compliance of local development plans with cantonal and federal laws. They have to secure their quota of crop rotation areas and to check whether the conversion of (mostly) agricultural zones to construction zones is in accordance with the likely needs of the municipalities. The municipal administration is probably the most important decision maker for spatial development. Every 15–20 years the local development plan is revised by the municipal administration, whereas smaller municipalities usually prefer to consult a private planning bureau for the process of revision. The local development plan indicates where new construction zones are to be defined and how large the allotments in these areas are supposed to be. It should be mentioned that in the direct democratic system of Switzerland, signatures are currently collected for a so-called “landscape initiative”. Concerns about urban and rural sprawl has led the Foundation of Landscape Protection to demand that no additional construction zones be defined for 20 years to come. This may sound more radical than it is, because, as Rodewald (2007) shows, 27% of all the construction zones in Switzerland are not yet used. It is therefore realistic to assume that currently available construction zones could cope with considerable population growth. Method Two core questions of interest are both prone to quantitative analysis, one of them static and the other dynamic. The static question is why some municipalities use more settlement area per head than others. The dynamic question is why some of these municipalities manage to reduce the amount of settlement area per head over time, while other municipalities are rapidly expanding this figure. One of the difficulties in operationalizing these questions in empirical research is the organization of spatial statistics in Switzerland. The statistical office does not, strictly speaking, publish figures relating to land that is covered with buildings. Its categories of land use always include both sealed and open space, houses and gardens. Four different variables were therefore used in order to describe urban and rural sprawl. - The first dependent variable was residential building area per head, a figure only available for the old land use statistics. This variable is restricted to residential buildings and their gardens. Unfortunately, the new land use statistics do not publish this figure any more. - The second dependent variable, building area per head, comprises, in addition to residential building area, the land used for public buildings and agricultural buildings.
- The variable traffic area per head includes roads, railway area and airport areas. - The SUM variable only describes the sum of traffic and building area per resident. - The SETTLE variable describes the whole settlement area, including (in addition to building area and traffic area) industrial areas, construction zones and parks.
A large number of variables can be assumed to influence these dependent variables. Among them certainly is the geographical position of the municipality. The patterns of settlement will vary between peripheral and periurban regions. Fortunately, the Swiss Federal Office for Spatial Planning (ARE) has issued a classification for Swiss municipalities of which periurban is one, so that “Periurban” is used as one of the variables. It may also play a role whether residents in the community will only live or also work in this municipality, which can be measured along the share of commuters among working population. The degree of the municipality’s urbanization is estimated by an additional three variables. While the “Centre” variable describes the categorization by the Federal government as a central city, the “Inhab” variable describes the actual size in terms of residents of the municipality. In order to account for the existence of small municipalities in an urban region and with urban character, the share of single households is supposed to be an indicator for urban lifestyles. The ARE-classification as industrial municipality describes the influence of an industrial structure on settlement patterns. Since forests enjoy much stronger protection than agricultural land, it is reasonable to assume that municipalities classified as agricultural by the ARE and municipalities with a lot of agricultural land will be able to use more settlement area per head than municipalities in which forests dominate. It goes almost without saying that the share of holiday homes in a municipality will positively influence the amount of settlement area per resident, because the owners of second homes will usually use a considerable amount of land without being counted as residents. In addition, the ARE-classification of a tourist municipality will be a fair proxy for tourism intensity which, on the one hand, may influence land use through additional construction activities, while on the other hand preserving landscape may be an important quality factor. Three variables further describe the geographic position in the country. While the French part of Switzerland serves as reference, dummy variables describe the difference that the German-speaking and the Italian-speaking parts make in terms of land use intensity. Switzerland is a country with extreme differences in altitude, so that this variable serves to identify different land use patterns between valley and mountain regions. Cars also need space, be it streets, parking lots or garages. The number of cars per resident will therefore also be a predicting variable for the intensity of land use per resident, and another influencing variable could be demographics. It is reasonable to assume that people consume more space as they get older. People tend to move into bigger homes and do not necessarily reduce their space once their children have left the household. The proportion of young people and the proportion of old people are therefore both predicting variables for the amount of constructed land per resident. Table 1 describes the broad scale of both dependent and independent variables. It becomes clear that the scope of Swiss municipalities varies widely, both in terms of land use and in terms of sociodemographic characteristics. This large variance leaves a lot of room for causal relations influencing sprawl.
S. Mann / Land Use Policy 26 (2009) 919–924
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Table 1 Variable to measure and explain sprawl statically (1992/1997). Variable
Scale
Average 2
RES BUILD TRAFFIC SUM
Residential building area (m ) per resident Building area (m2 ) per resident Traffic area (m2 ) per resident Traffic plus building area (m2 ) per resident
Commute Periurban Centre Inhab Single Industry Farmland Farmcomm Forest Tourism Holiday German Ital Alti Car Young Old
Share of working residents outcommuting Classified as periurban community Central city = 1; other = 0 Number of inhabitants Single household share of total households Classified as industrial community Farmland share of municipality Classified as farm community Forest share of municipality Classified as tourism community Holiday home share of total homes German Swiss area = 1; other = 0 Italian Swiss area = 1; other = 0 Altitude of municipality (metres above sea level) Cars per resident Residential share of persons up to 20 years Residential share of persons from 65 years
101 361 116 477 0.57 0.28 0.001 4938 0.24 0.10 0.41 0.26 0.34 0.05 0.17 0.58 0.08 633 0.77 0.23 0.13
Minimum
Maximum
a
1,785 5,357 5,000 8,375
0 0 0 26 0 0 0 0 0 0 0 0 0 200 0.002 0.01 0.02
1 1 1 336,882 0.59 1 0.94 1 0.96 1 0.95 1 1 1947 2.92 0.60 0.86
0 0a 0a 71
Data source: Federal Office of Statistics, own calculations. a Figures available in hectares only, roundoff error.
