Using landscape metrics to characterize towns along an urban-rural gradient

Abstract

Context Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation. Objectives We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability. Methods We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation. Results The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient. Conclusions Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

Effects of an Early Mass-flowering Crop on Wild Bee Communities and Traits in Power Line Corridors Vary With Floral Resources and Landscape Context

“…Additionally, urban and agricultural land cover in Maine contain different bee species than found in the forested matrix (Du Clos et al 2020; see also Harrison et al 2018), contributing to the greater species richness we observed in power line corridors in the Midcoast growing region. Urban land cover in Maine's lowbush blueberry production landscape is generally classi ed as exurban along an urban-rural land use gradient (Kaminski et al 2021), meaning there is plenty of green space and natural area that provides bee habitat. Although we found more wetland land cover Downeast than Midcoast, we do not have evidence that wetlands in uence Maine bee communities (Du Clos et al 2020).…”

Monitoring 3D Changes in Urban Forests Using Landscape Metrics Analyses Based on Multi-Temporal Remote Sensing Data

“…As researchers increasingly turn to R, a new 'landscapemetrics' package, an extensive collection of widely used LM becomes more popular [16]. In recent decades, interpreting these metrics has become an important research topic in landscape ecology [17], as well as in relation to the cityscape [18], sustainable development [19], the monitoring of land cover changes [20][21][22], and urban or regional planning [23]. Recent research has also shown the need to emphasize multi-scale interactions in landscape pattern studies, suggesting methods for big data analysis [24].…”

Evaluation of Land Cover Dynamics and Landscape Fragmentation in Ijebu Ode, Nigeria

“…Landscape metrics, otherwise referred to as spatial metrics, is a very useful tool for quantifying and assessing the distribution, pattern and structure of land use and land cover (Li & Wu, 2004;Kaminski et al, 2021;Maselli & Negri, 2021;Mohammadreza et al, 2022). The focus of landscape metrics is usually on three major characteristics of landscape: structure, function and change (Mohammadreza et al, 2022).…”

“…Different types of landscape metrics have been identified and applied to quantify and assess landscape fragmentation, both at level and class levels (McGarigal & Marks, 1995;Singh et al, 2017;Hesselbarth et al, 2019;Das & Angadi, 2021;Ai et al, 2022). Urban landscape fragmentation is usually the consequence of changes in landscape structure (Simons, 1988;Li & Wu, 2004;Kaminski et al, 2021). These changes are by-products of decreasing heterogeneity of landscape compositions and profound landscape fragmentation (Hartvigsen, 2014;Singh et al, 2014;Ciaian et al, 2018;Olayiwola & Fakayode, 2019;Bertram et al, 2021;Abbas et al, 2022).…”