Dr Adrian Fisher

Dr Adrian Fisher

Visiting Fellow
Field of Research
Remote Sensing, Geomorphology

Adrian Fisher is a geographer with the Joint Remote Sensing Research Program (JRSRP), based in the Centre for Ecosystem Science (CES). He is funded by the NSW Office of Environment and Heritage (OEH) to conduct remote sensing research, collaborating with researchers from the University of Queensland, OEH, CES, and the Queensland Department of Environment and Science. His research mainly involves large area mapping of vegetation structure, using satellite and airborne data, though he is also interested in using remote sensing data to examine the geomorphic evolution of Australia’s deserts.


Relating foliage and crown projective cover in Australian tree stands. Agricultural and Forest Meteorology, 259 39-57, 2018. doi:10.1016/j.agrformet.2018.04.016

Mapping trees in high resolution imagery across large areas using locally variable thresholds guided by medium resolution tree maps. International Journal of Applied Earth Observation and Geoinformation, 58 86-96, 2017. doi:10.1016/j.jag.2017.02.004

Comparing Landsat water index methods for automated water classification in eastern Australia. Remote Sensing of Environment, 175 167-182, 2016. doi:10.1016/j.rse.2015.12.055

Large-area, high-resolution tree cover mapping with multi-temporal SPOT5 imagery, New South Wales, Australia. Remote Sensing, 8 6: 515.1-515.23, 2016. doi:10.3390/rs8060515

Remote sensing measures restoration successes, but canopy heights lag in restoring floodplain vegetation. Remote Sensing, 8 7: 542.1-542.19, 2016. doi:10.3390/rs8070542

26Al/10Be dating of an aeolian dust mantle soil in western New South Wales, Australia. Geomorphology, 219 201-212, 2014. doi:10.1016/j.geomorph.2014.05.007

Cloud and cloud-shadow detection in SPOT5 HRG imagery with automated morphological feature extraction. Remote Sensing, 6 1: 776-800, 2014. doi:10.3390/rs6010776

A water index for SPOT5 HRG satellite imagery, New South Wales, Australia, determined by linear discriminant analysis. Remote Sensing, 5 11: 5907-5925, 2014. doi:10.3390/rs5115907


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