Description

Records change in land use (e.g., from brownfield to green areas by adding vegetated brownfield to UGI resource) and accounting for configuration (e.g., individual gardens, groups of gardens and socio-economic factors impact on the utility of private gardens for native biodiversity conservation).

Identifying urban land-use patterns is important for decision-makers to ensure sustainable development. Typical metrics for this indicator comprise the use of land use and land cover maps. These are typically obtained by classifying and modelling Remotely Sensed (RS) data, for example Landsat in a GIS environment. Use of remote sensing involves the application of multi temporal datasets to quantitatively analyse the temporal effects of the land use changes as well as green space configuration. Due to the high degree of complexity of urban issues, GIS and remote sensing (RS) technologies have long been used to facilitate scientists to assess the overall state of urban environment, to manage the urban infrastructures and improve the efficiency and rationality of its spatial management. A necessary prerequisite for the improvement of urban environment is rationality of its spatial management – the optimal division of urban spaces by their functional predestination. One of approaches suited to this is functional zonation of the city – a spatial management of basic types of activities – labour, household, recreational. Data on landuse change and greenspace configuration collected in these ways can be used to:

• Track landuse change on sites in relation to ecosystem service provision;
• Track trends in private garden use to monitor a substantial green infrastructure asset over which local authorities have little influence;
• Set targets for landuse change, for example recognising the highest quality brownfield sites for biodiversity and ecosystem service delivery and prioritising the beneficial reuse of brownfield sites with little environmental value.

Scale as linked to D2.2 framework

Applied methods:

• This indicator is generally applied at a city-scale, but neighbourhood and site level assessments can also be made.

Earth observation/Remote sensing methods:

• methods suitable for a range of geographical scales.

Data source [ link to data framework]

• Satellite-derived land use maps such as CORINE.

Data needs

• Required data will depend on selected methods, for further details see applied and earth observation/remote sensing metrics reviews in: Connecting Nature Indicator Metrics Reviews Env42_Applied and Env42_RS

Expected Outputs

• Percentage changes of land cover types
• Maps

Calculation methods

• GIS

Links and references

Applied methods:

• Daniels, G.D. and Kirkpatrick, J.B. (2006) Does variation in garden characteristics influence the conservation of birds in suburbia? Biological Conservation 133, 326–335.
• Goddard, MA, Dougill, AJ and Benton, TG (2010) Scaling up from gardens: biodiversity conservation in urban environments. TREE 1175 1–9.
• Jia, Y., Ge, Y., Ling, F., Guo, X., Wang, J., Wang, L., Chen, Y. and Li, X., 2018. Urban Land Use Mapping by Combining Remote Sensing Imagery and Mobile Phone Positioning Data. Remote Sensing, 10(3): 446.
• Mathey, J., Rößler, S., Banse, J., Lehmann, I. and Bräuer, A. (2015) Brownfields as an element of green infrastructure for implementing ecosystem services into urban areas. Journal of Urban Planning and Development, 141(3), A4015001.
• Pauleit, S. and Duhme, F. (2000) Assessing the environmental performance of land cover types for urban planning. Landscape and urban planning, 52(1), 1-20.
• Smith, RM, Gaston, KJ, Warren, P and Thompson, K (2006) Urban domestic gardens (VIII): Environmental correlates of invertebrate abundance. Biodiversity and Conservation, 15, 2515–2545.

Earth observation/Remote sensing methods:

• Agarwal C., G. M. Green, J. M. Grove, T. P. Evans and C. M. Schweik (2002) A Review and Assessment of Land-Use Change Models: Dynamics of Space, Time, and Human Choice. Apollo the International Magazine of Art and Antiques, 1 (1).
• Fonji, S. F., & Taff, G. N. (2014). Using satellite data to monitor land-use land-cover change in North-eastern Latvia. SpringerPlus, 3, 61. doi:10.1186/2193-1801-3-61
• Hansen, M.C.; Loveland, T.R. A review of large area monitoring of land cover change using Landsat data. Remote Sens. Environ. 2012, 122, 66–74.
• Yang, X.; Lo, C.P. Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area. Int. J. Remote Sens. 2002, 23, 1775– 1798.
• Baumann, M.; Ozdogan, M.; Kuemmerle, T.; Wendland, K.J.; Esipova, E.; Radeloff, V.C. Using the Landsat record to detect forest-cover changes during and after the collapse of the Soviet Union in the temperate zone of European Russia. Remote Sens. Environ. 2012, 124, 174–184.
• Taubenböck, H.; Esch, T.; Felbier, A. Monitoring urbanization in mega cities from space. Remote Sens. Environ. 2012, 117, 162–176
• Vanonckelen, S.; Lhermitte, S.; van Rompaey, A. The effect of atmospheric and topographic correction methods on land cover classification accuracy. Int. J. Appl. Earth Obs. Geoinf. 2013, 24, 9–21.