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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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 |
work_keys_str_mv |
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