@article {bnh-8355, title = {Representing vapour and capillary rise from the soil improves a leaf litter moisture model}, journal = {Journal of Hydrology}, volume = {612}, year = {2022}, month = {06/2022}, abstract = {

Litter moisture content plays a critical role in fire danger rating systems and forest ecosystems. Soil moisture content has been proposed to affect litter moisture due to vapour flux and capillary rise from the soil. However, few models consider soil water content when predicting litter moisture, and to our knowledge, no model includes capillary fluxes. In this study, we represented soil moisture coupling in a physics-based litter moisture prediction model by describing the vapour and capillary fluxes from the soil to litter. We aimed to evaluate if litter moisture predictions can be improved by incorporating the hydrological process at the soil-litter interface and explored the possible role of soil moisture in litter moisture simulations. Three model versions were compared against observations at a dry and wet experimental site in Australia: the original physics-based model, a model version extended with soil vapour flux only, and a version that incorporates both soil vapour flux and capillary rise. The simulation results suggest that soil moisture considerably influences litter moisture through soil vapour flux and capillary rise, which can lead to more than 10\% of oven-dried weight, particularly under wet soil conditions. The corresponding model showed the best performance in comparison with field observations. The contribution of upward soil moisture fluxes was small after long dry and warm periods but noticeable during more moist periods. Further research is needed to evaluate the revised model for a broader range of weather, soil and litter conditions.

}, keywords = {capillary rise, fuel moisture content, leaf litter, Soil moisture, vapour flux}, doi = {https://doi.org/10.1016/j.jhydrol.2022.128087}, url = {sciencedirect.com/science/article/abs/pii/S002216942200662X}, author = {Li Zhao and Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-7761, title = {The influence of soil moisture on surface and sub-surface litter fuel moisture simulation at five Australian sites}, journal = {Agricultural and Forest Meteorology}, volume = {298-299}, year = {2021}, month = {03/2021}, abstract = {

Fuel moisture content (FMC) of the litter is a critical factor determining fire ignition and spread and is an important input for most fire behaviour prediction models. Several models, ranging from empirical regression functions to physics-based models, have been developed to forecast litter FMC. Soil moisture below the litter layer has been shown to influence litter FMC, but few models explicitly consider its effect. This study aimed to evaluate how soil moisture content may affect litter FMC by coupling soil moisture as a boundary condition to the physics-based {\textquoteleft}Koba{\textquoteright} model, which simulates radiation, energy and moisture fluxes in the surface and subsurface litter layer. The coupled model was tested at five sites in Victoria, Australia, where litter FMC values were recorded continuously during 2014-2015 using calibrated fuel stick sensors. Two versions of the model were compared against the observations: an uncoupled model and a model version accounting for the vapour flux from soil to litter. The simulation results show that the influence of soil moisture depends on environmental conditions. Soil moisture appeared to have a minor influence on FMC when both soil and litter are dry, but a stronger influence when the soil is relatively wet. Correspondingly, the coupled model explained observed FMC better than the uncoupled model for the two wetter study sites. As expected, the subsurface litter in contact with the soil appeared more sensitive to soil moisture conditions than the surface litter. The influence of soil vapour flux on litter FMC can be considerable during the transition from wet to dry litter and soil conditions. This has implications for hazard reduction burning, which is typically planned to take advantage of transitional fuel moisture conditions. Further research is needed to understand the influence of the structure and thickness of litter on the importance of soil vapour flux.

}, keywords = {Coupled model, Dead fuel, forecast, fuel moisture content, Soil moisture}, doi = {https://doi.org/10.1016/j.agrformet.2020.108282}, url = {https://www.sciencedirect.com/science/article/abs/pii/S0168192320303841?dgcid=coauthor}, author = {Li Zhao and Marta Yebra and Albert van Dijk and Geoffrey J. Cary and Stuart Matthews and Gary J. Sheridan} } @article {bnh-7390, title = {Mapping bushfire hazard and impacts {\textendash} final project report}, number = {616}, year = {2020}, month = {10/2020}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Fuel condition (e.g. moisture content, horizontal and vertical continuity and the quantity or load) affect flammability and therefore is a key determinant of the ease of ignition and the spread rate of a fire. Many research institutions and management services are investing an important amount of resources on field-based fuel condition monitoring to understand its dynamics and support operational fire management activities. However, field sampling is expensive and time-consuming, sometimes subjective and implies also a delay time until the data are processed and made available. The Bushfire \& Natural Hazards CRC project {\textquoteleft}Mapping Bushfire Hazards and Impacts{\textquoteright} used cutting-edge technology to produce near-real-time spatial information on fuel condition, fire hazard and impact to support a wide range of fire risk management and response activities such as hazard reduction burning and pre-positioning firefighting resources and, in the longer term, the new Australian Fire Danger Rating System (AFDRS) given it considers fuel condition as ne of the key factors required to determine fire danger and support other decision -making.

The first phase of this project (2014-2017) involved the parallel investigation of several promising data sources and methods that can be categorised as either {\textquoteleft}in-field{\textquoteright} (grassland curing on-ground sensors and ground-based LiDAR laser scanning for fuel structure characterisation) or {\textquoteleft}national-scale{\textquoteright} (the Australian Flammability Monitoring System-AFMS, and the High-resolution Fire Risk and Impact (HiFRI) model-data fusion framework) methods. Generally, information derived from the national-scale methods appeared to represent enough accuracy and better return on investment and generated greater interest among end-users.

