Select Publications
Journal articles
2024, 'Tracking landscape scale vegetation change in the arid zone by integrating ground, drone and satellite data', Remote Sensing in Ecology and Conservation, 10, pp. 374 - 387, http://dx.doi.org/10.1002/rse2.375
,2022, 'Assessing the Accuracy of Landsat Vegetation Fractional Cover for Monitoring Australian Drylands', Remote Sensing, 14, http://dx.doi.org/10.3390/rs14246322
,2022, 'Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission', Remote Sensing of Environment, 270, http://dx.doi.org/10.1016/j.rse.2021.112845
,2021, 'Refining medium resolution fractional cover for arid Australia to detect vegetation dynamics and wind erosion susceptibility on longitudinal dunes', Remote Sensing of Environment, 265, http://dx.doi.org/10.1016/j.rse.2021.112647
,2021, 'Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems', Remote Sens Ecol Conserv, n/a, http://dx.doi.org/10.1002/rse2.228
,2021, 'Remote sensing of trophic cascades: multi-temporal landsat imagery reveals vegetation change driven by the removal of an apex predator', Landscape Ecology, 36, pp. 1341 - 1358, http://dx.doi.org/10.1007/s10980-021-01206-w
,2020, 'Modelling canopy gap probability, foliage projective cover and crown projective cover from airborne lidar metrics in Australian forests and woodlands', Remote Sensing of Environment, 237, http://dx.doi.org/10.1016/j.rse.2019.111520
,2019, 'The response of vegetation cover and dune activity to rainfall, drought and fire observed by multitemporal satellite imagery', Earth Surface Processes and Landforms, 44, pp. 2957 - 2967, http://dx.doi.org/10.1002/esp.4721
,2019, 'Ultra-high spatial resolution fractional vegetation cover from unmanned aerial multispectral imagery', International Journal of Applied Earth Observation and Geoinformation, 78, pp. 14 - 24, http://dx.doi.org/10.1016/j.jag.2019.01.013
,2018, 'Relating foliage and crown projective cover in Australian tree stands', Agricultural and Forest Meteorology, 259, pp. 39 - 47, http://dx.doi.org/10.1016/j.agrformet.2018.04.016
,2017, '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, pp. 86 - 96, http://dx.doi.org/10.1016/j.jag.2017.02.004
,2016, 'Comparing Landsat water index methods for automated water classification in eastern Australia', Remote Sensing of Environment, 175, pp. 167 - 182, http://dx.doi.org/10.1016/j.rse.2015.12.055
,2016, 'Large-Area, High-Resolution Tree Cover Mapping with Multi-Temporal SPOT5 Imagery, New South Wales, Australia', Remote Sensing, 8, pp. 515 - 515, http://dx.doi.org/10.3390/rs8060515
,2016, 'Remote Sensing Measures Restoration Successes, but Canopy Heights Lag in Restoring Floodplain Vegetation', Remote Sensing, 8, pp. 542 - 542, http://dx.doi.org/10.3390/rs8070542
,2014, '26Al/10Be dating of an aeolian dust mantle soil in western New South Wales, Australia', Geomorphology, 219, pp. 201 - 212, http://dx.doi.org/10.1016/j.geomorph.2014.05.007
,2013, 'Cloud and cloud-shadow detection in SPOT5 HRG imagery with automated morphological feature extraction', Remote Sensing, 6, pp. 776 - 800, http://dx.doi.org/10.3390/rs6010776
,2013, 'A water index for SPOT5 HRG satellite imagery, New South Wales, Australia, determined by linear discriminant analysis', Remote Sensing, 5, pp. 5907 - 5925, http://dx.doi.org/10.3390/rs5115907
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