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Classified earth observation data between 1990 and 2015 for the Perth Metropolitan Region, Western Australia using the Import Vector Machine algorithm.

Classified earth observation data between 1990 and 2015 for the Perth Metropolitan Region, Western Australia using the Import Vector Machine algorithm.
Classified earth observation data between 1990 and 2015 for the Perth Metropolitan Region, Western Australia using the Import Vector Machine algorithm.
This dataset represents land cover for 7 sequential snapshots (1990, 2000, 2003, 2005, 2007, 2013 and 2015) over the Perth Metropolitan Region, Western Australia (WA) derived from medium resolution Landsat data. Cloud free imagery was acquired in or close to the month of July coinciding with WA's winter months coinciding with peak green-up facilitating the greatest contrast between spectrally similar surfaces (e.g. bare earth and urban). Imagery was first standardised and normalised to remove inherent residual noise (e.g. differences in modelled atmospheric correction parameters) whilst permitting classification of all imagery based upon a single classification model. The model was computed from the 2005 image representing the month post maximum rainfall of all considered imagery associated with peak greenness and maximum spectral separability. Classification of the normalised data was achieved with the Import Vector Machine (IVM) algorithm following a hybrid forward/backward strategy that adds import vectors whilst continuously testing validity in each step, producing a sparse and more accurate classification solution. Classified land cover data is provided in raster format (.tif) and divided into the classes: bare earth (1), grassland (2), low urban albedo (e.g. asphalt (3)), water (4), forest (5) and high urban albedo (e.g. concrete (6)). Please see MacLachlan et al. (2017) for further details.
unsustainable development, urban expansion, remote sensing, Landsat, classified data
PANGAEA - Data Publisher for Earth & Environmental Science
MacLachlan, Andrew, Charles
7256882c-d3c7-4bd9-99e7-e2a5e4b5ed75
Biggs, Eloise
2bd93dcc-4396-460b-8329-13ce739ee9d4
Roberts, Gareth
fa1fc728-44bf-4dc2-8a66-166034093ef2
Boruff, Bryan
b13be7d3-1d2a-4030-a131-30bf4bfb114b
MacLachlan, Andrew, Charles
7256882c-d3c7-4bd9-99e7-e2a5e4b5ed75
Biggs, Eloise
2bd93dcc-4396-460b-8329-13ce739ee9d4
Roberts, Gareth
fa1fc728-44bf-4dc2-8a66-166034093ef2
Boruff, Bryan
b13be7d3-1d2a-4030-a131-30bf4bfb114b

MacLachlan, Andrew, Charles, Biggs, Eloise, Roberts, Gareth and Boruff, Bryan (2017) Classified earth observation data between 1990 and 2015 for the Perth Metropolitan Region, Western Australia using the Import Vector Machine algorithm. PANGAEA - Data Publisher for Earth & Environmental Science doi:10.1594/PANGAEA.871017 [Dataset]

Record type: Dataset

Abstract

This dataset represents land cover for 7 sequential snapshots (1990, 2000, 2003, 2005, 2007, 2013 and 2015) over the Perth Metropolitan Region, Western Australia (WA) derived from medium resolution Landsat data. Cloud free imagery was acquired in or close to the month of July coinciding with WA's winter months coinciding with peak green-up facilitating the greatest contrast between spectrally similar surfaces (e.g. bare earth and urban). Imagery was first standardised and normalised to remove inherent residual noise (e.g. differences in modelled atmospheric correction parameters) whilst permitting classification of all imagery based upon a single classification model. The model was computed from the 2005 image representing the month post maximum rainfall of all considered imagery associated with peak greenness and maximum spectral separability. Classification of the normalised data was achieved with the Import Vector Machine (IVM) algorithm following a hybrid forward/backward strategy that adds import vectors whilst continuously testing validity in each step, producing a sparse and more accurate classification solution. Classified land cover data is provided in raster format (.tif) and divided into the classes: bare earth (1), grassland (2), low urban albedo (e.g. asphalt (3)), water (4), forest (5) and high urban albedo (e.g. concrete (6)). Please see MacLachlan et al. (2017) for further details.

Archive
classifieddata.zip - Dataset
Available under License Creative Commons Attribution.
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More information

Published date: 24 January 2017
Keywords: unsustainable development, urban expansion, remote sensing, Landsat, classified data
Organisations: Geography & Environment, Global Env Change & Earth Observation

Identifiers

Local EPrints ID: 412070
URI: http://eprints.soton.ac.uk/id/eprint/412070
PURE UUID: 262be6b6-827b-4ac2-8d70-bfc436f1b969
ORCID for Gareth Roberts: ORCID iD orcid.org/0009-0007-3431-041X

Catalogue record

Date deposited: 05 Jul 2017 16:32
Last modified: 12 Apr 2024 01:44

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Contributors

Creator: Andrew, Charles MacLachlan
Creator: Eloise Biggs
Creator: Gareth Roberts ORCID iD
Creator: Bryan Boruff

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