It is one thing to explain differences between municipalities in the intensity of land use, but it is another to explain a different pace in expanding (or reducing) the use of land per inhabitant. Because the system of statistics has slightly changed, the dependent variables from Table 1 had to be partly adapted. While it was no longer possible to get information about residential buildings (RES), the SETTLE variable described the whole settlement area which included not only building and traffic areas, but also parks, industrial areas and special zones such as construction zones or dumpsites. Many variables which can be assumed to influence differences between regions, like the proportion of old people in a community, are not logically related to the speed with which urban and rural sprawl happens. While older people may need (or use) more space than young people, there is no reason why their demand for space, relative to younger people, should increase or decrease. However, two variables from Table 1 can well be imagined to spur or prevent urban and rural sprawl. If construction projects can easily be realized on farmland, but only with difficulty be realized on forest land, it is reasonable to assume that municipalities with a large share of farmland will be prone to urban sprawl to a greater degree than municipalities with a high share of forests. Table 2 with all the independent variables for the dynamic aspect of urban and rural sprawl therefore includes the variables Forest and Farmland. Table 2 contains only the 937 Swiss municipalities in the western part of the country for which the recent area statistics were available by late 2007. One other variable has been created to explain the development of land use: if a municipality loses inhabitants this will automati-
cally lead to a higher amount of settlement area per head. In order to maintain its settlement area per head the municipality would have to reconstruct part of the existing settlement area into agricultural land or forest; a practice that is – not only in Switzerland – almost non-existent. Municipalities with an influx of residents, however, have much more leeway to stabilize or even to reduce the amount of settlement area per head. The development of inhabitants therefore seems to be a fair predicting variable for the dynamic aspect of urban and rural sprawl. From the beginning of the study it appeared likely that the variables collected in Table 2 would only form a small part of the explanation for the speed of urban and rural sprawl. A large number of factors difficult to measure will also influence the decision to start construction projects in a community. These factors may include political processes, issues of land ownership or the availability of investors. In order to explore such soft issues of urban sprawl, it was decided to carry out some case studies. Municipalities were selected that showed a strong deviation from the results expected according to the regression analysis. Two municipalities, Gempenach and Tartegnin, were chosen because they reduced their settlement area per head considerably whereas the regression would have predicted a moderate increase. Two other municipalities, Concise and Bure, were chosen because their real increase in settlement area per head outpaced the predicted increase by far. It can be seen from Table 3 that the two groups of municipalities differed considerably: both the traffic and building area were much more modest (and remained so) in Gempenach and Tartegnin than in Concise and Bure, where this area expanded greatly.
Table 2 Variables to measure and explain sprawl dynamically. Variable SETTLE-dyn BUILD-dyn TRAFFIC-dyn Inhab-dyn Forest Farmland
Scale 2
m /resident (92/97–04/09) m2 /resident (92/97–04/09) m2 /resident (92/97–04/09) Rel. change residents 1997–2007 Forest share of municipality (92/97) Farmland share of municipality (92/97)
Data source: Federal Office of Statistics, own calculations.
Average
Minimum
Maximum
28.6 19.5 −0.7 0.092 0.30 0.50
−2143 −1028 −847 −0.35 0 0
9051 535 898 3.05 0.85 0.94
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S. Mann / Land Use Policy 26 (2009) 919–924
Table 3 Case study municipalities. Name
Residents 1997
Residents 2007
Settlement area per head 1997
Settlement area per head 2007
Gempenach Tartegnin
271 193
298 211
406 m2 415 m2
336 m2 332 m2
5 ha 5 ha
5 ha 5 ha
4 ha 2 ha
4 ha 2 ha
+47 +51
Concise Bure
675 704
713 684
919 m2 2074 m2
1402 m2 2661 m2
29 ha 97 ha
45 ha 106 ha
28 ha 31 ha
32 ha 41 ha
+73 +121
Case studies implied a visit to each selected municipality, an interview with a representative of either the local council or the administration, and a thorough inspection of the structure of the village. Other sources relating to the municipalities such as websites and development plans were also used. In addition, the cantonal administrations of Vaud (for Tartegnin and Concise), Jura (for Bure) and Fribourg (for Gempenach) were also visited. An interview with the person(s) in charge of spatial planning was conducted. Interviews on the local and cantonal level touched on similar issues, like the division of responsibilities or the narrative of the local planning process. The interviews were conducted in February and March 2008 and lasted 1–2 h each. Results Static analysis Table 4 displays very diverse results on the causes of urban and rural sprawl. Starting with the municipalities’ position with respect to cities, it does not play a large role how many persons commute to places outside the municipality. There is, however, a considerable influence of the periurban character of municipalities. Periurban municipalities seem to have a more careful approach to land use, particularly for traffic purposes. The three variables that indicate the level of urbanization create a complex picture. While it appears to be space-consuming to be a central city, it also becomes clear that urban attributes like a high number of inhabitants and a large share of single households both contribute to a decrease in the amount of building and, even more, in traffic area per resident. For every additional resident in a munic-
Traffic area 1997
Traffic area 2007
Building area 1997
Building area 2007
Predicted change (m2 /head)
ipality, the requirement of settlement area decreases by 1 dm2 per resident. Municipalities characterized by industry appear to be rather careful converting land to settlement areas. Concerning the different degrees of protection between farmland and forests, it can be confirmed that the agricultural character of a municipality encourages construction activities, particularly for residential purposes. A high share of forests in a municipality, however, has a very different impact, as should be expected from the previous section. It seems to slow down or even to prevent road and other traffic construction projects. The share of farmland has an ambivalent effect, slowing down traffic projects, but speeding up residential and other building. The high positive impact of holiday homes comes naturally from the definition of the dependent variables, because they use only residents as a denominator, not persons present in the village, while for holiday homes there is only space without a resident. This variable reminds us that it is, of course, extremely space-consuming if we switch between different homes. However, a touristy character of a municipality rather slows down building activities, probably because the value of open landscapes is a valuable asset. While, for our focus, the differences between the different parts of Switzerland are of lesser interest, the influence of altitude is not. It can be confirmed that in mountainous regions land use per resident is more extensive. This finding applies both to residential and to traffic projects. It is plausible because in densely populated valley regions space is scarcer so it is worthwhile conserving it more consciously. “Car” is a very illustrative variable as square metres and the OLS method are used. While both dependent and independent variables
Table 4 Results of explaining land use statically (n = 2891).
Commute Periurban Centre Inhab Single Industry Farmland Farmcommunity Forest Tourism Holiday German Ital Alti Car Young Old Constant R2 t-Values in parentheses. * p < 0.05. ** p < 0.01. *** p < 0.001.