Consequently, over 2017-2020, this research project focused on ensuring the continuity of the AFMS but further developing the algorithms to estimate fuel moisture content (FMC), and through this, its acceptance and adoption. The AFMS provides information on FMC and flammability across Australia at 500m resolution every four days. It also displays information on soil moisture content near the surface (0-10 cm) and shallow soils (10-35 cm) as research outcomes from the project {\textquotedblleft}Improving land dryness measures and forecast{\textquotedblright}. Our research project also improved estimates of litter FMC by incorporating the effect of soil moisture content in existing physics-based models, developed a methodology to map fuel loads using satellite data and an objective and observation-based approach to assess fire danger that considers spatial data on the occurrence of actual fires as well as on fire factors that are already routinely produced every day for Australia.

The improved litter FMC, fuel load and fire danger retrieval algorithms and products derived from this project are not yet included in the AFMS nor generated at near real-time and across Australia. Further research and development is needed to make that step and providing landscape scale, cost-effective way to comprehensively monitor fuel condition and fire danger at such a broad scale. Consequently, future research should focus on developing a multi-sensor system that will display daily information on fire danger and fuel condition from whatever satellite sensor has collected an image over Australia, including high-resolution satellite imagery. This will improve the temporal and spatial resolution of the information we currently provide at the AFMS that will allow the identification of, for example, local fuel moisture gradients in the landscape that are currently not identifiable using the 500m pixel resolution of the product we currently serve in the AFMS.

The use of high-resolution satellite imagery will provide an unprecedented level of detail and accuracy when estimating fuel condition, bringing the system closer to use in operations. However, the data volumes and large compute resources required to store and generate these high-resolution products becomes a challenge. Consequently, future research should also focus on developing an alternative methodology for computing fuel condition that can provide up to date estimations by reducing the required storage and computing resources using state-of-the-art artificial intelligence algorithms.

}, keywords = {Bushfire, hazard, impacts, mapping}, issn = {616}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-5430, title = {Mapping Bushfire Hazard and Impacts Annual Report 2017-2018}, number = {462}, year = {2019}, month = {03/2019}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {
Understanding and predicting fire behaviour is a priority for fire services, land managers and sometimes individual businesses and residents. This is an\ enormous scientific challenge given bushfires are complex phenomena, with\ their behaviour and resultant severity driven\ by\ complicated interactions\ among living and dead vegetation, topography and weather conditions.\ A good understanding of fire risk across the landscape is critical in preparing\ and responding to bushfire events and managing fire regimes, and remote\ sensing data will enhance this understanding. However, the vast array of spatial\ data sources available is not being used ve\ ry effectively in fire management.\ This project uses remote sensing observations\ to\ produce spatial information on\ fire hazard and impacts needed by planners, land managers and emergency\ services\ to effectively manage fire at landscape scales. The group works\ closely with ACT Parks and Conservation Service and agencies beyond the\ ACT to better understand their procedures and information needs, comparing\ these with the spatial data and mapping methods that are readily available,\ and developing the next generation of mapping technologies to help them\ prepare and respond to bushfires.
}, keywords = {Bushfire, fire impacts, hazards, mapping fire}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-5928, title = {Mapping bushfire hazards and impacts annual report 2018-2019}, number = {511}, year = {2019}, month = {09/2019}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

This annual report is the output from the Bushfire and National Hazards CRC (BNHCRC), Project A1 {\textquoteleft}Mapping Bushfire Hazard and Impacts{\textquoteright}. It summarises the project objectives, introduces the team members as well as documents the project progress and outcomes during the financial year 2018/2019.

During this financial year we have:

  1. Worked on a comprehensive characterization of fire risk conditions through the integration of fire weather, dead Fuel Moisture Content (FMC) and total biomass into the Australian Flammability Monitoring System (AFMS);
  2. Worked on AFMS website version 3 that incorporated feedback on the trial utilisation of the data service;
  3. Evaluated the feasibility and benefits of the operational use of alternative satellite data in AFMS to ensure long-term data continuity;
  4. Coupled a process-based model that simulates litter fuel moisture and a distributed biophysical model (the Australian Water Resources Assessment system Landscape model) to predict dead fuel moisture content;
  5. Published six journal manuscripts, seventeen conference abstracts and one milestone reports with another one in preparation. We have also had eight appearances in the media;
  6. Hosted two international exchange visits and were approached by more than 30 domestic and international applicants for a PhD scholarship or postdoc position in bushfire research; and
  7. Submitted an application for utilisation funds from the BNHCRC to develop a high-resolution prototype version of AFMS.

Over the next year (2019-2020), this research project will focus on finishing the analysis on the fire risk index as well as using remote sensing data to derive spatial and temporal explicit fuel accumulation curves. In terms of utilization, we will liaise with Geoscience Australia (GA) on transitioning the AFMS as GA has agreed to be in charge of the long term operationalization and maintenance.

}, keywords = {bushfires, fire behavior, fire impacts, hazards, impacts, mapping}, issn = {511}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary and Li Zhao and Honghao Zeng} } @conference {bnh-6397, title = {Towards comprehensive characterisation of flammability and fire danger }, booktitle = {Bushfire and Natural Hazards CRC Research Day AFAC19}, year = {2019}, month = {12/2019}, address = {Melbourne}, abstract = {

Fire danger ratings inform the community and fire managing agencies of fire risk. Fire danger ratings are currently primarily based on fire danger indices (FDIs) calculated using methods that were developed many decades ago. The challenges and issues with these methods are well documented. We aimed to develop a more objective and observation-based approach to fire danger assessment that considers spatial data on the occurrence of actual fires as well as on fire factors that are already routinely produced every day for Australia. A preliminary assessment suggested a very good potential of the methodology to formally and objectively incorporate any new fire danger predictors. The method can be combined with forecasted rather than observed weather and fuel conditions to produce forward predictions of expected FDI.

