Information on changes in the area of different ecosystems is needed in order to establish an accounting system for ecosystem conditions and services. Currently, there are no comprehensive field mappings for the German federal states that obey a uniform mapping system. To create a nationwide “ecosystem accounting”, it is necessary to develop a uniform system of ecosystem classifications that can consistently deal with diverse nationwide data sources on the extent and condition of ecosystems, some of which use their own forms of classification. Against this background, we present a concrete proposal on how to combine and blend GIS land-use and ecosystem data that is compatible with EU-wide approaches with other regularly collected data sources, for example, from sample-based surveys, so as to generate a complete, updatable picture of the state of Germany’s ecosystems. The area shares of ecosystem types (ETs) can be shown in maps. Allocation tables with different classes or levels (layers) enable an ecosystem extent accounting, which are used to help draw up balances (area balance, status balance, service balance) and can be further detailed, depending on the task at hand. First results and trends of areal changes of main and sub-ecosystem types in Germany, based on the proposed classification system, are presented and discussed. However, the brevity of the considered timeframe (the three periods 2012-2015-2018) does not yet allow us to pinpoint trends or migratory movements, as these may be masked by methodological changes in the classification of land use and land cover. Nonetheless, the presented system for accounting changes in ecosystem areas should be continued and developed in the future in order to create a useful tool for biodiversity monitoring in Germany.
Life Satisfaction Analyses in Germany reveal a significant positive correlation between the amount of green space within 1 km of residence and well-being. The comparison of the effects of green space and income on well-being allows the derivation of a monetary demand function for green spaces close to the place of home. This demand function was used together with land-use and population data to estimate the monetary value of green space close to home for every 2 km × 2 km grid cell in Germany.
The results can be used in environmental economic accounting as a proxy for the (visual) amenity services of green spaces close to residences and provide urban planners with additional information on the strength and spatial distribution of demand for green spaces in residential areas.
The study shows that, especially in densely populated areas where more than 30 per cent of the German population lives, the (simulated) exchange value of green spaces (price per additional hectare derived from the demand function) multiplied by the number of households that would pay this price, is higher than the price per ha that can be achieved on the real estate market.
A comparison with the results of a Hedonic Price Analysis that estimates the effect of urban green space on property prices finds that the values of urban green spaces calculated with this method were 38 to 124 times smaller than the values calculated with the Life Satisfaction Analysis and far below building land prices. The reason for the relatively low impact of urban green on property prices can be explained by market imperfections in the housing market.
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