The study was conducted through a German Federal Ministry for the Environment pilot project commissioned by the Federal Agency for Nature Conservation. It applies a national life-satisfaction model to the “visual amenity services” of urban ecosystems, defined in the UN System of Environmental-Economic Accounting as ecosystem contributions to local living conditions through sensory benefits, especially those provided by seeing natural features. The analysis considers only publicly accessible green space near residences. It estimates a hypothetical price for access, allowing the benefits of nearby green to be compared with alternative uses of urban land.

Its empirical foundation is a life-satisfaction analysis by Krekel and colleagues based on approximately 42,000 records from Germany’s Socio-Economic Panel for 2000–2012. Respondents rated their life satisfaction on a scale from 0 to 10, while the analysis also considered age, gender, marital status, health, education and income. The proportion of publicly accessible green space within a one-kilometre radius of each respondent’s home was included in a multicriteria regression. The estimated increase in life satisfaction associated with more green space was compared with the income increase associated with the same reported improvement, yielding an estimated marginal willingness to pay for an additional hectare.

The researchers distinguish the study’s life-satisfaction method from hedonic pricing analysis, which derives preferences for amenities from property-price differences. A comparison of two German studies using the same general one-kilometre green-space indicator found that hedonic estimates were only about one thirty-eighth to one one-hundred-and-twenty-fourth of the life-satisfaction estimates. A market-simulation model suggested that features of real-estate markets—including incomplete information, high transaction costs, short-term constraints on supply and equity preferences—may cause property prices to capture only part of green space’s association with life satisfaction. The present study therefore uses the Life Satisfaction Method, classified within the accounting framework as a simulated exchange-value approach.

For the national extrapolation, the researchers replaced the 2006 European Urban Atlas data used in the original analysis with the ATKIS Basis-DLM geodata in the IOER Monitor version. This dataset covers all of Germany rather than only its most urbanised regions and can use more precise cadastral information in settlements. The green-space measure includes woody vegetation, woodland, meadow and pasture, parks and other publicly accessible green space, sports, leisure and recreation areas, and cemeteries. This broader definition includes forests and agricultural grassland near settlements that were absent from the earlier Urban Atlas category. Population distribution came from the 2011 census, represented in 100-by-100-metre grid cells containing more than three residents, while the 2012 version of the land data was selected to keep the spatial inputs close in time to the life-satisfaction and census data.

Because both the land database and green-space definition had changed, the original marginal-utility function required adjustment before national extrapolation. The researchers first transformed it linearly to accommodate the higher average green-space supply per person produced by ATKIS data and the additional land classes. They then calibrated it so that an Urban Atlas calculation using the original function and an ATKIS calculation using the adjusted function produced the same total monetary value for the same area. This required reducing the slope of the fitted function. The valid nationwide monetary results come from a two-by-two-kilometre grid analysis; monetary results from a previously published, more detailed 100-by-100-metre analysis were found to be incorrect.

The model reports two different monetary concepts. Accounting-compatible exchange value is the simulated price of an additional, or “last,” unit of green space multiplied by the total area available to a household. Welfare value is the area under the marginal-utility curve and represents the total benefit of all nearby green space. Under normal market conditions, welfare value exceeds exchange value. Where green-space supply exceeds the point at which households are no longer willing to pay for an additional unit, exchange value is zero even though individual welfare value is at its maximum. Such places are generally on urban fringes or outside urban areas, where lower population numbers make the aggregate benefit smaller than in densely settled districts. A separate scarcity indicator multiplies the simulated marginal price by the number of households to show where an additional unit of green could have the greatest aggregate social significance.

In the highest-density cells, the estimated €783,838 per hectare per year corresponds to a one-time present value of €2,613 per square metre when calculated for an indefinite period at a 3% discount rate. Halving the discount rate to 1.5% doubles that one-time value. For comparison, average expenditure for land ready for construction in German cities with more than 500,000 inhabitants was just under €700 per square metre in 2016, the reference year for the monetary estimates. Even the present value of particularly expensive park construction and maintenance, calculated from information used by the earlier study, was about €680 per square metre. In the lowest-density cells, which contain 40% of the population, the green-space estimate averages just under €12 per square metre. This is below the €56 average 2016 sales value of building plots in municipalities with fewer than 2,000 inhabitants and the cited €78 present value for particularly low-cost green provision.

Intermediate-density cells, containing the remaining 30% of the population, have a mean green-space value of approximately €486 per square metre. Depending on the density class, this estimate is partly above and partly below the combined benchmark of €294 per square metre for building land in cities with 200,000–500,000 inhabitants and €379 per square metre for the cited construction and maintenance costs of parks. The researchers therefore conclude that, within the model’s assumptions, the amenity value of green space can exceed both development value and the costs of providing green in many locations. The estimates do not show that every city will capture a fiscal return: they measure household welfare through a simulated exchange value rather than municipal income.

Several limitations constrain how the national results can be used. The model uses an average marginal-utility function, making the monetary estimates income-neutral and potentially underrepresenting low-income neighbourhoods, where limited access to private gardens or fewer resources for recreational travel may increase the need for public green space. It also does not capture the value of large green spaces as local identity markers or establish minimum provision for every resident. Private gardens, urban and roadside trees, and qualitative features such as the condition and character of green space were excluded. Because health was already included in the original life-satisfaction regression, part of the measured association may reflect recreation, air filtration or local climate regulation rather than visual amenity alone; the study could not quantify those overlaps. The “sorted preferences” correction, which accounts for the possibility that people who value green more strongly choose to live where it is more abundant, remains uncertain because its proposed upper and lower limits are relatively far apart. Site-specific planning would additionally require current land-use dynamics, neighbourhood-level land prices and more detailed information on investment and maintenance costs.

Subject of Research: National modeling of urban green-space amenity values and their potential relevance to municipal planning in Germany.

Article Title: Setting priorities for greening cities with monetary accounting values for amenity services of urban green

Article References: Ekinci, B., Grunewald, K., Meier, S., Schwarz, S., Schweppe-Kraft, B., & Syrbe, R.-U. (2022). Setting priorities for greening cities with monetary accounting values for amenity services of urban green. One Ecosystem, 7, Article e89705. https://doi.org/10.3897/oneeco.7.e89705

Image Credits: AI Generated

DOI: 10.3897/oneeco.7.e89705

Keywords: urban green space, ecosystem accounting, life satisfaction, amenity services, Germany, municipal planning, welfare economics, land valuation, public green space, Setting, priorities, greening