}, keywords = {Fire danger rating, fire factors, risk managemnt}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Albert van Dijk and Marta Yebra and Geoffrey J. Cary and Sami Shah} } @article {bnh-5201, title = {Australian Flammability Monitoring System Version 1.0: User feedback and priorities for further development}, year = {2018}, month = {12/2018}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

In response to the information requirements expressed by end users, the Bushfire \& Natural Hazards CRC project {\textquoteleft}Mapping Bushfire Hazards and Impacts{\textquoteright} (Project A1) developed the Australian Flammability Monitoring System (AFMS)
website (version 1.0). The AFMS makes spatial information on fuel condition and flammability easier and faster to access.

This report summarises feedback received from end users and discusses priorities for future development that may potentially be addressed by the BNHCRC and the project team in future.

All end users involved in the project, and participating in several seminars and presentations featuring the AFMS, recognised the value of the system to improve fire management in Australia. However, they also identified some significant barriers to adoption by the Australian bushfire sector. Firstly, neither FMC nor FI are presently used in any models or systems. This means that the sector needs to explore the information and develop work processes for using it. Another key barrier is the timeliness of the system. It presently takes 15 days to acquire the satellite data, process and publish. This delay is too long to allow practitioners to trial the system during operations.

Consequently, future priorities for further development should focus on activities that will contribute to strengthening the usability of the AFMS and adoption. As a first step, we need to invest more time working with end users to develop specific operational applications and integrate the information displayed in the AFMS into current decision processes and tools (e.g. the ACT Parks and Conservation Service{\textquoteright}s Prescribe Burn Decision Tool). Meanwhile, we also need to improve timeliness, robustness, visual presentation and explanation of the information displayed on the AFMS website to make it easier for users to extract the important details.

The implementation of the AFMS into daily fire management operations will take fire management in Australia to a new level.

}, issn = {437}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-5102, title = {Estimating fire severity and carbon emissions over Australian tropical savannahs based on passive microwave satellite observations}, journal = {International Journal of Remote Sensing}, year = {2018}, month = {04/2018}, abstract = {

We investigated the use of a recently developed satellite-based vegetation optical depth (VOD) data set to estimate fire severity and carbon emission over Australian tropical savannahs. VOD is sensitive to the dynamics of all aboveground vegetation and available nearly every two days. For areas burned during 2003{\textendash}2010, we calculated the VOD change (ΔVOD) pre- and post-fire and the associated loss in the above ground biomass carbon. ΔVOD agreed well with the Normalized Burn Ratio change (ΔNBR) which is the metric used to estimate fire severity and carbon loss compared well with modelled emissions from the Global Fire Emissions Database (GFED). We found that the ΔVOD and ΔNBR are generally linearly related. The Pearson correlation coefficients (r) between VOD- and GFED-based fire carbon emissions for monthly and annual total estimates are very high, 0.92 and 0.96, respectively. A key feature of fire carbon emissions is the strong inter-annual variation, ranging from 21.1 Mt in 2010 to 84.3 Mt in 2004. This study demonstrates that a reasonable estimate of fire severity and carbon emissions can be achieved in a timely manner based on multiple satellite observations over Australian tropical savannahs, which can be complementary to the currently used approaches.

}, doi = {https://doi.org/10.1080/01431161.2018.1460507}, url = {https://www.tandfonline.com/doi/abs/10.1080/01431161.2018.1460507}, author = {Xi Chen and Y.Y Liu and Jason P. Evans and R.M. Parinussa and Albert van Dijk and Marta Yebra} } @article {bnh-5217, title = {Evaluation of the feasibility and benefits of operational use of alternative satellite data in the Australian Flammability Monitoring System to ensure long-term data continuity}, year = {2018}, month = {12/2018}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

The Australian Flammability Monitoring System (AFMS) is the first, continental-scale prototype web service providing spatial information on Live Fuel Moisture Content (FMC) and landscape flammability conditions derived from satellite observations. The system uses data from the MODIS (MODerate resolution Imaging Spectrometer) instruments on board the Terra and Aqua satellites, providing estimates of FMC and flammability over a fortnight leading up to the day of interest and at 500 m spatial resolution. The Terra and Aqua satellites have already exceeded the expected lifetime and, at some point in the not-too-distant future, will become inoperative.

To support the AFMS continuity and redundancy strategy, we evaluate the feasibility and relative benefits of using alternative remote sensing imagery in the AFMS to provide finer spatial and temporal resolutions. The evaluated data sources include the geostationary Japanese Himawari-8 satellite (10min, 2km), the European Sentinel-2 (5 days, 20 m), the Landsat (16 days, 30m) and VIIRS (daily, 750 m) satellites.

We use Radiative Transfer Models to build a database of simulated spectra for the different studied sensors and corresponding to different FMC conditions. The database is then used to test the suitability of the different sensor to retrieve FMC based on their different spectral characteristics and goodness of retrieval (e.g. r2 and RMSE between retrieved and modelled).

VIIRS obtained the highest accuracy retrieval (r2=0.8, RMSE=19\%, n=6178) followed by Sentinel-2 (r2=0.8, RMSE=23, n=6178), Landsat-8 (r2=0.8, RMSE=24, n=6178) and Himawari-8 (r2=0.7, RMSE=24, n=6178). These results were expected as VIIRS has a larger number of sensor bands (5 bands) in the Short Wave Infrared (SWIR) followed by Sentinel-2 (3 bands), Landsat and Himawari-8 (two bands each).

VIIRS, therefore, is likely the best candidate to ensure the AFMS website data provision continuity. Sentinel-2 (3 bands) and Himawari-8 are the best second and third candidates that obtain similar accuracies while increasing the spatial (Sentinel-2, 20m) and temporal (Himawari-8, 10 minutes) resolutions of the products displayed in the AFMS.

Future work will focus on integrating estimates from these different data sources to better support a range of fire management activities such as prescribed burning and pre-positioning of firefighting resources and inform the future National Fire Danger Rating System.

