@article {bnh-7029, title = {Estimating carbon stocks and biomass in surface fuel layers}, number = {586}, year = {2020}, month = {07/2020}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

In this report we describe a simple model that can be used to estimate carbon

(C) stocks in surface fuel layers for C accounting purposes. We used empirical data collected from dry sclerophyll forests from a range of sites in Victoria, New South Wales and the Australian Capital Territory. This information was used to develop an easy-to-use tool to improve estimates of C emissions from prescribed burning. Models developed using data from each state have been reported previously {\textendash} here we present an evaluation of a universal model developed using the complete empirical dataset for all sites in all three states, and two separate models ({\textquoteleft}universal{\textquoteright} models) developed using data from all the sites burnt by prescribed fires and nearby unburnt sites.

Samples of the near-surface fuel layer were separated into three fractions: fine fuel (\<9 mm diameter), intact leaves, and twigs and other material such as fruits, flowers and bark. The dry weight and C content of each fraction was determined. To model biomass and C content of surface fuels, a mixture design was used. For each site, the proportion of the total fuel load of each of the three surface litter fractions was used as an independent factor (x1, x2, and x3), and the corresponding total fuel load (t ha-1) or C content (t C ha-1) was used as the dependent factor. A response surface was fitted to the mixture design using a Generalised Blending Mixture model (GBM) and a polynomial equation for each response was generated by running the GBM with varying numbers of terms included in the response surface equation. To determine the best fitting equation, Akaike information criterion (AICc) was used as a measure of the relative quality of the response surface for a given set of data in relation to other model iterations. Data were randomly assigned into an 80:20 split for training and testing of the response surface of the model. Models were also validated against a second set of data collected from high and low productivity forest sites. This additional information improved data spread and, thus, model testing.

The response surfaces fitted to data showed reasonable agreement with the data but the universal model (burnt and unburnt data from all sites combined) tended to be unreliable with both over- and underpredictions depending upon which dataset was being used for testing or validation. Universal models created using data from all burnt or unburnt sites were better than other trained models for predicting of biomass or C content in relation to fire history.

}, keywords = {biomass, carbon stocks, estimates, surface fuel layers}, issn = {586}, author = {Danica Parnell and Malcolm Possell and Bell, Tina} } @article {bnh-6222, title = {A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing}, journal = {Remote Sensing}, volume = {11}, year = {2019}, month = {09/2019}, abstract = {

Characteristics describing below canopy vegetation are important for a range of forest ecosystem applications including wildlife habitat, fuel hazard and fire behaviour modelling, understanding forest recovery after disturbance and competition dynamics. Such applications all rely on accurate measures of vegetation structure. Inherent in this is the assumption or ability to demonstrate measurement accuracy. 3D point clouds are being increasingly used to describe vegetated environments, however limited research has been conducted to validate the information content of terrestrial point clouds of understory vegetation. This paper describes the design and use of a field frame to co-register point intercept measurements with point cloud data to act as a validation source. Validation results show high correlation of point matching in forests with understory vegetation elements with large mass and/or surface area, typically consisting of broad leaves, twigs and bark 0.02 m diameter or greater in size (SfM, MCC 0.51{\textendash}0.66; TLS, MCC 0.37{\textendash}0.47). In contrast, complex environments with understory vegetation elements with low mass and low surface area showed lower correlations between validation measurements and point clouds (SfM, MCC 0.40 and 0.42; TLS, MCC 0.25 and 0.16). The results of this study demonstrate that the validation frame provides a suitable method for comparing the relative performance of different point cloud generation processes

}, keywords = {3D remote sensing, biomass, forest measurement, structure from motion, terrestrial laser scanning, validation, vegetation structure}, doi = {https://doi.org/10.3390/rs11182118}, url = {https://www.mdpi.com/2072-4292/11/18/2118}, author = {Samuel Hillman and Luke Wallace and Karin Reinke and Bryan Hally and Simon Jones and Daisy Saldias} } @mastersthesis {bnh-5778, title = {Remote sensing of tree structure and biomass in north Australia mesic savanna}, volume = {Philosophy}, year = {2019}, month = {05/2019}, school = {Charles Darwin Unviersity}, type = {Doctorate}, address = {Melbourne}, abstract = {

The quantification of Above Ground Biomass (AGB) plays a major role in issues related to greenhouse gas emissions and carbon sequestration, pertaining to global warming and the effects of climate change. In Eucalyptus miniata/tetrodonta dominated open-forest in Australia{\textquoteright}s northern tropical savanna, AGB mapping is challenging, due to the complex structure of the canopy stand, highly dynamic woody cover, vast spatial extent, vulnerability to climatic effects and the impacts of extensive fire.\ 

Remotely sensed data allow for the mapping, quantification and monitoring of AGB at various scales. Quantification of AGB in tropical savanna by common medium and coarse spatial resolution optical sensor data is inappropriate to monitor finer-grained ecological processes responsible for measuring carbon stocks at an individual tree level and are limited in detecting vertical vegetation structure. There is limited research on the utility of airborne LiDAR (Light Detection and Ranging) and alternative high resolution (\< 0.5 m) remote sensing tools for Australian savanna structural assessment. The main goal of this research is to evaluate the efficiency of small footprint airborne LiDAR and determine whether Unmanned Aerial Systems (UAS) and Very High Resolution (VHR) satellite stereo remote sensing data can be used to extract tree biophysical and vertical structural parameters for the purposes of accurately estimating biomass stocks in Australian mesic savannas.\ 

This study utilized a two-phase LiDAR analysis procedure integrating both Individual Tree Detection (ITC) and Area-Based Approaches (ABA) to better understand how the uncertainty of biomass estimation varies with scale. Regression analysis was applied on remote sensing data to develop biomass estimation models based on tree height allometry. This study demonstrated that where field-plot data are spatially limited, it is possible to use a hierarchical integration approach based on AGB uncertainty calculation and calibration to upscale AGB estimates from individual trees to broader landscapes.

