A new data aggregation technique to improve landscape metric downscaling

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Scale is a fundamental concept in landscape ecology and considerable attention has been given to the scale-dependent relationships of landscape metrics. Many metrics have been found to exhibit very consistent scaling relationships as map resolution (i.e., pixel or grain size) is increased. However, these scaling relationships tend to break down when attempting to 'downscale' them, and the scaling function is often unable to accurately predict metric values for finer resolutions than the original data. The reasons for this breakdown are not well understood. This research examines the downscaling behavior of metrics using various data aggregation techniques in an attempt to better understand the characteristics of metric scaling behavior. First, downscaling performance is examined using the traditional method of aggregation known as 'majority rules'. Second, a new data aggregation technique is introduced that utilizes fractional land cover abundances obtained from sub-pixel remote sensing classifications in order to capture a greater amount of the spatial heterogeneity present in the landscape. The goal of this new aggregation technique is to produce a more accurate scaling relationship that can be downscaled to predict metric values at fine resolutions. Results indicate that sub-pixel classifications have the potential to transform data aggregation to allow more accurate downscaling for certain landscapes, but accuracy is linked to the spatial heterogeneity of the landscape.

Original languageEnglish (US)
Pages (from-to)1261-1276
Number of pages16
JournalLandscape Ecology
Volume29
Issue number7
DOIs
StatePublished - Aug 2014
Externally publishedYes

Keywords

  • Aggregation
  • Classification
  • Landscape metrics
  • Modifiable areal unit problem (MAUP)
  • Pattern
  • Population weighting
  • Power law
  • Spectral unmixing

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Ecology
  • Nature and Landscape Conservation

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