}, issn = {448}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-4586, title = {A fuel moisture content and flammability monitoring methodology for continental Australia based on optical remote sensing}, journal = {Remote Sensing of Environment}, volume = {212}, year = {2018}, month = {06/2018}, pages = {12}, chapter = {260}, abstract = {

Fuel Moisture Content (FMC) is one of the primary drivers affecting fuel flammability that lead to fires. Satellite observations well-grounded with field data over the highly climatologically and ecologically diverse Australian region served to estimate FMC and flammability for the first time at a continental-scale. The methodology includes a physically-based retrieval model to estimate FMC from MODIS (Moderate Resolution Imaging Spectrometer) reflectance data using radiative transfer model inversion. The algorithm was evaluated using 360 observations at 32 locations around Australia with mean accuracy for the studied land cover classes (grassland, shrubland, and forest) close to those obtained elsewhere (r2 = 0.58, RMSE = 40\%) but without site-specific calibration. Logistic regression models were developed to generate a flammability index, trained on fire events mapped in the MODIS burned area product and four predictor variables calculated from the FMC estimates. The selected predictor variables were actual FMC corresponding to the 8-day and 16-day period before burning; the same but expressed as an anomaly from the long-term mean for that date; and the FMC change between the two successive 8-day periods before burning. Separate logistic regression models were developed for grassland, shrubland and forest. The models obtained an {\textquotedblleft}Area Under the Curve{\textquotedblright} calculated from the Receiver Operating Characteristic plot method of 0.70, 0.78 and 0.71, respectively, indicating reasonable skill in fire risk prediction.

}, keywords = {Fire occurrence, Fire risk, Forests., GEOPROSAIL inversion, Grasslands, MODIS, PROSAIL inversion, Shrubs}, doi = {10.1016}, url = {https://www.sciencedirect.com/science/article/pii/S0034425718302116$\#$.WvZrg57h8og.twitter}, author = {Marta Yebra and Xingwen Quan and David Ria{\~n}o and Pablo Rozas Larraondo and Albert van Dijk and Geoffrey J. Cary} } @conference {bnh-4775, title = {A lidar-derived fuel map for the ACT}, booktitle = {AFAC18}, year = {2018}, month = {09/2018}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Perth}, abstract = {

Many Australian fire managers rely on fuel maps derived from vegetation classifications and time-since-fire via an accumulation curve (e.g. Phoenix Rapidfire). However fuel maps derived using this method lack potentially critical information about pockets of high and low fuel loads. This is important because a poor understanding of fuels was found to be a critical factor in investigations of both the Margaret River and Lancefield prescribed burn escapes. A potential solution for this problem is the use of LiDAR to create spatially-explicit fuel information.

A LiDAR dataset covering the whole of the ACT was flown over a number of months in 201516 using the LAS 1.4 format. The density of returns was 8ppm over the urban area and 4ppm over the remainder of the territory including a large alpine national park that covers 45 percent of the ACT. Bushfire \& Natural Hazards Cooperative Research Centre (BNHCRC) research partners arranged for the dataset to be included in feasibility analyses conducted by the Terrestrial Ecology Research Network (TERN) AusCover Landscape Observatory project. A number of fuel-related layers were created based on the Overall Fuel Hazard Assessment (OFHA) and inputs to Project Vesta.

The fuel layers were created at resolutions of 1m, 2m, 5m and 25m in the NetCDF file format. The 25m data were selected for initial assessment because these were the only whole-of-territory datasets easily manipulated in ArcGIS 10. Qualitative assessments indicate: 1) a discernible pattern of fuel variation related to topography; 2) good agreement between LiDAR-derived elevated and near-surface fuel layers and OFHA data collected during the LiDAR acquisition; and 3) good agreement between the LiDAR and fire severity assessments made on burns that were conducted a short time before the acquisition. The next step is to conduct quantitative assessments.

}, author = {Adam J. Leavesley and Albert van Dijk and Marta Yebra} } @article {bnh-5051, title = {Mapping bushfire hazards and impacts: annual project report 2017-18}, year = {2018}, month = {11/2018}, institution = {Bushfire and Natural Hazards CRC}, abstract = {

Understanding and predicting fire behaviour is a priority for fire services, land managers and sometimes individual businesses and residents. This is an enormous scientific challenge given bushfires are complex phenomena, with\  their behaviour and resultant severity driven by complicated interactions among living and dead vegetation, topography and weather conditions.\ 

}, issn = {426}, author = {Marta Yebra and Geoffrey J. Cary and Albert van Dijk} } @conference {bnh-3914, title = {The Australian Flammability Monitoring System}, booktitle = {AFAC17}, year = {2017}, month = {09/2017}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Sydney}, abstract = {

The Australian Flammability Monitoring System (AFMS) is the first, continental-scale prototype web explorer providing spatial information on current Live Fuel Moisture Content (FMC) and landscape-scale fuel flammability derived from satellite observations. The satellite observations are converted into FMC using a radiative transfer modelling inversion approach. Evaluation of the FMC estimates using 408 observations at 35 locations around Australia shows similar accuracies (r2=0.60, RMSE=39\%) across the vegetation classes studied (grassland, shrubland and forest) to those derived elsewhere globally. Flammability estimates are calculated using logistic regression models relating fire occurrence to FMC. Separate prediction models were developed for grassland, shrubland and forest, obtaining performance metrics (Area Under the Curve) of 0.70, 0.78 and 0.71, respectively (where skillful predictions range between 0.5 and1). A web-based data explorer will be available to fire and land management agencies and any other interested parties in all states and territories. The AFMS can support a range of fire management activities such as prescribed burning and pre-positioning of firefighting resources and can inform the future National Fire Danger Rating System.

}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary and Xingwen Quan and Joel Rahman and Zac H. Dodds and Pablo Rozas} } @article {bnh-4196, title = {Mapping bushfire hazards and impacts: annual project report 2016-17}, number = {308}, year = {2017}, month = {09/2017}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

This annual report is output from the Bushfire and National Hazards CRC, {\textquoteleft}Mapping Bushfire Hazard and Impacts{\textquoteright}. It summarises the project objectives, introduces the team members as well as documents the project progress and outcomes during the financial year 2016/2017.

