Effects of changing scale on landscape pattern analysis: scaling relations

By Jianguo Wu. Landscape Ecology, 2004

1,128 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/c9b434f180d66b15b1908c126cc388e4ddd428ad

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In Ecology

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

The influence of thematic resolution on metric selection for biodiversity monitoring in agricultural landscapes (2007, background): “The metrics’ values thus not only depend on the landscapes’ characteristics but on a number of decisions made in preparing the landscape data (see for example Baldwin et al. 2004; Wu 2004).”
Multivariate correlations between imagery and field measurements across scales: comparing pixel aggregation and image segmentation (2010, methodology): “…data are of interest, and if so, then defining appropriate scales of analysis such that patterns relevant to an objective can be: (1) separated out from the background noise generated at finer scales, and (2) placed in context of processes operating at coarser scales (Wu 1999, 2004).”
Characterizing urban sprawl using multi-stage remote sensing images and landscape metrics (2006, methodology): “To understand spatial scale dependence of landscape metrics, Wu (2004) systematically studied scaling relations for landscape pattern measurement when comparing 17 class-level landscape metrics for four landscapes (land use and land cover maps), including the Phoenix urban area.”
Scale dependent inference in landscape genetics (2010, neutral): “While there is extensive knowledge of how changing grain of analysis affects landscape structure (Turner et al. 1989; Wickham and Ritters 1995; Wu 2004), there is relatively little known about how grain affects pattern–process relationships.”
Landscape metric performance in analyzing two decades of deforestation in the Amazon Basin of Rondonia, Brazil (2006, background): “Landscape level metric responses had a third category, a staircase pattern response (Wu, 2004).”
A multi-scaled analysis of avian response to habitat amount and fragmentation in the Canadian dry mixed-grass prairie (2006, methodology): “Parameter estimates derived using the LSI index are assumed to be robust to choice of landscape grain size, as this index shows consistent and robust scaling relationships (Wu 2004).”
A new approach for rescaling land cover data (2008, background): “Although numerous studies have assessed spatial aggregation errors (e.g., Costanza and Maxwell 1994; Moody and Woodcock 1995, 1996; Turner et al. 1989; Wu 2004), and model-based corrections have been suggested (e.”
On the accuracy of landscape pattern analysis using remote sensing data (2008, background): “Upscaling landscape metrics across grain sizes is often difficult or impossible because most metrics show erratic and unpredictable scaling behavior (Wu 2004).”
Response of arthropod species richness and functional groups to urban habitat structure and management (2010, background): “The size of the grid cells chosen to calculate these indices is critical for spatial pattern detection (Wu 2004).”
Evaluating empirical scaling relations of pattern metrics with simulated landscapes (2004, methodology): “As in Wu et al. (2002) and Wu (2004) , the scaling relations of the metrics with respect to changing grain size seem to fall into 3 types.”
Putting the ‘landscape’ in landscape genetics (2007, methodology): “These methods can be coupled with simulation techniques to examine the expected genetic neighborhood size, or testing how variability or pattern changes at different spatial scales (Gardner et al., 1987; Saura and Martı́nez-Millán, 2001; Wu, 2004).”
Evaluating the effectiveness of landscape metrics in quantifying spatial patterns (2010, background): “…more focus has been paid to scale relations (Wu et al., 2000, 2002; Saura and Martinez-Millan, 2001; Lausch and Herzog, 2002; Shen et al., 2004; Wu, 2004; Uuemaa et al., 2005; Saura and Castro, 2007), the accuracy of source data (Shao et al., 2001; Shao and Wu, 2008), and the ecological…”