Leo Lymburner

Dr. Leo Lymburner


Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2014 in Remote Sensing of Environment
Verified
Journal Article
Open access
DRD.P. Roy
D.P. Roy
MWMichael Wulder
Michael Wulder
TLT.R. Loveland
T.R. Loveland
WCWoodcock C.E.
Woodcock C.E.
RAR.G. Allen
R.G. Allen
Zhe ZhuZhe Zhu
Zhe Zhu
Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements

1 May 2019 in Remote Sensing of Environment
Verified
Journal Article
Open access
MWMichael Wulder
Michael Wulder
TLThomas R. Loveland
Thomas R. Loveland
DRDavid P. Roy
David P. Roy
CCChristopher J. Crawford
Christopher J. Crawford
JMJeffrey G. Masek
Jeffrey G. Masek
Zhe ZhuZhe Zhu
Zhe Zhu

1 March 2016 in Remote Sensing of Environment
Verified
Journal Article
Open access
NMN. Mueller
N. Mueller
ALA. Lewis
A. Lewis
DRD. Roberts
D. Roberts
SRS. Ring
S. Ring
RMR. Melrose
R. Melrose
AIA. Ip
A. Ip
Following extreme flooding in eastern Australia in 2011, the Australian Government established a programme to improve access to flood information across Australia. As part of this, a project was undertaken to map the extent of surface water across Australia using the multi-decadal archive of Landsat satellite imagery. A water detection algorithm was used based on a decision tree classifier, and a comparison methodology using a logistic regression. This approach provided an understanding of the confidence in the water observations. The results were used to map the presence of surface water across the entire continent from every observation of 27years of satellite imagery. The Water Observation from Space (WOfS) product provides insight into the behaviour of surface water across Australia through time, demonstrating where water is persistent, such as in reservoirs, and where it is ephemeral, such as on floodplains during a flood. In addition the WOfS product is useful for studies of wetland extent, aquatic species behaviour, hydrological models, land surface process modelling and groundwater recharge. This paper describes the WOfS methodology and shows how similar time-series analyses of nationally significant environmental variables might be conducted at the continental scale

28 August 2018 in Remote Sensing
Verified
Journal Article
Open access
PDF file
JDJohn Dwyer
John Dwyer
DRDavid Roy
David Roy
BSBrian Sauer
Brian Sauer
CJCalli B. Jenkerson
Calli B. Jenkerson
Hankui ZhangHankui Zhang
Hankui Zhang
LLLeo Lymburner
Leo Lymburner
Data that have been processed to allow analysis with a minimum of additional user effort are often referred to as Analysis Ready Data (ARD). The ability to perform large scale Landsat analysis relies on the ability to access observations that are geometrically and radiometrically consistent, and have had non-target features (clouds) and poor quality observations flagged so that they can be excluded. The United States Geological Survey (USGS) has processed all of the Landsat 4 and 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) archive over the conterminous United States (CONUS), Alaska, and Hawaii, into Landsat ARD. The ARD are available to significantly reduce the burden of pre-processing on users of Landsat data. Provision of pre-prepared ARD is intended to make it easier for users to produce Landsat-based maps of land cover and land-cover change and other derived geophysical and biophysical products. The ARD are provided as tiled, georegistered, top of atmosphere and atmospherically corrected products defined in a common equal area projection, accompanied by spatially explicit quality assessment information, and appropriate metadata to enable further processing while retaining traceability of data provenance.

1 April 2019 in Remote Sensing of Environment
Verified
Journal Article
Open access
Zhe ZhuZhe Zhu
Zhe Zhu
MWMichael Wulder
Michael Wulder
DRDavid P. Roy
David P. Roy
CWCurtis E. Woodcock
Curtis E. Woodcock
MHMatthew C. Hansen
Matthew C. Hansen
TSTed A. Scambos
Ted A. Scambos

1 December 2017 in Remote Sensing of Environment
Verified
Journal Article
Open access
ALAdam Lewis
Adam Lewis
SOSimon Oliver
Simon Oliver
LLLeo Lymburner
Leo Lymburner
BEBen Evans
Ben Evans
LWLesley Wyborn
Lesley Wyborn
LWLan-Wei Wang
Lan-Wei Wang