In consultation with the end users we have identified a subset of key outputs that have the highest utilisation potential, and that will be the focus of our work program in the future.

On those lines, the project team has made considerable progress this financial year towards the validation and increased accessibility to the {\textquotedblleft}Australian Flammability Monitoring System{\textquotedblright} for operational prediction of live fuel moisture content (FMC) and flammability in Australia. In this regard, we have created a prototype web service to make spatial information on FMC and flammability easier and faster to access.

Additionally we have:

1)\ \ \  Evaluated the suitability of coarse resolution near-surface soil moisture data to improve the McArthur forest fire danger index

2)\ \ \  Undertaken development of a predictive model for estimating forest surface fuel load with LiDAR data

3)\ \ \  Developed a satellite-based method for the estimation of grassland aboveground biomass

4)\ \ \  Published four journal manuscript with another three currently in review and one invited book chapter in preparation, ten conference abstracts and two milestone reports;

5)\ \ \  Hosted two international exchange visits and were approached by more than 30 domestic and international applicants for a PhD scholarship or postdoc position in bushfire research; and

Over the next three years (2017-2020), this research project will focus on increasing the understanding, reliability and long-term continuity of the AFMS, and through this, its acceptance and adoption. Also, a small number of promising, low-cost in-field techniques will continue to be investigated to improve their cost/benefit ratio and utility.

}, issn = {308}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-3920, title = {Using alternative soil moisture estimates in the McArthur Forest Fire Danger Index}, journal = {International Journal of Wildland Fire}, year = {2017}, month = {08/2017}, abstract = {

McArthur{\textquoteright}s Forest Fire Danger Index (FFDI) incorporates the Keetch{\textendash}Byram Drought Index (KBDI) estimate of soil dryness. Improved approaches for estimating soil moisture now exist, with potential for informing the calculation of FFDI. We evaluated the effect, compared with KBDI, of two alternative methods of estimating soil moisture: the rainfall-based Antecedent Precipitation Index and soil moisture from the Soil Moisture Ocean Salinity satellite mission. These methods were used to calculate FFDI over a sample period of 5\ years (2010{\textendash}14) at seven locations around Australia. The effect of substituting the alternatives for KBDI, and of entirely replacing the Drought Factor (DF) (a measure of fuel availability in FFDI) with the alternatives was explored by studying the effect on magnitude, distribution and timing of FFDI and associated Fire Danger Rating (FDR). Both approaches predicted drier soil conditions than KBDI, resulting in fewer Low{\textendash}Moderate FDR days and more days of High FDR and above. The alternative methods replacing KBDI had little effect on seasonal patterns of FDR. Of all approaches, replacing DF entirely with the soil moisture alternatives most closely mimicked McArthur{\textquoteright}s FFDI. Overall, if alternative measures of soil moisture are adopted for FFDI, the entire replacement of the DF term should be considered.

}, doi = {10.1071/WF16217}, url = {http://www.publish.csiro.au/WF/WF16217}, author = {C.M Holgate and Albert van Dijk and Geoffrey J. Cary and Marta Yebra} } @article {bnh-3227, title = {Comparison of remotely sensed and modelled soil moisture data sets across Australia}, journal = {Remote Sensing of Environment}, volume = {186}, year = {2016}, month = {12/2016}, abstract = {

This study compared surface soil moisture from 11 separate remote sensing and modelled products across Australia in a common framework. The comparison was based on a correlation analysis between soil moisture products and\ in situ\ data collated from three separate ground-based networks: OzFlux, OzNet and CosmOz. The correlation analysis was performed using both original data sets and temporal anomalies, and was supported by examination of the time series plots. The interrelationships between the products were also explored using cluster analyses. The products considered in this study include: Soil Moisture Ocean Salinity (SMOS; both Land Parameter Retrieval Model (LPRM) and L-band Microwave Emission of the Biosphere (LMEB) algorithms), Advanced Microwave Scanning Radiometer 2 (AMSR2; both LPRM and Japan Aerospace Exploration Agency (JAXA) algorithms) and Advanced Scatterometer (ASCAT) satellite-based products, and WaterDyn, Australian Water Resource Assessment Landscape (AWRA-L), Antecedent Precipitation Index (API), Keetch-Byram Drought Index (KBDI), Mount{\textquoteright}s Soil Dryness Index (MSDI) and CABLE/BIOS2 model-based products. The comparison of the satellite and model data sets showed variation in their ability to reflect\ in\ situ\ soil moisture conditions across Australia owing to individual product characteristics. The comparison showed the satellite products yielded similar ranges of correlation coefficients, with the possible exception of AMSR2_JAXA. SMOS (both algorithms) achieved slightly better agreement with\ in situ\ measurements than the alternative satellite products overall. Among the models, WaterDyn yielded the highest correlation most consistently across the different locations and climate zones considered. All products displayed a weaker performance in estimating soil moisture anomalies than the original data sets (i.e.\ the absolute values), showing all products to be more effective in detecting interannual and seasonal soil moisture dynamics rather than individual events. Using cluster analysis we found satellite products generally grouped together, whereas models were more similar to other models. SMOS (based on LMEB algorithm and ascending overpass) and ASCAT (descending overpass) were found to be very similar to each other in terms of their temporal soil moisture dynamics, whereas AMSR2 (based on LPRM algorithm and descending overpass) and AMSR2 (based on JAXA algorithm and ascending overpass) were dissimilar. Of the model products, WaterDyn and CABLE were similar to each other, as were the API/AWRA-L and KBDI/MSDI pairs. The clustering suggests systematic commonalities in error structure and duplication of information may exist between products. This evaluation has highlighted relative strengths, weaknesses, and complementarities between products, so the drawbacks of each may be minimised through a more informed assessment of fitness for purpose by end users.