RES
BUILD
TRAFFIC
SUM
−1.11 (−0.49) −8.13 (−2.05)* 159.97 (2.70)** −0.001 (−4.00)*** −46.68 (−1.69) −17.75 (−3.51)*** 52.35 (5.15)*** 7.88 (1.97)* −8.07 (−0.73) −56.11 (−6.90)*** 194.85 (14.20)*** 7.68 (2.42)* 15.02 (2.12)* 0.05 (6.17)*** 2.32 (0.33) 36.95 (1.05) 440.28 (13.75)*** −38.69 (−2.29)* 0.36
−5.58 (−0.80) −22.88 (−1.85) 643.68 (3.49)*** −0.005 (−5.55)*** −384.13 (−4.47)*** −11.56 (−0.73) 76.16 (2.41)** 19.50 (1.57) −51.00 (−1.49) −188.19 (−7.44)*** 664.48 (15.57)*** −47.10 (−4.77)*** −14.89 (−0.68) 0.06 (2.13)* 48.61 (2.23)* −201.10 (−1.84) 1154.46 (11.59)*** 265.36 (5.04)*** 0.35
−14.65 (−1.81) −59.10 (−4.13)*** 771.66 (3.61)*** −0.006 (−5.48)*** −353.13 (−3.55)*** −58.91 (−3.24)** −169.18 (−4.63)*** 52.59 (3.66)*** −240.00 (−6.05)*** −246.50 (−8.41)*** 294.79 (5.96)*** −4.63 (−0.41) −12.84 (−0.50) 0.34 (11.51)*** 82.26 (3.26)** −292.65 (−2.31)* 967.49 (8.39)*** 186.33 (3.05)** 0.33
−20.23 (−1.55) −81.97 (−3.55)*** 1415.34 (4.11)*** −0.01 (−6.37)*** −737.20 (−4.60)*** −70.47 (−2.40)* −93.02 (−1.58) 72.09 (3.11)** −291.00 (−4.55)*** −434.69 (−9.21)*** 959.18 (12.04)*** −51.72 (−2.80)** −27.73 (−0.67) 0.39 (8.28)*** 130.87 (3.22)** −493.75 (−2.42)* 2121.95 (11.41)*** 451.68 (4.60)*** 0.39
S. Mann / Land Use Policy 26 (2009) 919–924 Table 5 Results of explaining land use dynamically (n = 937).
Inhab-dyn Forest Farmland Constant R2
SETTLE-dyn
BUILD-dyn
TRAFFIC-dyn
−757 (−14.9) 185* (2.0) 187** (2.7) −52 (−0.9) 0.20
−317 (−38.8) 50** (3.4) 49** (4.4) 9 (0.9) 0.62
−288** (−27.4) 12 (0.6) 9 (0.7) 17 (1.4) 0.45
**
**
t-Values in parentheses. * p < 0.05. ** p < 0.01.
use resident as denominator, these cancel each other out. One car needs 174 additional square metres, of which two thirds consist of additional traffic space and one third of buildings (such as garages, multi-storey car parks, etc.). The demographics of a municipality obviously have a large impact on urban and rural sprawl. While young people apparently need slightly less land than others, people of 65 and over increase their land requirements considerably, equally distributed between building and traffic area. All factors taken together, they explain about one third of the variance in settlement area requirements per resident. While it is clear that soft factors play an important role, there are clear and quantifiable indicators that contribute to urban and rural sprawl. Dynamic analysis Table 5 confirms the hypothesis that the development of inhabitants is a good predictor for the development of settlement area per head. Clearly, however, there is little room for stagnating or even depopulating municipalities to reduce their settlement area per head. The t-value for the “Inhab-dyn” variable is therefore extraordinarily high. During the last 15 years there was apparently hardly any distinction between municipalities with a high forest share and municipalities with a high farmland share. Both types of municipality had more extensive construction activities than municipalities without a lot of farmland and forests. Having said this, it should be remembered that between 1995 and 2007 the amount of farmland in municipalities included in Table 5 shrank by 1.5% while the amount of forests grew by 0.2%. This means that the presence of forest may have enabled construction activities, but these activities did not take place in forests. The large differences in the quality of the regressions catch the eye. The patterns explaining the development in (public and residential) buildings can be much better explained than the development of settlement area per person altogether. It is plausible that the development of industrial zones, parks or dumpsites follows a lot of other patterns that are difficult to quantify. Case studies Each of the municipalities listed in Table 3 had its very own story of why the land use patterns deviated from what would have been expected according to the regressions. In Gempenach a construction site had been planned but had to be de-zoned because the area became a groundwater protection zone where no construction activities were allowed. However, the pressure to engage in construction activities remained limited since the municipality was situated in a rather peripheral area and since most residents, according to a survey, preferred a strategy of only modest growth. Given the rural character of the village, mention should be made of the high share of apartment buildings, which may be due to the limited income of most residents.
