Methods to Quantify Regional Differences in Land Cover Change

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 des...

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Main Authors: Alexis Comber, Heiko Balzter, Beth Cole, Peter Fisher, Sarah C.M. Johnson, Booker Ogutu
Format: Article
Language:English
Published: MDPI AG 2016-02-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/8/3/176
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spelling doaj-da4d0f2dceaf4ac0b6f3b71852823bee2020-11-24T21:33:05ZengMDPI AGRemote Sensing2072-42922016-02-018317610.3390/rs8030176rs8030176Methods to Quantify Regional Differences in Land Cover ChangeAlexis Comber0Heiko Balzter1Beth Cole2Peter Fisher3Sarah C.M. Johnson4Booker Ogutu5School of Geography, University of Leeds, Leeds LS2 9JT, UKCentre for Landscape and Climate Research, Department of Geography, University of Leicester, Leicester LE1 7RH, UKCentre for Landscape and Climate Research, Department of Geography, University of Leicester, Leicester LE1 7RH, UKCentre for Landscape and Climate Research, Department of Geography, University of Leicester, Leicester LE1 7RH, UKCentre for Landscape and Climate Research, Department of Geography, University of Leicester, Leicester LE1 7RH, UKGeography and Environment, University of Southampton, Southampton SO17 1BJ, UKThis 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.http://www.mdpi.com/2072-4292/8/3/176land cover changeland use changeremote sensing accuracystatistical analysisvisualization
collection DOAJ
language English
format Article
sources DOAJ
author Alexis Comber
Heiko Balzter
Beth Cole
Peter Fisher
Sarah C.M. Johnson
Booker Ogutu
spellingShingle Alexis Comber
Heiko Balzter
Beth Cole
Peter Fisher
Sarah C.M. Johnson
Booker Ogutu
Methods to Quantify Regional Differences in Land Cover Change
Remote Sensing
land cover change
land use change
remote sensing accuracy
statistical analysis
visualization
author_facet Alexis Comber
Heiko Balzter
Beth Cole
Peter Fisher
Sarah C.M. Johnson
Booker Ogutu
author_sort Alexis Comber
title Methods to Quantify Regional Differences in Land Cover Change
title_short Methods to Quantify Regional Differences in Land Cover Change
title_full Methods to Quantify Regional Differences in Land Cover Change
title_fullStr Methods to Quantify Regional Differences in Land Cover Change
title_full_unstemmed Methods to Quantify Regional Differences in Land Cover Change
title_sort methods to quantify regional differences in land cover change
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2016-02-01
description 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.
topic land cover change
land use change
remote sensing accuracy
statistical analysis
visualization
url http://www.mdpi.com/2072-4292/8/3/176
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