}, doi = {http://dx.doi.org/10.1016/j.rse.2016.09.015}, url = {http://www.sciencedirect.com/science/article/pii/S0034425716303583}, author = {C.M Holgate and R.A.M. De Jeu and Albert van Dijk and Y.Y Liu and Luigi J. Renzullo and Vinod Kumar and Imtiaz Dharssi and R.M. Parinussa and R. Van Der Schalie and A. Gevaert and Jeffrey Walker and D. McJannet and J. Cleverly and V. Haverd and Trudinger, C and Briggs, P} } @article {bnh-3422, title = {Deriving comprehensive forest structure information from mobile laser scanning observations using automated point cloud classification}, journal = {Environmental Modelling \& Software}, volume = {82}, year = {2016}, month = {08/2016}, pages = {142-151}, chapter = {142}, abstract = {

The advent of mobile laser scanning has enabled time efficient and cost effective collection of forest structure information. To make use of this technology in calibrating or evaluating models of forest and landscape dynamics, there is a need to systematically and reproducibly automate the processing of LiDAR point clouds into quantities of forest structural components. Here we propose a method to classify vegetation structural components of an open-understorey eucalyptus forest, scanned with a {\textquoteleft}Zebedee{\textquoteright} mobile laser scanner. It detected 98\% of the tree stems (N\ =\ 50) and 80\% of the elevated understorey components (N\ =\ 15). Automatically derived DBH values agreed with manual field measurements with r2\ =\ 0.72, RMSE\ =\ 3.8\ cm, (N\ =\ 27), and total basal area agreed within 1.5\%. Though this methodological study was restricted to one ecosystem, the results are promising for use in applications such as fuel load, habitat structure, and biomass estimations.

}, doi = {10.1016/j.envsoft.2016.04.025}, url = {http://www.sciencedirect.com/science/article/pii/S1364815216301207}, author = {Marselis, S and Marta Yebra and Jovanovic, T and Albert van Dijk} } @article {bnh-3094, title = {Mapping bushfire hazard and impacts: Annual project report 2015-2016}, number = {227}, year = {2016}, month = {09/2016}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

This annual report is an output from the Bushfire and National Hazards CRC, Project {\textquoteleft}Mapping Bushfire Hazard and Impacts{\textquoteright}. It summarizes the project objectives, introduces the team members as well as documents the project progress and outcomes during the financial year 2015/2016.

The project team has made considerable progress this financial year and has generated a number of nationwide products. More specifically this financial year we have:

1)\ \ \  developed and tested the {\textquotedblleft}Bushfire Information System{\textquotedblright} with potential for operational prediction of live fuel moisture content and fire occurrence in Australia;

2)\ \ \  analyzed the suitability of near-surface soil moisture data to improve the McArthur forest fire danger index;

3)\ \ \  tested a forest carbon uptake estimation model constrained with remote sensing data at 25 m to 5 km resolution and evaluated against field data; and

4)\ \ \  Developed a predictive model for estimating forest surface fuel load with LiDAR data.

We have also completed some activities initialized during the previous financial year including:

1)\ \ \  the development and testing of a new software tool to automatically derive detailed vegetation structure information from ground-based LiDAR; and

2)\ \ \  testing an on-ground network of curing/FMC sensors.

We have maintained an effective and engaging relationship with project end users. The most intensive interactions have been with ACT Parks and Conservation, with whom the team collaborates closely, including in an operational setting. However, now that we have generated a number of nationwide products, more end users are identifying how they can practically engage in the research. This has led to a large number of follow-up projects that have been requested and will be addressed as much as possible over the next years, contingent on future project funding.

Additionally we:

1)\ \ \  published 1 journal manuscript with another 6 currently in review and one invited book chapter in preparation, 10 conference abstracts, one conference paper and 3 milestone reports;

2)\ \ \  hosted three international exchange visits and were approached by more than 15 domestic and international applicants for a PhD scholarship or postdoc position in bushfire research; and

3)\ \ \  in consultation with the end users, identified a subset of key outputs that have the highest utilisation potential, and that will be the focus of our work program in the future.

}, issn = {227}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-3284, title = {Natural hazards in Australia: droughts}, journal = {Climatic Change}, volume = {139}, year = {2016}, month = {11/2016}, pages = {37-54}, chapter = {37}, abstract = {

Droughts are a recurrent and natural part of the Australian hydroclimate, with evidence of drought dating back thousands of years. However, our ability to monitor, attribute, forecast and manage drought is exposed as insufficient whenever a drought occurs. This paper summarises what is known about drought hazard, as opposed to the impacts of drought, in Australia and finds that, unlike other hydroclimatic hazards, we currently have very limited ability to tell when a drought will begin or end. Understanding, defining, monitoring, forecasting and managing drought is also complex due to the variety of temporal and spatial scales at which drought occurs and the diverse direct and indirect causes and consequences of drought. We argue that to improve understanding and management of drought, three key research challenges should be targeted: (1) defining and monitoring drought characteristics (i.e. frequency, start, duration, magnitude, and spatial extent) to remove confusion between drought causes, impacts and risks and better distinguish between drought, aridity, and water scarcity due to over-extractions; (2) documenting historical (instrumental and pre-instrumental) variation in drought to better understand baseline drought characteristics, enable more rigorous identification and attribution of drought events or trends, inform/evaluate hydrological and climate modelling activities and give insights into possible future drought scenarios; (3) improving the prediction and projection of drought characteristics with seasonal to multidecadal lead times and including more realistic modelling of the multiple factors that cause (or contribute to) drought so that the impacts of natural variability and anthropogenic climate change are accounted for and the reliability of long-term drought projections increases.

