@article {bnh-5056, title = {Limitations of high resolution satellite stereo imagery for estimating canopy height in Australian tropical savannas}, journal = {International Journal of Applied Earth Observation and Geoinformation}, volume = {75}, year = {2019}, month = {03/2019}, pages = {12}, chapter = {83}, abstract = {

Obtaining reliable measures of tree canopy height across large areas is a central element of forest inventory and carbon accounting. Recent years have seen an increased emphasis on the use of active sensors like Radar and airborne LiDAR (light detection and scanning) systems to estimate various 3D characteristics of canopy and crown structure that can be used as predictors of biomass. However, airborne LiDAR data are expensive to acquire, and not often readily available across large remote landscapes. In this study, we evaluated the potential of stereo imagery from commercially available Very High Resolution (VHR) satellites as an alternative for estimating canopy height variables in Australian tropical savannas, using a semi-global dense matching (SGM) image-based technique. We assessed and compared the completeness and vertical accuracy of extracted canopy height models (CHMs) from GeoEye 1 and WorldView 1 VHR satellite stereo pairs and summarised the factors influencing image matching effectiveness and quality.

Our results showed that stereo dense matching using the SGM technique severely underestimates tree presence and canopy height. The highest tree detection rates were achieved by using the near-infrared (NIR) band of GE1 (8{\textendash}9\%). WV1-GE1 cross-satellite (mixed) models did not improve the quality of extracted canopy heights. We consider these poor detection rates and height retrievals to result from: i) the clumping crown structure of the dominant Eucalyptus spp.; ii) their vertically oriented leaves (affecting the bidirectional reflectance distribution function); iii) image band radiometry and iv) wind induced crown movement affecting stereo-pair point matching. Our detailed analyses suggest that current commercially available VHR satellite data (0.5 m resolution) are not well suited to estimating canopy height variables, and therefore above ground biomass (AGB), in Eucalyptus dominated north Australian tropical savanna woodlands.

}, keywords = {canopy height, Satellite, Savanna, Stereo}, doi = {10.1016/j.jag.2018.10.021}, url = {https://www.sciencedirect.com/science/article/pii/S0303243418308390}, author = {Grigorijs Goldbergs and Stefan Maier and Shaun R Levick and Andrew C. Edwards} } @article {bnh-4399, title = {A comparison and validation of satellite-derived fire severity mapping techniques in fire prone north Australian savannas: Extreme fires and tree stem mortality}, journal = {Remote Sensing of Environment}, volume = {206}, year = {2018}, month = {03/2018}, pages = {287-299}, chapter = {287}, abstract = {

Severe fires in tropical savanna systems are recognised as incurring significant impacts on a variety of ecological attributes, including woody vegetation structure and greenhouse gas emissions. However, knowledge of the frequency and extent of severe fires is restricted given challenges associated with the development of reliable remotely sensed mapping procedures. This study takes advantage of three wildfires, 900{\textendash}5300\ km2\ in extent, containing very severely affected areas, occurring in semi-evergreen, eucalypt-dominated, tropical Australian savanna, which resulted in significant areas of complete canopy scorch, very significant tree stem mortality (24{\textendash}55\%), and associated loss of living above ground biomass (47{\textendash}69\%) at respective sites. Although increased map scale is generally considered to improve the reliability of fire severity mapping, our analysis found \>\ 90\% agreement between Landsat and MODIS-derived burnt area mapping, and \>\ 80\% for binary (severe vs. non-severe) fire severity mapping. Mapping of internal fire (unburnt) patchiness was enhanced with finer resolution Landsat imagery, but the much longer orbital return cycle precluded its use at two of the three sites given extended cloudy conditions. Application of an automated MODIS-derived fire severity mapping algorithm (overall reliability in 2015\ =\ 75\%) calibrated for generalised north Australian savanna conditions, suggests that 15\% and 12\% of Australia{\textquoteright}s 1.3\ M\ km2\ tropical savannas region were burnt by severe fires in 2015 and 2016, respectively. The study illustrates the potential for MODIS-derived fire severity mapping, the impacts of very severe fires on stand structure, and ongoing challenges associated with deriving reliable fire severity mapping products in Australian savanna systems.

