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Are landscape ecologists addressing uncertainty in their remote sensing data?

Citation

Lechner, AM and Langford, WT and Bekessy, SA and Jones, SD, Are landscape ecologists addressing uncertainty in their remote sensing data?, Landscape Ecology, 27, (9) pp. 1249-1261. ISSN 0921-2973 (2012) [Refereed Article]

Copyright Statement

Copyright 2013 Springer

DOI: doi:10.1007/s10980-012-9791-7

Abstract

In this quantitative review, we investigate the degree to which landscape ecology studies that use spatial data address spatial uncertainty when conducting analyses. We identify three broad categories of spatial uncertainty that are important in determining the characterisation of landscape pattern and affect the outcome of analysis in landscape ecology: (i) classification scheme uncertainty, (ii) spatial scale and (iii) classification error. The second category, spatial scale, was further subdivided into five scale dependent factors (i) pixel size, (ii) minimum mappable unit, (iii) smoothing, (iv) thematic resolution and (v) extent. We reviewed all articles published in the journal Landscape ecology in 2007 and recorded how spatial data was used and whether spatial uncertainty was addressed or reported in ecological analyses. This review found that spatial uncertainty was rarely addressed and/or reported. Only 23 % of articles addressed one or more scale dependent factors and 47 % reported one or more as issues. Most articles used the default pixel size of the sensor, and only a single study of the 59 investigated the effect of classification accuracy on ecological analyses. We demonstrate that spatial uncertainty is not being addressed as standard practice in analyses in landscape ecology, and then describe methods to test for spatial uncertainty and potential solutions that can be developed in the future.

Item Details

Item Type:Refereed Article
Keywords:scale, spatial uncertainty, classification error, landscape pattern, remote sensing, GIS, land-cover mapping
Research Division:Engineering
Research Group:Geomatic Engineering
Research Field:Photogrammetry and Remote Sensing
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Environmental Sciences
Author:Lechner, AM (Dr Alex Lechner)
ID Code:95630
Year Published:2012
Web of Science® Times Cited:33
Deposited By:Centre for Environment
Deposited On:2014-10-06
Last Modified:2014-12-01
Downloads:0

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