}, doi = {10.1007/s10584-016-1798-7}, url = {http://link.springer.com/article/10.1007/s10584-016-1798-7}, author = {Anthony S. Kiem and Fiona Johnson and Seth Westra and Albert van Dijk and Jason P. Evans and O{\textquoteright}Donnell, Alison J. and Alexandra Rouillard and Cameron Barr and Johnathon Tyler and Mark Thyer and Doerte Jakob and Fitsum Woldemeskel and Bellie Sivakumar and Raj Mehrotra} } @article {bnh-3283, title = {Natural hazards in Australia: floods}, journal = {Climatic Change}, volume = {139}, year = {2016}, month = {11/2016}, pages = {21-35}, chapter = {21}, abstract = {

Floods are caused by a number of interacting factors, making it remarkably difficult to explain changes in flood hazard. This paper reviews the current understanding of historical trends and variability in flood hazard across Australia. Links between flood and rainfall trends cannot be made due to the influence of climate processes over a number of spatial and temporal scales as well as landscape changes that affect the catchment response. There are also still considerable uncertainties in future rainfall projections, particularly for sub-daily extreme rainfall events. This is in addition to the inherent uncertainty in hydrological modelling such as antecedent conditions and feedback mechanisms.

Research questions are posed based on the current state of knowledge. These include a need for high-resolution climate modelling studies and efforts in compiling and analysing databases of sub-daily rainfall and flood records. Finally there is a need to develop modelling frameworks that can deal with the interaction between climate processes at different spatio-temporal scales, so that historical flood trends can be better explained and future flood behaviour understood.

}, doi = {10.1007/s10584-016-1689-y}, url = {http://link.springer.com/article/10.1007/s10584-016-1689-y}, author = {Fiona Johnson and Christopher J. White and Albert van Dijk and Marie Ekstrom and Jason P. Evans and Doerte Jakob and Anthony S. Kiem and M. Leonard and Alexandra Rouillard and Seth Westra} } @article {bnh-1844, title = {Global vegetation gross primary production estimation using satellite-derived light-use efficiency and canopy conductance}, journal = {Remote Sensing of Environment}, volume = {163}, year = {2015}, month = {06/2015}, pages = {206-216}, chapter = {206}, abstract = {

Climate and physiological controls of vegetation gross primary production (GPP) vary in space and time. In many ecosystems, GPP is primary limited by absorbed photosynthetically-active radiation; in others by canopy conductance. These controls further vary in importance over daily to seasonal time scales. We propose a simple but effective conceptual model that estimates GPP as the lesser of a conductance-limited (Fc) and radiation-limited (Fr) assimilation rate.\ Fc\ is estimated from canopy conductance while\ Fr\ is estimated using a light use efficiency model. Both can be related to vegetation properties observed by optical remote sensing. The model has only two fitting parameters: maximum light use efficiency, and the minimum achieved ratio of internal to external CO2\ concentration. The two parameters were estimated using data from 16 eddy covariance flux towers for six major biomes including both energy- and water-limited ecosystems. Evaluation of model estimates with flux tower-derived GPP compared favourably to that of more complex models, for fluxes averaged; per day (r2\ =\ 0.72, root mean square error, RMSE\ =\ 2.48\ μmol\ C\ m2\ s-\ 1, relative percentage error, RPE\ =\ -\ 11\%), over 8-day periods (r2\ =\ 0.78 RMSE\ =\ 2.09\ μmol\ C\ m2\ s-\ 1,RPE\ =\ -\ 10\%), over months (r2\ =\ 0.79, RMSE\ =\ 1.93\ μmol\ C\ m2\ s-\ 1, RPE\ =\ -\ 9\%) and over years (r2\ =\ 0.54, RMSE\ =\ 1.62\ μmol\ C\ m2\ s-\ 1, RPE\ =\ -\ 9\%). Using the model we estimated global GPP of 107\ Pg\ C\ y-\ 1\ for 2000{\textendash}2011. This value is within the range reported by other GPP models and the spatial and inter-annual patterns compared favourably. The main advantages of the proposed model are its simplicity, avoiding the use of uncertain biome- or land-cover class mapping, and inclusion of explicit coupling between GPP and plant transpiration.

}, keywords = {Photosynthesis; Canopy conductance; Light use efficiency; FLUXNET; MODIS; Gross primary production; GPP; Vegetation}, doi = {doi:10.1016/j.rse.2015.03.016}, url = {http://www.sciencedirect.com/science/article/pii/S0034425715001121}, author = {Marta Yebra and Albert van Dijk and Ray Leuning and Guerschman, Juan Pablo} } @article {bnh-2402, title = {Mapping bushfire hazard and impact}, year = {2015}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-2311, title = {Mapping bushfire hazard and impacts: Annual project report 2014-2015}, number = {119}, year = {2015}, month = {10/2015}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

This annual report is an output from the Bushfire and National Hazards CRC Project {\textquoteleft}Mapping Bushfire Hazard and Impacts{\textquoteright}. It summarises the project objectives, introduces the team members as well as documents the project progress and outcomes during the finantial year 2014/2015.\ The project team has made great progress this year as demonstrated by:

1)\ \ \  Developing a model framework, the High-resolution Fire Risk and Impact (HiFRI) framework, to provide best possible estimates on forest fuel load and moisture content and fire impacts on landscape values such as water resource generation and carbon storage.

2)\ \ \  Developing and tested a new software tool based in MATLAB to automatically derive detailed vegetation structure information from ground-based LiDAR

3)\ \ \  Successfully obtaining two student top-up scholarships from BNHCRC, what will have further positive impacts on the quality of our research.

4)\ \ \  Maintaining a healthy and engaging relationship with end users. The strongest connections have been with ACT Parks and Conservation, with whom the team collaborate closely and hands-on. However, the expectations are that once the project team have been able to demonstrate the practical value of research in the ACT, additional end users will find it easier to see how they can concretely engage in the research.