}, keywords = {biomass, greenhouse gas, Lidar, northern Australia, remote sensing, tree structure}, url = {https://researchers.cdu.edu.au/en/studentTheses/remote-sensing-of-tree-structure-and-biomass-in-north-australia-m}, author = {Grigorijs Goldbergs} } @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} } @mastersthesis {bnh-6701, title = {Initiation of smouldering combustion in biomass}, year = {2018}, month = {05/2018}, school = {University of Adelaide}, address = {Adelaide}, abstract = {

Wildfires are naturally occurring phenomena that result in significant and catastrophic damage. Due to climate change, there has been a significant increase in the frequency, severity, and extent of wildfires. Therefore, there is a growing need to mitigate wildfire risk. In order to help mitigate the risk of wildfires, greater understanding is required. One particular gap in knowledge is the impact of smouldering combustion of potential fuel on wildfires. This thesis focuses on combustion of fuel beds in wildfires. Specifically, the thesis targets smouldering combustion. Smouldering combustion is a common type of combustion regime in wildfires and hazard reduction burning (a wildfire mitigation measure). Smouldering is a slow and low-temperature form of combustion, which shows no flame. Smouldering is a serious hazard because of its low ignition temperature, which makes it particularly relevant to fire initiation and spread. Smouldering plays a vital role in wildfires, as many forest biomass fuels such as grass, leaves and coarse woody debris are prone to smoulder. Most previous studies of smouldering combustion have only been carried out on polyurethane foam, due to its importance for residential fires. However, smouldering has been scarcely investigated from the point of view of wildfires. For example, smouldering combustion of forest fuel is scarcely studied. Hence, the project aims to develop a greater understanding of the initiation of smouldering combustion in biomass under different conditions with an emphasis on wildfire. Locating smouldering combustion in wildfires and hazard reduction burning is difficult and time-consuming, as there is no effective method to identify the initiation of smouldering combustion in biomass fuel beds. It is critical to know when and where smouldering combustion in a biomass fuel bed starts, as smouldering combustion could transition to flaming combustion under certain conditions. Radiation is one of the important heat transfer mechanisms in wildfires; however, there are few studies on smouldering combustion in biomass fuel beds started by external radiant heat flux. Although oxidiser flow rate and oxygen concentration have significant in influences on the propagation of smouldering front, their effects on the initiation of smouldering combustion in biomass fuels are not well understood. Hence, the effects of oxidiser flow rate and oxygen concentration on the initiation of smouldering combustion are investigated. Fuels in a forest are diverse, and it is essential to have a better understanding of what effects forest fuels have on smouldering combustion. Thus, the effects of plant species and plant parts on the initiation of smouldering in biomass fuel beds are also investigated. Within this framework, the work presented in this thesis can be split into two main topics: 1. Conditions required to initiate smouldering combustion in bio- mass fuel beds The required radiant heat flux and air flow rate for the initiation of smouldering and flaming combustion in a biomass fuel bed are investigated in an experimental testing rig. This investigation identifies and quantifies smouldering and flaming combustion in a biomass fuel bed based on the measurements of temperature, product gas concentration and mass change, and the required radiant heat flux and air flow rate for the initiation of smouldering and flaming combustion are determined. The effects of heating time and oxygen concentration on the initiation of radiation-aided and self-sustained smouldering combustion are investigated in the same testing rig. In this experimental study, the differences between radiation-aided and self-sustained smouldering combustion are characterised based on the measurements of temperature, product gas concentration and mass change, and the required heating time and oxygen concentration for radiation-aided and self-sustained smouldering combustion are determined. 2. Factors that influence smouldering combustion in biomass fuel beds The results from the first topic reveal that oxygen availability has significant effects on the initiation of smouldering combustion in a biomass fuel bed. The air permeability of a biomass fuel bed determines oxygen availability in that fuel bed. Hence, the air permeability of natural forest fuel beds is investigated in an air permeability testing rig. In this study, the air permeability of natural forest fuel beds is determined using experimental and theoretical methods. A comparison between the experimental and theoretical methods is made. The effects of Euca- lyptus species and plant parts on smouldering combustion are also investigated. In this study, the different plant parts from different Eucalyptus species are characterised based on the results of the thermogravimetric and ultimate analyses. The results of this study show that the differences among the different plant parts from different Eucalyptus can be characterised and quantified based on the results of the thermogravimetric and ultimate analyses. It is also found that Eucalyptus species and plant parts have significant effects on smouldering combustion. Although this thesis covers a series of experimental studies of the initiation of smouldering combustion in biomass fuel beds. There are still many important factors to be considered. For examples, the thesis focuses on small-scale laboratory experiments to better understand the fundamental studies of smouldering combustion of biomass. However, the real-world conditions could be much more complex. For example, forest fuel beds are composed with fuel particles with various sizes and shapes. These factors also have effects on smouldering combustion.

}, keywords = {biomass, Bushfire, smouldering combustion}, url = {https://digital.library.adelaide.edu.au/dspace/handle/2440/114254}, author = {Wang, Houzhi} }