}, doi = {10.1016/j.rse.2017.12.038}, url = {http://www.sciencedirect.com/science/article/pii/S0034425717306223}, author = {Andrew C. Edwards and Jeremy Russell-Smith and Stefan Maier} } @article {bnh-4424, title = {Efficiency of Individual Tree Detection Approaches Based on Light-Weight and Low-Cost UAS Imagery in Australian Savannas}, journal = {Remote Sensing}, volume = {10}, year = {2018}, month = {01/2018}, abstract = {
The reliability of airborne light detection and ranging (LiDAR) for delineating individual trees and estimating aboveground biomass (AGB) has been proven in a diverse range of ecosystems, but can be difficult and costly to commission. Point clouds derived from structure from motion (SfM) matching techniques obtained from unmanned aerial systems (UAS) could be a feasible low-cost alternative to airborne LiDAR scanning for canopy parameter retrieval. This study assesses the extent to which SfM three-dimensional (3D) point clouds{\textemdash}obtained from a light-weight mini-UAS quadcopter with an inexpensive consumer action GoPro camera{\textemdash}can efficiently and effectively detect individual trees, measure tree heights, and provide AGB estimates in Australian tropical savannas. Two well-established canopy maxima and watershed segmentation tree detection algorithms were tested on canopy height models (CHM) derived from SfM imagery. The influence of CHM spatial resolution on tree detection accuracy was analysed, and the results were validated against existing high-resolution airborne LiDAR data. We found that the canopy maxima and watershed segmentation routines produced similar tree detection rates (~70\%) for dominant and co-dominant trees, but yielded low detection rates (\<35\%) for suppressed and small trees due to poor representativeness in point clouds and overstory occlusion. Although airborne LiDAR provides higher tree detection rates and more accurate estimates of tree heights, we found SfM image matching to be an adequate low-cost alternative for the detection of dominant and co-dominant tree stands.
}, keywords = {biomass, canopy height, low-cost UAS, segmentation, single tree detection, structure from motion}, doi = {10.3390/rs10020161 }, url = {http://www.mdpi.com/2072-4292/10/2/161/htm}, author = {Grigorijs Goldbergs and Stefan Maier and Shaun R Levick and Andrew C. Edwards} } @article {BF-3787, title = {Modelling the potential for prescribed burning to mitigate carbon emissions from wildfires in fire-prone forests of Australia}, year = {2012}, url = {http://www.publish.csiro.au/paper/WF11023.htm}, author = {Gill, A. Malcolm and Hutley, LB and Garry D. Cook and Jeremy Russell-Smith and Stefan Maier and Roxburgh, Stephen and Meyer, C.P. (Mick) and Damian J. Barrett and Keith, H and Ross Bradstock and Geoffrey J. Cary and Owen Price and Williams, RJ} } @article {BF-2415, title = {Improving estimates of savanna burning emissions for greenhouse accounting in northern Australia: limitations, challenges, applications}, journal = {International Journal of Wildland Fire}, volume = {18}, year = {2009}, month = {2009}, pages = {1}, abstract = {Although biomass burning of savannas is recognised as a major global source of greenhouse gas emissions, quantification remains problematic with resulting regional emissions estimates often differing markedly. Here we undertake a critical assessment of Australia{\textquoteright}s National Greenhouse Gas Inventory (NGGI) savanna burning emissions methodology. We describe the methodology developed for, and results and associated uncertainties derived from, a landscape-scale emissions abatement project in fire-prone western Arnhem Land, northern Australia. The methodology incorporates (i) detailed fire history and vegetation structure and fuels type mapping derived from satellite imagery; (ii) field-based assessments of fuel load accumulation, burning efficiencies (patchiness, combustion efficiency, ash retention) and N : C composition; and (iii) application of standard, regionally derived emission factors. Importantly, this refined methodology differs from the NGGI by incorporation of fire seasonality and severity components, and substantial improvements in baseline data. We consider how the application of a fire management program aimed at shifting the seasonality of burning (from one currently dominated by extensive late dry season wildfires to one where strategic fire management is undertaken earlier in the year) can provide significant project-based emissions abatement. The approach has wider application to fire-prone savanna systems dominated by anthropogenic sources of ignition.}, doi = {10.1071/WF08009}, author = {Jeremy Russell-Smith and Murphy, Brett P. and Meyer, C.P. (Mick) and Garry D. Cook and Stefan Maier and Andrew C. Edwards and Schatz, Jon and Brocklehurst, Peter} }