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Tartegnin is much more centrally located than Gempenach, being situated near Lake Geneva and between the cities of Geneva and Lausanne. However, most of the income in Tartegnin is generated by wine production and trading. Winegrowers make up the majority of the local council. Although they are usually also landowners and therefore potential beneficiaries of new construction activities, they resist such projects because they would undermine their own income source. One hectare of vineyard generates a much higher turnover than one hectare of arable land or grassland. The pressure is therefore great to preserve this land as a viable source of income. Similarly to Tartegnin, Concise is also centrally located on a lakeside. However, farming plays only a minor role in the village which is mainly inhabited by commuters to nearby towns. Among the main “land consumers” in this village are certainly public buildings. One large building hosts a sports hall and a public library which is open 6 h per week. It also used to contain the local administration, but recently a new building has been constructed to house the local administration and the local school. The local administration also receives a lot of calls from people interested in building detached houses and can only approve a few of them. The construction of generously sized detached houses is the main influencing factor for high land use in the peripheral community of Bure near the French border. The local administration has been requested once by the cantonal administration to restrict the plot size of detached houses, but argued that large plots would be the only reason for potential residents to choose Bure as a home location. One characteristic of the village is therefore large areas with thinly spread houses. Another factor that contributes to large requirements for space is a large military training area. The four villages visited have in common the fact that neither were any of the representatives informed about their own consumption level of settlement area per resident, nor did anybody know about the objective of stabilizing the settlement area per resident at 400 m2 . Local administrative representatives were, in general, critical of the large number of restrictions which the administration of a village has to handle. Sensitivity to the need to preserve open space was hardly traceable. In the cantonal administrations the situation was remarkably different. The representatives often felt somewhat torn between communal administrations with their desire for free expansion and the Federal administration with its critique of excessive land consumption and unnecessary construction zone declarations. In some cases the cantonal administration declared they wanted stronger instruments from Federal level in order to steer local developments. Conclusions Switzerland is in a situation with a high scarcity of open space. Under these circumstances it is likely that the optimum construction activities from a municipality point of view often does not match the optimum from a national point of view. From a national point of view, some construction projects that appear desirable for the residents of a municipality may inappropriately reduce the remaining open space. This gap was tackled when the Federal administration defined the objective of stabilizing settlement area per resident at around 400 m2 . However, there are hardly any instruments available to attain this objective. As long as enough farmland is available in a municipality, there is little to prevent the local administration from converting the land to a construction zone, a process that is usually highly profitable for the landowner. And nothing can then prevent the process of urban and rural sprawl within the defined construction zone, nor do any incentives exist to delay the process of zoning or the process of construction. Only if opportunity costs for the
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municipality itself are high, the consumption of land for settlement purposes is slowed down. This occurs through a high productivity of the open space, be it through touristy or through high-value agricultural uses. Incentives to account for the social cost of urban and rural sprawl on the national level, however, are urgently needed. These incentives should be directed towards local administrations, as they have a lot of leeway to save or to use their land. While economists, as cited above, have developed numerous systems for steering the process of spatial development by incentives and disincentives, it appears important also to take into account the motivation structure of local representatives. It appears likely that mounting public pressure will result in a system change with better preservation of open space. And it would increase the efficiency of this process if this system change were to lean more towards incentives and disincentives, particularly for rural municipalities, than towards restrictions. Acknowledgements I am grateful to my colleague Elvira Zingg for help in collecting the data and for discussions about the results of the study. The usual disclaimer applies. References American Farmland Trust, 2004. Fact Sheet—Status of Local PACE programs. Farmland Information Center, Washington. American Farmland Trust, 2005. Fact Sheet—Status of State PACE programs. Farmland Information Center, Washington. Arlt, G., Gössel, J., Heber, B., Hennersdorf, J., Lehmann, I., Thinh, N.X., 2003. Auswirkungen städtischer Nutzungsstrukturen auf Bodenversiegelung und Bodenpreis. IÖR-Schriften, Bd. 34. Dresden.
Bizer, K., 1996. Handelbare Flächenausweisungsrechte zur Lenkung der gemeindlichen Ausweisung von Siedlungs- und Verkehrsflächen. In: J. Köhn, M.J. Welfens: Neue (Eds.), Ansätze in der Umweltökonomie. Marburg: Metropolis. Brueckner, J.K., 2000. Urban sprawl: diagnosis and remedies. International Regional Science Review 23 (2), 160–171. Bundesamt für Raumentwicklung, 2006. Sachplan Fruchtfolgeflächen FFF, Vollzugshilfe 2006. Bern: ARE. Clawson, M., 1962. Urban sprawl and speculation in suburban land. Land Economics 38 (2), 99–111. Deilmann, C., 2004. Szenarien der Rohstoff- und Flächeninanspruchnahme für das Bauen und Wohnen 2025. Wissenschaftliche Zeitschrift der TU Dresden 53 (1–2). Frenkel, A., 2004. The potential effect of national growth-management policy on urban sprawl and the depletion of open spaces and farmland. Land Use policy 21 (4), 357–369. Levia, D.F., 1999. Farmland conversion and residential development in North Central Massachusetts. Land Degradation and Development 9 (2), 123–130. Long, H., Heilig, G.K., Li, X., Zhang, M., 2007. Socio-economic development and landuse change: analysis of rural housing land transition in the Transect of the Yangtse River, China. Land Use Policy 24 (1), 141–153. Mei, Y., XueRong, X., Xie, Y.C., Guangjin, T., 2005. Socioeconomic driving forces of arable land conversion: a case study of Wuxian City, China. Global Environmental Change 15 (3), 238–252. Meurer, P., 2001. Instrumente für eine nachhaltige Entwicklung von Flächennutzung. Peter Lang, Frankfurt. Real Estate Research Corporation, 1974. The Costs of Sprawl: Detailed Cost Analysis. Environmental Protection Agency, Washington. Rodewald, R., 2007. Die Landschaftsinitiative – die Antwort der Stiftung Landschaftsschutz Schweiz (SL) auf den “Fall Galmiz”. Blätter für Agrarrecht 41 (3), 231–238. Schweizerischer Bundesrat, 2002. Strategie Nachhaltige Entwicklung 2002. Bern. Weber, G., 2001. Schlechte Flächenbilanzen – was tun? Zum Stand der Bodenpolitik in Österreich. In Umweltbundesamt: Versiegelt Österreich? Der Flächenverbrauch und seine Eignung als Indikator für Umweltbeeinträchtigungen. Wien. Weise, P., 2000. Ökonomische Anreizinstrumente zur Vorhaltung ökologischer Flächenleistungen. In: K. Brake and U. Richter: Ökonomische Bewertung von Flächennutzung und Flächensteuerung. Kosten-Nutzen-Betrachtung und Instrumente zur Entlohnung ökologischer Leistungen als Lösungsansätze von Flächennutzungskonkurrenzen. Oldenburg. Whyte, W.H., 1958. The Exploding Metropolis. Doubleday, Garden City.
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Land Use Policy journal homepage: www.elsevier.com/locate/landusepol
Institutional causes of urban and rural sprawl in Switzerland Stefan Mann ∗ Federal Research Station Agroscope Reckenholz Tänikon, Tänikon 8356, Ettenhausen, Switzerland
a r t i c l e
i n f o
Article history: Received 23 April 2008 Received in revised form 8 September 2008 Accepted 19 November 2008 Keywords: Urban sprawl Housing Rural development Settlement area Land degradation
a b s t r a c t Open space is a very scarce resource in Switzerland. The Federal Government aims to stabilize the use of settlement area per resident at 400 m2 . This paper starts by outlining the institutional system of spatial planning in Switzerland. Regressions then explain both the current level of land use per resident as well as the development of this indicator. Factors like cars per resident, the proportion of old people and the rural character of the municipality do increase land use per resident. Case studies show that there are currently hardly any instruments available with which to steer land use beyond the local level. It is concluded that incentives for local administrations should be introduced in order to limit urban and rural sprawl. © 2008 Elsevier Ltd. All rights reserved.
