Using remote sensing in support of environmental management : a framework for selecting products, algorithms and methods
Date
2016-08
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Traditionally, to map environmental features using remote sensing, practitioners will use training data to
develop models on various satellite data sets using a number of classification approaches and use test
data to select a single ‘best performer’ from which the final map is made. We use a combination of an
omission/commission plot to evaluate various results and compile a probability map based on consistently
strong performing models across a range of standard accuracy measures. We suggest that this
easy-to-use approach can be applied in any study using remote sensing to map natural features for
management action. We demonstrate this approach using optical remote sensing products of different
spatial and spectral resolution to map the endemic and threatened flora of quartz patches in the
Knersvlakte, South Africa. Quartz patches can be mapped using either SPOT 5 (used due to its relatively
fine spatial resolution) or Landsat8 imagery (used because it is freely accessible and has higher spectral
resolution). Of the variety of classification algorithms available, we tested maximum likelihood and
support vector machine, and applied these to raw spectral data, the first three PCA summaries of the
data, and the standard normalised difference vegetation index.We found that there is no ‘one size fits all’
solution to the choice of a ‘best fit’ model (i.e. combination of classification algorithm or data sets), which
is in agreement with the literature that classifier performance will vary with data properties.We feel this
lends support to our suggestion that rather than the identification of a ‘single best’ model and a map
based on this result alone, a probability map based on the range of consistently top performing models
provides a rigorous solution to environmental mapping.
Description
CITATION: De Klerk, H.M. et al. 2016. Using remote sensing in support of environmental management: A framework for selecting products, algorithms and methods. Journal of Environmental Management, (182):564-573, doi:10.1016/j.jenvman.2016.07.073.
The original publication is available at http://www.journals.elsevier.com/journal-of-environmental-management/
The original publication is available at http://www.journals.elsevier.com/journal-of-environmental-management/
Keywords
Environmental management -- Remote sensing
Citation
De Klerk, H.M. et al. 2016. Using remote sensing in support of environmental management: A framework for selecting products, algorithms and methods. Journal of Environmental Management, (182):564-573, doi:10.1016/j.jenvman.2016.07.073.