Characterizing and measuring urban landscapes for sustainability

Abstract

Urban areas are key to sustainability, and understanding heterogeneity in urban landscapes is important for linking development patterns to ecological, economic, and social health. Here, we characterize the urban landscape for the purpose of revealing structural variations that affect sustainability. We develop a new language and classification schema for breaking down urban areas into sub-metropolitan land units that, unlike administrative boundaries, are based on objective measures of the built and natural environment and are comparable across and within urban areas. These units capture structural differences that population density does not. The classification schema offers a process-based characterization of urban landscapes-one where 'urban' is defined by the human and biophysical interactions mediated by the urban environment and complements existing land classification systems, like those based on land use and land cover. As an example, the schema is applied here to understand transportation behaviors-a particular urban process with wide-ranging implications for urban sustainability. Using GIS, satellite, and census spatial data, we apply the classification schema in 909 US urban areas, systematically clustering development with similar structural attributes linked to transportation behaviors. In this way, an urban area is divided into a collection of smaller landscapes, larger than individual households and smaller than census tracts, that are distinct in how they function. The study shows that characterizing the urban landscape in this way can distinguish between neighborhoods with different travel behaviors. Extensions of the schema can be used to monitor and manage urban systems towards sustainability, targeting spatial planning strategies to the micro-geographies where they would be most relevant.

Mapping urban-rural gradients of settlements and vegetation at national scale using Sentinel-2 spectral-temporal metrics and regression-based unmixing with synthetic training data

“…For example, emissions from transportation greatly depend on the patterns of settlement development ( Baiocchi et al, 2015 ). Within settlements, the type and structure of sub-areas also has a large impact on different aspects of human life quality, mobility behaviour, settlement resilience and environmental impacts of built-up features ( Stokes and Seto, 2019 ). This is why settlement mapping requires a spatially comprehensive approach encompassing the entire urban-rural gradient, where the character regarding building density, building structure, object sizes, green space and infrastructure varies gradually.…”

Remote Sensing-Based Analysis of Landscape Pattern Evolution in Industrial Rural Areas: A Case of Southern Jiangsu, China

“…Consequently, the spatiotemporal characteristics of landscape changes in metropolitan areas can be monitored, facilitating the investigation of the influence of urban expansion on both urban and rural landscapes [18,19]. Land-use change maps can also reflect the influence of land consolidation on local landscape patterns, which is vital for optimizing land consolidation models and accelerating the sustainable development of local communities [20,21]. The evolution of landscape patterns also leads to changes in the spatial and ecosystem structures of landscapes, which ultimately influences ecological security [22][23][24].…”

Urban Land Use: Central to Building a Sustainable Future

“…Growing evidence from multiple disciplines shows that urban land use, form, and structure are central to achieving desirable sustainability outcomes. 4 Patterns of human movement and demand for raw materials are shaped by urban ge-ometries and the configuration of spaces and transit corridors. 5,6 Urban design can foster-or prevent-accessibility, which can reduce carbon footprints and build social cohesion, walkability, which can reduce chronic disease risks, and green spaces that improve mental health and reduce the urban-heat-island effect.…”

“…Here, we deconstruct urban land use into seven different dimensions that encapsulate ideas of materiality, configuration, inter-relational attributes, and use of time 4,12 (Figure 2). A single blueprint could be produced from measuring each of these dimensions at the neighborhood or city level.…”