Introduction Where high population density and wealth come together, open space often becomes a scarce resource and upcoming construction projects start to appear as “urban sprawl” (Whyte, 1958; Clawson, 1962; Real Estate Research Corporation, 1974; Brueckner, 2000; Frenkel, 2004). This is the case in large parts of the United States, where the American Farmland Trust (2004, 2005) names 27 State and many more local “conservation easement programs” to regulate new housing activities. The problem is even more serious in Western Europe, where the average population density is above 100 persons/km2 and therefore three times the US level. In Switzerland a population density of 180 persons/km2 , large uninhabitable Alpine areas and an income level far above even the European average lead to a rapid aggravation of the problem. Rodewald (2007) estimates that 22% of all possible land for construction is already used for housing or traffic. This means that the housing and traffic sprawl is not restricted to urban areas any more, so that it seems appropriate to define something like “rural sprawl”. For want of a better term, this describes building activities in rural landscapes that degrade the scenic and/or environmental quality of the area (for similar issues, see Long et al., 2007). The stated objective of the Swiss Federal Government is to stabilize land use patterns. In 2002 (Schweizerischer Bundesrat, 2002), it was proposed to keep the current settlement area at about 400 m2 per head. Recent statistics completed for West-
∗ Tel.: +41 52 368 32 38; fax: +41 52 365 11 90. E-mail address: [email protected]. 0264-8377/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.landusepol.2008.11.004
ern Switzerland indicate that the number there has grown from 400 m2 /head in the 1990s to 409 m2 /head now. It is therefore worthwhile analysing the factors which drive construction activities and developing suggestions on how to steer the process in a more effective way. This paper thus claims to bridge a gap between normative and descriptive research in the field of urban sprawl. Researchers who have analysed cases of farmland loss and urban sprawl have usually not spent a lot of effort developing suggestions on how to regulate urban sprawl (Levia, 1999; Arlt et al., 2003; Deilmann, 2004; Mei et al., 2005). On the other hand, economists suggesting marketbased instruments to reflect the scarcity of open space have rarely thought through their suggestions properly in terms of real-world conditions (Bizer, 1996; Weise, 2000; Meurer, 2001; Weber, 2001). In linking these two levels, the positive analysis starts by briefly outlining the institutional framework of building activities in Switzerland (The institutional framework of spatial development in Switzerland). In Method, the methodology for determining the main influencing factors of urban and rural sprawl is outlined. Quantitative results and case studies are presented in Results. Conclusions on how to adapt legal conditions for construction activities are developed in Conclusions. The institutional framework of spatial development in Switzerland Responsibilities relating to the development of new residential or industrial areas and traffic routes are clearly shared between the federal level, the 26 cantons as the most important regional entities, and municipal administrations.
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Federal law defines three important different categories of space. In construction zones, building activities are generally allowed as long as some architectural rules specific to the area are complied with. In agricultural zones, only farm buildings may be constructed. In the forest, no construction activities whatsoever are allowed. Federal law also defines the way zones can be converted. This is most difficult in the case of forests, which only may be cleared and converted to construction zones if there is no other chance of realizing the relevant project. In 1996 the Federal Government defined a quota of arable land (“crop rotation area”) to be maintained for each canton. This land may not, in general, be converted to construction zones after the canton reaches its defined minimum level. However, experience has shown that there are only a few cases where the status of crop rotation area has actually prevented construction projects (Bundesamt für Raumentwicklung, 2006). The cantonal administration has a duty to check the compliance of local development plans with cantonal and federal laws. They have to secure their quota of crop rotation areas and to check whether the conversion of (mostly) agricultural zones to construction zones is in accordance with the likely needs of the municipalities. The municipal administration is probably the most important decision maker for spatial development. Every 15–20 years the local development plan is revised by the municipal administration, whereas smaller municipalities usually prefer to consult a private planning bureau for the process of revision. The local development plan indicates where new construction zones are to be defined and how large the allotments in these areas are supposed to be. It should be mentioned that in the direct democratic system of Switzerland, signatures are currently collected for a so-called “landscape initiative”. Concerns about urban and rural sprawl has led the Foundation of Landscape Protection to demand that no additional construction zones be defined for 20 years to come. This may sound more radical than it is, because, as Rodewald (2007) shows, 27% of all the construction zones in Switzerland are not yet used. It is therefore realistic to assume that currently available construction zones could cope with considerable population growth. Method Two core questions of interest are both prone to quantitative analysis, one of them static and the other dynamic. The static question is why some municipalities use more settlement area per head than others. The dynamic question is why some of these municipalities manage to reduce the amount of settlement area per head over time, while other municipalities are rapidly expanding this figure. One of the difficulties in operationalizing these questions in empirical research is the organization of spatial statistics in Switzerland. The statistical office does not, strictly speaking, publish figures relating to land that is covered with buildings. Its categories of land use always include both sealed and open space, houses and gardens. Four different variables were therefore used in order to describe urban and rural sprawl. - The first dependent variable was residential building area per head, a figure only available for the old land use statistics. This variable is restricted to residential buildings and their gardens. Unfortunately, the new land use statistics do not publish this figure any more. - The second dependent variable, building area per head, comprises, in addition to residential building area, the land used for public buildings and agricultural buildings.
- The variable traffic area per head includes roads, railway area and airport areas. - The SUM variable only describes the sum of traffic and building area per resident. - The SETTLE variable describes the whole settlement area, including (in addition to building area and traffic area) industrial areas, construction zones and parks.
