Abstract
This paper describes and illustrates methods for quantifying regional differences in land use/land cover changes. A series of approaches are used to analyse differences in land cover change from data held in change matrices. These are contingency tables and are commonly used in remote sensing to describe the spatial coincidence of land cover recorded over two time periods. Comparative analyses of regional change are developed using odds ratios to analyse data in two regions. These approaches are extended using generalised linear models to analyse data for three or more regions. A generalised Poisson regression model is used to generate a comparative index of change based on differences in change likelihoods. Mosaic plots are used to provide a visual representation of statistically surprising land use losses and gains. The methods are explored using a hypothetical but tractable dataset and then applied to a national case study of coastal land use changes over 50 years conducted for the National Trust. The suitability of the different approaches to different types of problem and the potential for their application to land cover accuracy measures are briefly discussed.
Highlights
The correspondence matrix has become the de facto method for reporting on post classification land cover change [1,2,3]
Possible objectives include determining how much more probable land cover change is in Region A compared to Region B or C, or the relative likelihood of a specific change in Zone Z compared to Zone Y. It is within this context that this paper suggests some statistical approaches that can be readily applied to land cover change data, as summarised in a correspondence matrix
This paper describes a series of approaches for statistically comparing land cover change in different regions based on analyses of data held in correspondence matrices
Summary
The correspondence matrix has become the de facto method for reporting on post classification land cover change [1,2,3]. The purpose of this paper is not to contribute to the debate about the salience of Kappa and similar statistics for describing change or accuracy. Rather, it is to explore how methods for analysing contingency tables may be applied to correspondence matrices arising from analyses of land cover and Remote Sens. These are applied to the results of a national coastal land use change study that compared data from 1965 and 2014. A recent review of land cover change using optical remote sensing identified post-classification comparison as the most widely used change analysis along with the correspondence matrix [3,11]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
