Abstract
Domestic gardens provide residents with immediate access to landscape amenities and numerous ecological provisions. These ecological provisions have been proven to be largely determined by greenspace composition and landscape, but the fragmentation and heterogeneity of garden environments present challenges to greenspace mapping. Here, we first developed a recognition method to create a garden parcel data set in the medieval Leuven city of Belgium, based on the land use layers and agricultural land parcels. Then, we applied multi-sourced satellite imagery to evaluate the added value of spatial resolution, plant phenology and 3D structure in identifying four vegetation types. Finally, we characterized the greenspace landscapes in garden parcels. Compared with single ALOS-2 imagery, SPOT-7 imagery and Pleiades-1A imagery increased the overall accuracy by 4% and 8%, respectively. The accuracy improvement (21%) produced from multi-temporal stereo Pleiades-1A imagery strongly verified the significance of plant phenology and 3D structure in garden mapping. The average greenspace cover in garden parcels was 71% but varied from 56% in urban gardens to 82% in rural gardens. The garden greenspace landscape is fragmented by the artificial structures in urban areas but has a more aggregated size and less complex shapes in rural areas. This study calls for greater attention to be paid to gardens, and for multi-disciplinary studies conducted in collaboration with urban ecologists and landscape designers to maximize the benefits to residents of both immediate landscape amenities and ecological provisions, in the face of global environmental changes and public health risks.
Highlights
To evaluate the Normalized Digital Surface Model (nDSM) layer generated from stereo Pleiades-1A imagery, we here introduced an nDSM derived from Light Detection and Range (LiDAR) altitude data
The accuracy was improved up to 13% when combining multi-temporal and stereo Pleiades imagery. These improvements indicated that plant phenology and nDSM are a remarkable addition to single satellite imagery for urban green infrastructure (UGI) mapping
Domestic gardens comprise more than one-third of urban areas in many cities but have been the focus of less study due to their small size and lack of regulation
Summary
The introduce of multi-sourced data set may increase uncertainties caused by systematic and non-systematic factors, whereas, with the development of remote sensed techniques, increasing satellites capture a greater variety of image products, like multi-temporal and stereoscopic images. We first developed an approach to derive garden parcel data sets based on available spatial data sets, and we demonstrated the UGI composition and landscape at garden scale by applying multi-temporal stereo imagery to UGI mapping in domestic gardens. During the UGI mapping, we developed classification schemes based on ALOS-2, SPOT-7 and Pleiades imagery These were designed to (1) evaluate the added value of increased spatial resolution, plant phenology and 3D structure for identifying vegetation types, and (2) demonstrate the composition and landscape variations of domestic gardens in the compact European city of Leuven, Belgium. Our case study exemplified an application of garden monitoring and called for greater attention from both local authorities and stakeholders to garden management and ecological provisions
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