A large number of variables can be assumed to influence these dependent variables. Among them certainly is the geographical position of the municipality. The patterns of settlement will vary between peripheral and periurban regions. Fortunately, the Swiss Federal Office for Spatial Planning (ARE) has issued a classification for Swiss municipalities of which periurban is one, so that “Periurban” is used as one of the variables. It may also play a role whether residents in the community will only live or also work in this municipality, which can be measured along the share of commuters among working population. The degree of the municipality’s urbanization is estimated by an additional three variables. While the “Centre” variable describes the categorization by the Federal government as a central city, the “Inhab” variable describes the actual size in terms of residents of the municipality. In order to account for the existence of small municipalities in an urban region and with urban character, the share of single households is supposed to be an indicator for urban lifestyles. The ARE-classification as industrial municipality describes the influence of an industrial structure on settlement patterns. Since forests enjoy much stronger protection than agricultural land, it is reasonable to assume that municipalities classified as agricultural by the ARE and municipalities with a lot of agricultural land will be able to use more settlement area per head than municipalities in which forests dominate. It goes almost without saying that the share of holiday homes in a municipality will positively influence the amount of settlement area per resident, because the owners of second homes will usually use a considerable amount of land without being counted as residents. In addition, the ARE-classification of a tourist municipality will be a fair proxy for tourism intensity which, on the one hand, may influence land use through additional construction activities, while on the other hand preserving landscape may be an important quality factor. Three variables further describe the geographic position in the country. While the French part of Switzerland serves as reference, dummy variables describe the difference that the German-speaking and the Italian-speaking parts make in terms of land use intensity. Switzerland is a country with extreme differences in altitude, so that this variable serves to identify different land use patterns between valley and mountain regions. Cars also need space, be it streets, parking lots or garages. The number of cars per resident will therefore also be a predicting variable for the intensity of land use per resident, and another influencing variable could be demographics. It is reasonable to assume that people consume more space as they get older. People tend to move into bigger homes and do not necessarily reduce their space once their children have left the household. The proportion of young people and the proportion of old people are therefore both predicting variables for the amount of constructed land per resident. Table 1 describes the broad scale of both dependent and independent variables. It becomes clear that the scope of Swiss municipalities varies widely, both in terms of land use and in terms of sociodemographic characteristics. This large variance leaves a lot of room for causal relations influencing sprawl.
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Table 1 Variable to measure and explain sprawl statically (1992/1997). Variable
Scale
Average 2
RES BUILD TRAFFIC SUM
Residential building area (m ) per resident Building area (m2 ) per resident Traffic area (m2 ) per resident Traffic plus building area (m2 ) per resident
Commute Periurban Centre Inhab Single Industry Farmland Farmcomm Forest Tourism Holiday German Ital Alti Car Young Old
Share of working residents outcommuting Classified as periurban community Central city = 1; other = 0 Number of inhabitants Single household share of total households Classified as industrial community Farmland share of municipality Classified as farm community Forest share of municipality Classified as tourism community Holiday home share of total homes German Swiss area = 1; other = 0 Italian Swiss area = 1; other = 0 Altitude of municipality (metres above sea level) Cars per resident Residential share of persons up to 20 years Residential share of persons from 65 years
101 361 116 477 0.57 0.28 0.001 4938 0.24 0.10 0.41 0.26 0.34 0.05 0.17 0.58 0.08 633 0.77 0.23 0.13
Minimum
Maximum
a
1,785 5,357 5,000 8,375
0 0 0 26 0 0 0 0 0 0 0 0 0 200 0.002 0.01 0.02
1 1 1 336,882 0.59 1 0.94 1 0.96 1 0.95 1 1 1947 2.92 0.60 0.86
0 0a 0a 71
Data source: Federal Office of Statistics, own calculations. a Figures available in hectares only, roundoff error.
It is one thing to explain differences between municipalities in the intensity of land use, but it is another to explain a different pace in expanding (or reducing) the use of land per inhabitant. Because the system of statistics has slightly changed, the dependent variables from Table 1 had to be partly adapted. While it was no longer possible to get information about residential buildings (RES), the SETTLE variable described the whole settlement area which included not only building and traffic areas, but also parks, industrial areas and special zones such as construction zones or dumpsites. Many variables which can be assumed to influence differences between regions, like the proportion of old people in a community, are not logically related to the speed with which urban and rural sprawl happens. While older people may need (or use) more space than young people, there is no reason why their demand for space, relative to younger people, should increase or decrease. However, two variables from Table 1 can well be imagined to spur or prevent urban and rural sprawl. If construction projects can easily be realized on farmland, but only with difficulty be realized on forest land, it is reasonable to assume that municipalities with a large share of farmland will be prone to urban sprawl to a greater degree than municipalities with a high share of forests. Table 2 with all the independent variables for the dynamic aspect of urban and rural sprawl therefore includes the variables Forest and Farmland. Table 2 contains only the 937 Swiss municipalities in the western part of the country for which the recent area statistics were available by late 2007. One other variable has been created to explain the development of land use: if a municipality loses inhabitants this will automati-
cally lead to a higher amount of settlement area per head. In order to maintain its settlement area per head the municipality would have to reconstruct part of the existing settlement area into agricultural land or forest; a practice that is – not only in Switzerland – almost non-existent. Municipalities with an influx of residents, however, have much more leeway to stabilize or even to reduce the amount of settlement area per head. The development of inhabitants therefore seems to be a fair predicting variable for the dynamic aspect of urban and rural sprawl. From the beginning of the study it appeared likely that the variables collected in Table 2 would only form a small part of the explanation for the speed of urban and rural sprawl. A large number of factors difficult to measure will also influence the decision to start construction projects in a community. These factors may include political processes, issues of land ownership or the availability of investors. In order to explore such soft issues of urban sprawl, it was decided to carry out some case studies. Municipalities were selected that showed a strong deviation from the results expected according to the regression analysis. Two municipalities, Gempenach and Tartegnin, were chosen because they reduced their settlement area per head considerably whereas the regression would have predicted a moderate increase. Two other municipalities, Concise and Bure, were chosen because their real increase in settlement area per head outpaced the predicted increase by far. It can be seen from Table 3 that the two groups of municipalities differed considerably: both the traffic and building area were much more modest (and remained so) in Gempenach and Tartegnin than in Concise and Bure, where this area expanded greatly.
Table 2 Variables to measure and explain sprawl dynamically. Variable SETTLE-dyn BUILD-dyn TRAFFIC-dyn Inhab-dyn Forest Farmland
Scale 2
m /resident (92/97–04/09) m2 /resident (92/97–04/09) m2 /resident (92/97–04/09) Rel. change residents 1997–2007 Forest share of municipality (92/97) Farmland share of municipality (92/97)
Data source: Federal Office of Statistics, own calculations.
