Abstract
Domestic gardens are an important component of cities, contributing significantly to urban green infrastructure (GI) and its associated ecosystem services. However, domestic gardens are incredibly heterogeneous which presents challenges for quantifying their GI contribution and associated benefits for sustainable urban development. This study applies an innovative methodology that combines citizen science data with high resolution image analysis to create a garden dataset in the case study city of Manchester, UK. An online Citizen Science Survey (CSS) collected estimates of proportional coverage for 10 garden land surface types from 1031 city residents. High resolution image analysis was conducted to validate the CSS estimates, and to classify 7 land surface cover categories for all garden parcels in the city. Validation of the CSS land surface estimations revealed a mean accuracy of 76.63% (s = 15.24%), demonstrating that citizens are able to provide valid estimates of garden surface coverage proportions. An Object Based Image Analysis (OBIA) classification achieved an estimated overall accuracy of 82%, with further processing required to classify shadow objects. CSS land surface estimations were then extrapolated across the entire classification through calculation of within image class proportions, to provide the proportional coverage of 10 garden land surface types (buildings, hard impervious surfaces, hard pervious surfaces, bare soil, trees, shrubs, mown grass, rough grass, cultivated land, water) within every garden parcel in the city. The final dataset provides a better understanding of the composition of GI in domestic gardens and how this varies across the city. An average garden in Manchester has 50.23% GI, including trees (16.54%), mown grass (14.46%), shrubs (9.19%), cultivated land (7.62%), rough grass (1.97%) and water (0.45%). At the city scale, Manchester has 49.0% GI, and around one fifth (20.94%) of this GI is contained within domestic gardens. This is useful evidence to inform local urban development policies.
Highlights
Private domestic gardens can significantly contribute to a city’s green infrastructure (GI), potentially occupying over a third of a city’s urban surface area [1]
The remainder of responses were from households in rental properties from private landlords, registered landlords/ housing associations or the council
A combined approach was applied to classify land surface cover of urban domestic gardens using citizen science data and high resolution image analysis. This combined approach was advantageous for two main reasons. It enabled an assessment of the quality of citizen science data collected in relation to estimations of land cover proportions of ten common domestic garden land surface cover types, finding that citizens are able to quite accurately estimate this within their gardens
Summary
Private domestic gardens can significantly contribute to a city’s green infrastructure (GI), potentially occupying over a third of a city’s urban surface area [1]. The infrastructure and surface cover associated with urban environments renders these areas vulnerable to climate change and extreme meteorological events These small pockets of urban greenspace, perform an important role in the regulation of climate and reduction of associated climate risks such as flooding and the urban heat island [2]. It is important that this aspect of GI is accurately mapped as current approaches can lead to an overestimation of urban greenspace, in addition to subsequent erroneous evaluation of ecosystem service provision and environmental deprivation. This has implications for the future resilience of an urban environment and the health and well-being of its citizens
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