Green volume is a parameter used in landscape planning denoted by the green volume number (GVZ). The GVZ was developed in Hamburg in the 1980s with the purpose of quantifying the required vegetation to be planted in binding numbers for landscape, green space and development planning (Schulze et al. 1984).
The GVZ measures the existence of three-dimensional vegetation bodies (trees, shrubs, grasses) present in one unit of area and is denoted in unit m³ per m². In Berlin, this refers to both blocks and block segment areas shown in map 1 : 5,000 (ISU5, Spatial Reference, 2020) as well as to road segments.
The functions of vegetation are manifold. The following applies to many of them: the larger the green volume, the more pronounced its impact. The following functions are particularly important in relation to urban and landscape planning:
- dust binding,
- increase of evaporation,
- decrease of temperature,
- increase of small-scale air circulation,
- shading,
- habitat and biotope function,
- noise reduction.
Furthermore, green volume plays an important role in recreation, cityscape and landscape.
Comprehensive green volume data has been collected in multiple cities to date, e.g. by means of laser scanner data and spatial deficits in the provision of green space have been identified. (Meinel 2022, Frick et al. 2020). In the Brandenburg State Capital of Potsdam, the green volume number, along with biotope type mapping and the degree of imperviousness, is an integral part of its environmental monitoring carried out in a six-year cycle (Brandenburg State Capital of Potsdam 2018). With the help of the impervious soil coverage and green volume parameters, the environmental status may serve as an indicator of quality of life and housing and the climatic burden on urban quarters (Arlt et al. 2005, State Capital of Potsdam 2010).
Due to the climate change and climate adaptation in the cities, the green volume has become more and more important in recent years (cf. Reusswig et al. 2016, SenStadtUm 2016a). The diverse beneficial effects vegetation has, e.g. on the local climate, have been proven in a range of studies (cf. Meinel et al. 2022). The shading effect of trees, among other things, was hence investigated. Using the example of three sites, an Oxford research project demonstrated that the surface temperature of lawns and paved areas in the shade of trees was greatly reduced (by up to 13 K), as compared to that of unshaded areas. Furthermore, the project found that green volume has a direct impact on surface temperature. By increasing the green volume by 10 %, it is possible to reduce the temperature by 2.2 K (1961-1990) and 2.5 K (scenario 2080) (Gill et al. 2007). Increasing the green volume therefore lowers the maximum surface temperature, thus mitigating the effects of climate change and the formation of urban heat islands.
For Potsdam, green volume and imperviousness were confirmed to be relevant in influencing the temperature development within the context of climate adaptation. Taking the example of a hot summer day with temperatures ranging from approx. 25 to 35 °C, it was demonstrated that each additional m³/m² of green volume reduces the temperatures by about 0.3 K, while 1% (1 m²/100 m²) of additional imperviousness causes the temperature to rise by about 0.03 K (Tervooren 2015).
The distribution of green volume also plays a role in this (Mathey et al. 2011). Large, connected open spaces and parks have a more pronounced internal climatic effect and a slightly greater cooling effect on their surroundings than many smaller, scattered open spaces. At the same time, a dense network of smaller open spaces allows for easier accessibility, compensating for the above advantages. These effects can be explained applying the indicators “Cold air affect range within settlement areas” and “Green spaces with high volume flow” (SenStadtUm 2016c) of the summary Climate Analysis Map of Berlin.
There is no doubt in the scientific community about the importance of the green volume indicator in determining the quality of residential areas (F+B 2020). Since 2019, it has been part of a list of 13 indicators used to determine the quality of residential locations for the Berlin rent index.