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Sub-pixel land cover classification for improved urban area estimates using Landsat

Sub-pixel land cover classification for improved urban area estimates using Landsat
Sub-pixel land cover classification for improved urban area estimates using Landsat
Urban areas are Earth’s fastest growing land use that impact hydrological and ecological systems and the surface energy balance. The identification and extraction of accurate spatial information relating to urban areas is essential for future sustainable city planning owing to its importance within global environmental change and human-environment interactions. However, monitoring urban expansion using medium resolution (30-250m) imagery remains challenging due to the variety of surface materials that contribute to measured reflectance resulting in spectrally mixed pixels. This research integrates high spatial resolution orthophotos and Landsat imagery to identify differences across a range of diverse urban subsets within the rapidly expanding Perth Metropolitan Region, Western Australia. Results indicate that calibrating Landsat derived sub-pixel land cover estimates with correction values (calculated from spatially explicit comparisons of sub-pixel Landsat values to classified high resolution data which accounts for over (under) estimations of Landsat) reduces moderate resolution urban area over (under) estimates by on average 55.08% for the Perth Metropolitan Region. This approach can be applied to other urban areas globally through use of frequently available and/or low cost high spatial resolution imagery (e.g. using Google Earth). This will improve urban growth estimations to help monitor and measure change whilst providing metrics to facilitate sustainable urban development targets within cities around the world.
urban areas, landsat, spatial resolution, urban land use
0143-1161
5763-5792
MacLachlan, Andrew
7256882c-d3c7-4bd9-99e7-e2a5e4b5ed75
Roberts, Gareth
fa1fc728-44bf-4dc2-8a66-166034093ef2
Biggs, Eloise
f0afed06-18ac-4a4d-841c-36ea4ff8a3b4
Boruff, Bryan
b13be7d3-1d2a-4030-a131-30bf4bfb114b
MacLachlan, Andrew
7256882c-d3c7-4bd9-99e7-e2a5e4b5ed75
Roberts, Gareth
fa1fc728-44bf-4dc2-8a66-166034093ef2
Biggs, Eloise
f0afed06-18ac-4a4d-841c-36ea4ff8a3b4
Boruff, Bryan
b13be7d3-1d2a-4030-a131-30bf4bfb114b

MacLachlan, Andrew, Roberts, Gareth, Biggs, Eloise and Boruff, Bryan (2017) Sub-pixel land cover classification for improved urban area estimates using Landsat. International Journal of Remote Sensing, 38 (20), 5763-5792. (doi:10.1080/01431161.2017.1346403).

Record type: Article

Abstract

Urban areas are Earth’s fastest growing land use that impact hydrological and ecological systems and the surface energy balance. The identification and extraction of accurate spatial information relating to urban areas is essential for future sustainable city planning owing to its importance within global environmental change and human-environment interactions. However, monitoring urban expansion using medium resolution (30-250m) imagery remains challenging due to the variety of surface materials that contribute to measured reflectance resulting in spectrally mixed pixels. This research integrates high spatial resolution orthophotos and Landsat imagery to identify differences across a range of diverse urban subsets within the rapidly expanding Perth Metropolitan Region, Western Australia. Results indicate that calibrating Landsat derived sub-pixel land cover estimates with correction values (calculated from spatially explicit comparisons of sub-pixel Landsat values to classified high resolution data which accounts for over (under) estimations of Landsat) reduces moderate resolution urban area over (under) estimates by on average 55.08% for the Perth Metropolitan Region. This approach can be applied to other urban areas globally through use of frequently available and/or low cost high spatial resolution imagery (e.g. using Google Earth). This will improve urban growth estimations to help monitor and measure change whilst providing metrics to facilitate sustainable urban development targets within cities around the world.

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Sub-pixel land cover classification for improved urban area estimates using Landsat - Accepted Manuscript
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Accepted/In Press date: 13 June 2017
e-pub ahead of print date: 6 July 2017
Published date: October 2017
Additional Information: Funded by the Economic and Social Research Council, grant : ES/J500161/1, titled: Examining the current state, pressures and the potential risks of urban expansion in the Perth Metropolitan Region (PMR)
Keywords: urban areas, landsat, spatial resolution, urban land use
Organisations: Global Env Change & Earth Observation, Geography & Environment

Identifiers

Local EPrints ID: 409854
URI: http://eprints.soton.ac.uk/id/eprint/409854
ISSN: 0143-1161
PURE UUID: 95dd7f73-8138-4b19-8f43-d6b2d1ec5758
ORCID for Gareth Roberts: ORCID iD orcid.org/0009-0007-3431-041X

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Date deposited: 01 Jun 2017 04:08
Last modified: 12 Jun 2024 04:01

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Contributors

Author: Andrew MacLachlan
Author: Gareth Roberts ORCID iD
Author: Eloise Biggs
Author: Bryan Boruff

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