Average
Minimum
Maximum
28.6 19.5 −0.7 0.092 0.30 0.50
−2143 −1028 −847 −0.35 0 0
9051 535 898 3.05 0.85 0.94
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Table 3 Case study municipalities. Name
Residents 1997
Residents 2007
Settlement area per head 1997
Settlement area per head 2007
Gempenach Tartegnin
271 193
298 211
406 m2 415 m2
336 m2 332 m2
5 ha 5 ha
5 ha 5 ha
4 ha 2 ha
4 ha 2 ha
+47 +51
Concise Bure
675 704
713 684
919 m2 2074 m2
1402 m2 2661 m2
29 ha 97 ha
45 ha 106 ha
28 ha 31 ha
32 ha 41 ha
+73 +121
Case studies implied a visit to each selected municipality, an interview with a representative of either the local council or the administration, and a thorough inspection of the structure of the village. Other sources relating to the municipalities such as websites and development plans were also used. In addition, the cantonal administrations of Vaud (for Tartegnin and Concise), Jura (for Bure) and Fribourg (for Gempenach) were also visited. An interview with the person(s) in charge of spatial planning was conducted. Interviews on the local and cantonal level touched on similar issues, like the division of responsibilities or the narrative of the local planning process. The interviews were conducted in February and March 2008 and lasted 1–2 h each. Results Static analysis Table 4 displays very diverse results on the causes of urban and rural sprawl. Starting with the municipalities’ position with respect to cities, it does not play a large role how many persons commute to places outside the municipality. There is, however, a considerable influence of the periurban character of municipalities. Periurban municipalities seem to have a more careful approach to land use, particularly for traffic purposes. The three variables that indicate the level of urbanization create a complex picture. While it appears to be space-consuming to be a central city, it also becomes clear that urban attributes like a high number of inhabitants and a large share of single households both contribute to a decrease in the amount of building and, even more, in traffic area per resident. For every additional resident in a munic-
Traffic area 1997
Traffic area 2007
Building area 1997
Building area 2007
Predicted change (m2 /head)
ipality, the requirement of settlement area decreases by 1 dm2 per resident. Municipalities characterized by industry appear to be rather careful converting land to settlement areas. Concerning the different degrees of protection between farmland and forests, it can be confirmed that the agricultural character of a municipality encourages construction activities, particularly for residential purposes. A high share of forests in a municipality, however, has a very different impact, as should be expected from the previous section. It seems to slow down or even to prevent road and other traffic construction projects. The share of farmland has an ambivalent effect, slowing down traffic projects, but speeding up residential and other building. The high positive impact of holiday homes comes naturally from the definition of the dependent variables, because they use only residents as a denominator, not persons present in the village, while for holiday homes there is only space without a resident. This variable reminds us that it is, of course, extremely space-consuming if we switch between different homes. However, a touristy character of a municipality rather slows down building activities, probably because the value of open landscapes is a valuable asset. While, for our focus, the differences between the different parts of Switzerland are of lesser interest, the influence of altitude is not. It can be confirmed that in mountainous regions land use per resident is more extensive. This finding applies both to residential and to traffic projects. It is plausible because in densely populated valley regions space is scarcer so it is worthwhile conserving it more consciously. “Car” is a very illustrative variable as square metres and the OLS method are used. While both dependent and independent variables
Table 4 Results of explaining land use statically (n = 2891).
Commute Periurban Centre Inhab Single Industry Farmland Farmcommunity Forest Tourism Holiday German Ital Alti Car Young Old Constant R2 t-Values in parentheses. * p < 0.05. ** p < 0.01. *** p < 0.001.
RES
BUILD
TRAFFIC
SUM
−1.11 (−0.49) −8.13 (−2.05)* 159.97 (2.70)** −0.001 (−4.00)*** −46.68 (−1.69) −17.75 (−3.51)*** 52.35 (5.15)*** 7.88 (1.97)* −8.07 (−0.73) −56.11 (−6.90)*** 194.85 (14.20)*** 7.68 (2.42)* 15.02 (2.12)* 0.05 (6.17)*** 2.32 (0.33) 36.95 (1.05) 440.28 (13.75)*** −38.69 (−2.29)* 0.36
−5.58 (−0.80) −22.88 (−1.85) 643.68 (3.49)*** −0.005 (−5.55)*** −384.13 (−4.47)*** −11.56 (−0.73) 76.16 (2.41)** 19.50 (1.57) −51.00 (−1.49) −188.19 (−7.44)*** 664.48 (15.57)*** −47.10 (−4.77)*** −14.89 (−0.68) 0.06 (2.13)* 48.61 (2.23)* −201.10 (−1.84) 1154.46 (11.59)*** 265.36 (5.04)*** 0.35
−14.65 (−1.81) −59.10 (−4.13)*** 771.66 (3.61)*** −0.006 (−5.48)*** −353.13 (−3.55)*** −58.91 (−3.24)** −169.18 (−4.63)*** 52.59 (3.66)*** −240.00 (−6.05)*** −246.50 (−8.41)*** 294.79 (5.96)*** −4.63 (−0.41) −12.84 (−0.50) 0.34 (11.51)*** 82.26 (3.26)** −292.65 (−2.31)* 967.49 (8.39)*** 186.33 (3.05)** 0.33
−20.23 (−1.55) −81.97 (−3.55)*** 1415.34 (4.11)*** −0.01 (−6.37)*** −737.20 (−4.60)*** −70.47 (−2.40)* −93.02 (−1.58) 72.09 (3.11)** −291.00 (−4.55)*** −434.69 (−9.21)*** 959.18 (12.04)*** −51.72 (−2.80)** −27.73 (−0.67) 0.39 (8.28)*** 130.87 (3.22)** −493.75 (−2.42)* 2121.95 (11.41)*** 451.68 (4.60)*** 0.39
S. Mann / Land Use Policy 26 (2009) 919–924 Table 5 Results of explaining land use dynamically (n = 937).
Inhab-dyn Forest Farmland Constant R2
SETTLE-dyn
BUILD-dyn
TRAFFIC-dyn
−757 (−14.9) 185* (2.0) 187** (2.7) −52 (−0.9) 0.20
−317 (−38.8) 50** (3.4) 49** (4.4) 9 (0.9) 0.62
−288** (−27.4) 12 (0.6) 9 (0.7) 17 (1.4) 0.45
**
**
t-Values in parentheses. * p < 0.05. ** p < 0.01.
