Object‐based characterisation of reference sites for mine site closure using hyperspatial multispectral UAV imagery

Whiteside, Timothy G., Bartolo, Renée E., Erskine, Peter and Fletcher, Andrew (2014). Object‐based characterisation of reference sites for mine site closure using hyperspatial multispectral UAV imagery. In: Ioannis Gitas, Giorgios Mallinis, Petros Patias, Dimitris Stathakis and Georgios Zalidis, GEOBIA 2014, Αdvancements, trends and challenges, 5th Geographic Object-Based Image Analysis Conference, Greece. GEOBIA 2014, Thessaloniki, Greece, (119-123). 21-24 May 2014.

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Name Description MIMEType Size Downloads
Author Whiteside, Timothy G.
Bartolo, Renée E.
Erskine, Peter
Fletcher, Andrew
Title of paper Object‐based characterisation of reference sites for mine site closure using hyperspatial multispectral UAV imagery
Conference name GEOBIA 2014
Conference location Thessaloniki, Greece
Conference dates 21-24 May 2014
Proceedings title GEOBIA 2014, Αdvancements, trends and challenges, 5th Geographic Object-Based Image Analysis Conference, Greece
Journal name South-Eastern European Journal of Earth Observation and Geomatics
Place of Publication Thessaloniki, Greece
Publisher Aristotle University of Thessaloniki
Publication Year 2014
Sub-type Fully published paper
Open Access Status
ISSN 2241-1224
Editor Ioannis Gitas
Giorgios Mallinis
Petros Patias
Dimitris Stathakis
Georgios Zalidis
Volume 3
Issue 2s
Start page 119
End page 123
Total pages 5
Collection year 2015
Language eng
Abstract/Summary Monitoring schemes to assess the success in mine site rehabilitation typically on data from offsite analogues or pre‐mining baselines (collectively reference sites) that describe the ecosystems of the region. Differences between rehabilitated sites and reference sites are evaluated using environmental indicators. Field‐based methods that sample reference sites are limited in the temporal and spatial scale, due to the time and effort required. Unmanned aerial vehicles (UAVs) for remote sensing acquire imagery at sub‐ decimetre ground sample distance that create orthomosaics and digital surface models (DSMs). These data are of spatial extents far greater than can be achieved using field sampling and consequently, the spatial extent of features and heterogeneity of sites can be more readily characterized. A geographic object‐based framework was used to analyse UAV‐based orthomosaics and DSMs captured over reference sites in Kakadu National Park, northern Australia, surrounding Ranger uranium mine. The UAV sensors provided information at a spatial scale to successfully characterise the reference sites. The analysis provided a number of the key environmental indicators including vegetation structural information, such as canopy cover and height, and fractional ground cover estimates. The methodology established here will form a basis for monitoring the impacts and success of rehabilitation as progress occurs towards mine closure.
Keyword UAV
Hyper spatial resolution
Mine rehabilitation
Q-Index Code EX
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Conference Paper
Collections: Centre for Mined Land Rehabilitation Publications
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Created: Tue, 31 Mar 2015, 14:50:13 EST by Anthony Yeates on behalf of Centre For Mined Land Rehabilitation