Abstract
Landscape metrics are widely used to measure the spatial pattern of landscapes. However, there are important gaps in their application. For instance, landscape metrics are sensitive to the spatial scale of analysis (i.e., extent and resolution) but while the influence of extent and resolution has been previously studied, their interaction has rarely been studied. In addition, studies assessing the influence of spatial scale on landscape metrics have scarcely paid attention to the impacts of land cover on this assessment, which reduces the generalisability or comparability of studies. Furthermore, as there are numerous landscape metrics that have been developed, these metrics exhibit degrees of correlation. Considered together, these limitations make it challenging to compare results across studies and form synthesis. We suggest that identifying a parsimonious set of metrics to promote comparability of studies will be desirable. We used Singapore as a case study to analyse how 11 commonly used landscape metrics responded to changing extents (ranging from 60 m × 60 m to 1200 m × 1200 m) in relation to resolution (Landsat 8, Sentinel-2, and WorldView-3) and land cover (vegetation and impervious surface). We used principal component analysis to identify bundles of metrics and recommend a set of common metrics across a combination of extent-resolution-land cover combinations. We highlight key observations from the study: 1) the response of all metrics to changes in spatial scale and land cover can be modelled with reasonable accuracy (indicated by model performance: R2 > 0.8); 2) different types of mathematical functions (e.g., linear, logarithmic) were found suitable for the response curve of metrics, suggesting different metrics responded differently to changing scales; 3) a consistent pattern of change for individual metrics was observed across extents, resolutions, and land covers; and 4) four metrics, PLAND (the proportional area of a landscape occupied by a certain land cover, expressed as percentage), SHAPE_AM (indicates the geometrical shape complexity of patches of a given land cover), PD (indicates the number of patches of a certain land cover type per hectare of the landscape that is an indication of the fragmentation level), and ENN_AM (indicates how close the patches of a certain land cover are in relation to one another), can adequately explain the spatial pattern across the studied extents, resolutions, and land covers. Our findings advance the knowledge of and promote comparability of studies on spatial pattern quantification using landscape metrics.
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Data Availability
The data supporting the findings of the study are available in the Mendeley Data repository with the following citation. Masoudi, Mahyar; Richards, Daniel; Tan, Puay Yok (2024), “Data underlying research paper entitled ‘Assessment of the influence of spatial scale and type of land cover on urban landscape pattern analysis using landscape metrics’”, Mendeley Data, V1, https://doi.org/10.17632/rtfc64334p.1.
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Acknowledgements
We would like to thank the anonymous reviewers for their useful feedback. We also like to thank Mr. Aikeen Lim for assistance with the initial data analysis.
Funding
This research was supported by the National Research Foundation, Prime Minister’s Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) Programme (NRF2016-ITC001-013). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
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Mahyar Masoudi: conceptualisation, methodology, software, validation, formal analysis, investigation, data curation, writing—original draft, writing—review and editing, visualisation, and project administration. Dan R. Richards: resources, writing—review and editing, and funding acquisition. Puay Yok Tan: conceptualisation, resources, writing—review and editing, supervision, and funding acquisition.
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Masoudi, M., Richards, D.R. & Tan, P.Y. Assessment of the Influence of Spatial Scale and Type of Land Cover on Urban Landscape Pattern Analysis Using Landscape Metrics. J geovis spat anal 8, 8 (2024). https://doi.org/10.1007/s41651-024-00170-8
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DOI: https://doi.org/10.1007/s41651-024-00170-8