use resident as denominator, these cancel each other out. One car needs 174 additional square metres, of which two thirds consist of additional traffic space and one third of buildings (such as garages, multi-storey car parks, etc.). The demographics of a municipality obviously have a large impact on urban and rural sprawl. While young people apparently need slightly less land than others, people of 65 and over increase their land requirements considerably, equally distributed between building and traffic area. All factors taken together, they explain about one third of the variance in settlement area requirements per resident. While it is clear that soft factors play an important role, there are clear and quantifiable indicators that contribute to urban and rural sprawl. Dynamic analysis Table 5 confirms the hypothesis that the development of inhabitants is a good predictor for the development of settlement area per head. Clearly, however, there is little room for stagnating or even depopulating municipalities to reduce their settlement area per head. The t-value for the “Inhab-dyn” variable is therefore extraordinarily high. During the last 15 years there was apparently hardly any distinction between municipalities with a high forest share and municipalities with a high farmland share. Both types of municipality had more extensive construction activities than municipalities without a lot of farmland and forests. Having said this, it should be remembered that between 1995 and 2007 the amount of farmland in municipalities included in Table 5 shrank by 1.5% while the amount of forests grew by 0.2%. This means that the presence of forest may have enabled construction activities, but these activities did not take place in forests. The large differences in the quality of the regressions catch the eye. The patterns explaining the development in (public and residential) buildings can be much better explained than the development of settlement area per person altogether. It is plausible that the development of industrial zones, parks or dumpsites follows a lot of other patterns that are difficult to quantify. Case studies Each of the municipalities listed in Table 3 had its very own story of why the land use patterns deviated from what would have been expected according to the regressions. In Gempenach a construction site had been planned but had to be de-zoned because the area became a groundwater protection zone where no construction activities were allowed. However, the pressure to engage in construction activities remained limited since the municipality was situated in a rather peripheral area and since most residents, according to a survey, preferred a strategy of only modest growth. Given the rural character of the village, mention should be made of the high share of apartment buildings, which may be due to the limited income of most residents.
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Tartegnin is much more centrally located than Gempenach, being situated near Lake Geneva and between the cities of Geneva and Lausanne. However, most of the income in Tartegnin is generated by wine production and trading. Winegrowers make up the majority of the local council. Although they are usually also landowners and therefore potential beneficiaries of new construction activities, they resist such projects because they would undermine their own income source. One hectare of vineyard generates a much higher turnover than one hectare of arable land or grassland. The pressure is therefore great to preserve this land as a viable source of income. Similarly to Tartegnin, Concise is also centrally located on a lakeside. However, farming plays only a minor role in the village which is mainly inhabited by commuters to nearby towns. Among the main “land consumers” in this village are certainly public buildings. One large building hosts a sports hall and a public library which is open 6 h per week. It also used to contain the local administration, but recently a new building has been constructed to house the local administration and the local school. The local administration also receives a lot of calls from people interested in building detached houses and can only approve a few of them. The construction of generously sized detached houses is the main influencing factor for high land use in the peripheral community of Bure near the French border. The local administration has been requested once by the cantonal administration to restrict the plot size of detached houses, but argued that large plots would be the only reason for potential residents to choose Bure as a home location. One characteristic of the village is therefore large areas with thinly spread houses. Another factor that contributes to large requirements for space is a large military training area. The four villages visited have in common the fact that neither were any of the representatives informed about their own consumption level of settlement area per resident, nor did anybody know about the objective of stabilizing the settlement area per resident at 400 m2 . Local administrative representatives were, in general, critical of the large number of restrictions which the administration of a village has to handle. Sensitivity to the need to preserve open space was hardly traceable. In the cantonal administrations the situation was remarkably different. The representatives often felt somewhat torn between communal administrations with their desire for free expansion and the Federal administration with its critique of excessive land consumption and unnecessary construction zone declarations. In some cases the cantonal administration declared they wanted stronger instruments from Federal level in order to steer local developments. Conclusions Switzerland is in a situation with a high scarcity of open space. Under these circumstances it is likely that the optimum construction activities from a municipality point of view often does not match the optimum from a national point of view. From a national point of view, some construction projects that appear desirable for the residents of a municipality may inappropriately reduce the remaining open space. This gap was tackled when the Federal administration defined the objective of stabilizing settlement area per resident at around 400 m2 . However, there are hardly any instruments available to attain this objective. As long as enough farmland is available in a municipality, there is little to prevent the local administration from converting the land to a construction zone, a process that is usually highly profitable for the landowner. And nothing can then prevent the process of urban and rural sprawl within the defined construction zone, nor do any incentives exist to delay the process of zoning or the process of construction. Only if opportunity costs for the
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municipality itself are high, the consumption of land for settlement purposes is slowed down. This occurs through a high productivity of the open space, be it through touristy or through high-value agricultural uses. Incentives to account for the social cost of urban and rural sprawl on the national level, however, are urgently needed. These incentives should be directed towards local administrations, as they have a lot of leeway to save or to use their land. While economists, as cited above, have developed numerous systems for steering the process of spatial development by incentives and disincentives, it appears important also to take into account the motivation structure of local representatives. It appears likely that mounting public pressure will result in a system change with better preservation of open space. And it would increase the efficiency of this process if this system change were to lean more towards incentives and disincentives, particularly for rural municipalities, than towards restrictions. Acknowledgements I am grateful to my colleague Elvira Zingg for help in collecting the data and for discussions about the results of the study. The usual disclaimer applies. References American Farmland Trust, 2004. Fact Sheet—Status of Local PACE programs. Farmland Information Center, Washington. American Farmland Trust, 2005. Fact Sheet—Status of State PACE programs. Farmland Information Center, Washington. Arlt, G., Gössel, J., Heber, B., Hennersdorf, J., Lehmann, I., Thinh, N.X., 2003. Auswirkungen städtischer Nutzungsstrukturen auf Bodenversiegelung und Bodenpreis. IÖR-Schriften, Bd. 34. Dresden.
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