5)\ \ \  Publishing 1 journal paper, 4 conference abstracts and 2 milestone reports. In addition another manuscript is currently under review with Remote Sensing of Environment,top-ranked in the category of remote sensing.

6)\ \ \  Communicating progress on the research goals to end users by organising two workshops with operational stakeholders and other researchersandpublishing divulgative material in blogs and other media.

7)\ \ \  Receiving international researchers exchange visits and being approached by more than 15 domestic and international requests for PhD scholarships or postdoc positions on the topic of bushfire research. Of particular interest has been our innovative work in LiDAR vegetation mapping.

}, issn = {119}, author = {Marta Yebra and Albert van Dijk and Geoffrey J. Cary} } @article {bnh-1555, title = {Mapping Bushfire Hazard and Impacts Annual Report 2014}, year = {2015}, abstract = {

This is an annual report for the year 2013/14 for the Mapping Bushfire Hazard and Impacts project. This project will bring the industry closer to an operational broad-scale, spatially explicit fuel data collection system relevant to Vesta or Overall Fuel Hazard Assessment (OFHA) that can be used in existing fire behaviour models. The work will also help end-users to understand what information is easily and reliably collected from remote systems as a precursor to developing a new fire behaviour model based on the remote data.

}, author = {Albert van Dijk} } @article {bnh-1883, title = {A model-data fusion framework for estimating fuel properties, vegetation growth, carbon storage and the water balance at hillslope scale}, year = {2015}, month = {06/2015}, abstract = {

This progress report is an output from the Bushfire and National Hazards CRC, Project A1 {\textquoteleft}Mapping Bushfire Hazard and Impacts{\textquoteright}. It documents the first steps in the development of a model-data fusion framework to provide estimates on historic fire impacts on landscape values, as well as potentially real-time estimates of current fuel load and flammability. Model-data fusion refers to the blending of observations with model predictions by considering the error in both.

A case study area was undertaken to analyse the value of alternative airborne and remote sensing observations in a model-data fusion framework. The data were used to set up a spatial forest growth, water use and carbon uptake model at high (25 m) spatial resolution and daily time step. The model shares a common heritage with the Australian Water Resources Assessment Landscape (AWRA-L) water balance model used by the Bureau of Meteorology, and includes coupled models of water, carbon and biomass (fuel) dynamics that can be applied at high resolution. The model-data fusion framework is provisionally referred to here as the High-resolution Fire Risk and Impact (HiFRI) framework.

The case study comprised the period 2000-2010 for the western ACT, including native forests, plantation forests and grasslands. Much of the area was burnt in 2003. The data integrated within HiFRI included high-resolution Landsat imagery, a digital elevation model and daily climate grids. The case study demonstrated that it is feasible to produce estimates of water and carbon balance variables. The results show strong slope effects associated with solar irradiance. Integrating satellite observations also showed the expected influence from vegetation regrowth after the fire.

}, author = {Albert van Dijk and Marta Yebra and Geoffrey J. Cary} } @article {bnh-1661, title = {Using LiDAR for forest and fuel structure mapping: options, benefits, requirements and costs}, number = {64}, year = {2015}, month = {03/2015}, institution = {Bushfire and Natural Hazards CRC}, abstract = {

Understanding fuel structure is important for assessing suppression difficulty, risk of damage from bushfires, monitoring fuel build up and planning hazard reduction programs. Technologies such as airborne Light Detection and Ranging (LiDAR) can provide precise information about fuel structure over larger areas. However, the use of LiDAR by fire managers is still in the early stages and has not been implemented through any routine operational program in Australia.

This report aims to address this situation by describing and evaluating the maturity and suitability of airborne LiDAR to derive the different types of information needed in forest fuel assessment. It does so through a set of questions scoped in consultation with fire managers through the Bushfire and Natural Hazards CRC project {\textquoteleft}Mapping bushfire hazard and impacts{\textquoteright}. The language and technical detail is aimed at a wide audience with fields of expertise outside LiDAR.

This report first covers some of the basic principles on LiDAR and then focuses on the analysis of the information content and accuracy of airborne LiDAR to retrieve the forest fuel attributes that are important for fire management. The information that can be derived about the height, cover fraction and density of different over- and understorey layers is assessed, along with other useful information that may be derived. Additional measurements that help to make more optimal use of airborne LiDAR data are presented, including terrestrial laser scanning, UAV-borne LiDAR, and airborne imaging. Guidance is provided on discovering existing LiDAR data, factors determining the cost of new LiDAR data acquisition, and options for processing the data. Finally, the current and future development in the use of LiDAR for fire management are discussed.

Summarising, airborne LiDAR may be considered a mature data product that is commercially available, using established data standards. However, standardised data specifications and processing methods for applications in fuel mapping do not yet exist. Essential aspects to consider are the type of fuel information, accuracy and spatial detail desired. Greater data density can increase accuracy and spatial detail, but will also increase the cost of acquisition. In forests with a dense overstorey canopy high data density may be the only way to obtain information on the understorey. In small-scale applications, field or UAV-mounted LiDAR systems may be a suitable alternative for airborne LiDAR.

Priority areas for research and development to achieve more cost-effective and successful use of LiDAR by the fire management community were identified. This includes the development of standardised methods to acquire and process airborne LiDAR data for fuel mapping, the validation of these methods using field measurements, and investigation of full-waveform airborne LiDAR as a promising alternative to current LiDAR data collection methods. The Bushfire and Natural Hazards CRC project {\textquoteleft}Mapping bushfire hazard and impacts{\textquoteright} is working with end users to pursue each of these lines of enquiry.

}, issn = {64}, author = {Marta Yebra and Marselis, S and Albert van Dijk and Geoffrey J. Cary and Chen, Yang} }