FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3152756331> ?p ?o ?g. }

• W3152756331 abstract "Australia’snative Eucalypt forests are the most fire-prone in the world due to high ratesof fuel accumulation, high flammability of fuel, and seasonally hot and dryweather conditions. Projected changes in the frequency and intensity of extremeclimate and weather could increase the occurrence of ‘mega-fires’, extreme fireevents with catastrophic impacts on people and the environment. Current methodsfor fire risk mitigation and prediction such as fire danger rating systems,fire behaviour models, and hazard reduction treatments require an accuratedescription of forest fuel. However, fire management authorities share a commonchallenge to efficiently and accurately quantify forest fuel properties (e.g.fuel load and fuel structure) at a landscape scale. A landscape includes thephysical elements of geo-physically defined landforms, such as forests,grasslands, and lakes. This thesis investigates the application of the LightDetection and Ranging (LiDAR) technique in quantifying forest fuel properties,including fuel structural characteristics and litter-bed fuel load at alandscape scale.    Currently, fire fighters and land managers still rely onempirical knowledge to visually assess forest fuel characteristics of distinctfuel layers. The visual assessment method provides a subjective description offuel properties that can lead to unreliable fire behaviour prediction andhazard estimation. This study developed a novel method to classify understoreyfuel layers in order to quantify fuel structural characteristics moreaccurately and efficiently by integrating terrestrial LiDAR data and GeographicInformation Systems (GIS). The GIS-based analysis and processing proceduresallow more objective descriptions of fuel covers and depths for individual fuellayers. The more accurate forest fuel structural information derived fromterrestrial LiDAR data can be used to prescribe fire hazard-reduction burns,predict fire behaviour potentials, monitor fuel growth, and conserve foresthabitats and ecosystems in multilayered Eucalypt forests.    Traditionally, litter-bed fuel load is directly measured throughdestructive sampling, sorting, and immediate weighing after oven drying for 24hours at 105 °C. This direct measurement of fuel load on a landscape scalerequires extensive field sampling, post laboratory work and statisticalanalysis, which is labour intensive and time consuming. This study found newrelationships among forest litter-bed fuel load, surface fuel depth, firehistory and environmental factors through multiple regressions with airborneand terrestrial LiDAR data. The fuel load models established in this studyindicate that litter-bed depth and fire history are the primary predictors inestimating litter-bed fuel load, while canopy density and terrain features aresecondary predictors.    Current fuel models are constrained to estimate spatialvariations in fuel load within homogeneous vegetation that previouslyexperienced the same fire events. This study developed a predictive modelthrough multiple regression to estimate the spatial distribution of litter-bedfuel load in multilayered eucalypt forests with various fire histories andforest fuel types. This model uses forest structural indices and terrainfeatures derived from airborne LiDAR data as predictors, which can be appliedwhen data on forest fuel types and previous fire disturbances are absent. Itcan be used to map the litter-bed fuel load distribution at a landscape scaleto support regional wildland fire management and planning.    This study indicates that LiDAR allows a more efficient andaccurate description of fuel structural characteristics and estimation oflitter-bed fuel load. The results from this study can assist fire hazardassessment, fuel reduction treatment, and fire behaviour prediction, andtherefore may reduce the impact to communities and environment." @default.
• W3152756331 created "2021-04-26" @default.
• W3152756331 creator A5020819058 @default.
• W3152756331 date "2017-04-05" @default.
• W3152756331 modified "2023-09-23" @default.
• W3152756331 title "LiDAR Application in Forest Fuel Measurements for Bushfire Hazard Mitigation" @default.
• W3152756331 cites W100464641 @default.
• W3152756331 cites W133894003 @default.
• W3152756331 cites W1505951429 @default.
• W3152756331 cites W1515736137 @default.
• W3152756331 cites W1518098811 @default.
• W3152756331 cites W1526740462 @default.
• W3152756331 cites W1528309322 @default.
• W3152756331 cites W1558900320 @default.
• W3152756331 cites W1571411223 @default.
• W3152756331 cites W1573763320 @default.
• W3152756331 cites W1582014504 @default.
• W3152756331 cites W1600877088 @default.
• W3152756331 cites W1618442464 @default.
• W3152756331 cites W1640415252 @default.
• W3152756331 cites W1680392829 @default.
• W3152756331 cites W1883991860 @default.
• W3152756331 cites W1893813512 @default.
• W3152756331 cites W1965722011 @default.
• W3152756331 cites W1968385740 @default.
• W3152756331 cites W1969601839 @default.
• W3152756331 cites W1974110440 @default.
• W3152756331 cites W1974523404 @default.
• W3152756331 cites W1977940988 @default.
• W3152756331 cites W1981489183 @default.
• W3152756331 cites W1987064464 @default.
• W3152756331 cites W1987610258 @default.
• W3152756331 cites W1989561113 @default.
• W3152756331 cites W1990409457 @default.
• W3152756331 cites W1990660785 @default.
• W3152756331 cites W1994985780 @default.
• W3152756331 cites W1996263757 @default.
• W3152756331 cites W1998779060 @default.
• W3152756331 cites W1998902551 @default.
• W3152756331 cites W2001618165 @default.
• W3152756331 cites W2001742722 @default.
• W3152756331 cites W2006219734 @default.
• W3152756331 cites W2008969571 @default.
• W3152756331 cites W2012824497 @default.
• W3152756331 cites W2014181466 @default.
• W3152756331 cites W2018517565 @default.
• W3152756331 cites W2018820549 @default.
• W3152756331 cites W2020861455 @default.
• W3152756331 cites W2021131407 @default.
• W3152756331 cites W2024158525 @default.
• W3152756331 cites W2027319497 @default.
• W3152756331 cites W2027672019 @default.
• W3152756331 cites W2029449972 @default.
• W3152756331 cites W2029877530 @default.
• W3152756331 cites W2030066785 @default.
• W3152756331 cites W2030337367 @default.
• W3152756331 cites W2032199972 @default.
• W3152756331 cites W2032962499 @default.
• W3152756331 cites W2033130094 @default.
• W3152756331 cites W2034562813 @default.
• W3152756331 cites W2038530930 @default.
• W3152756331 cites W2038790471 @default.
• W3152756331 cites W2041960396 @default.
• W3152756331 cites W2043142216 @default.
• W3152756331 cites W2047192529 @default.
• W3152756331 cites W2048997388 @default.
• W3152756331 cites W2049154679 @default.
• W3152756331 cites W2051204016 @default.
• W3152756331 cites W2053452673 @default.
• W3152756331 cites W2053618729 @default.
• W3152756331 cites W2054804188 @default.
• W3152756331 cites W2055314812 @default.
• W3152756331 cites W2055569426 @default.
• W3152756331 cites W2055639236 @default.
• W3152756331 cites W2056496234 @default.
• W3152756331 cites W2065258204 @default.
• W3152756331 cites W2065577834 @default.
• W3152756331 cites W2068182092 @default.
• W3152756331 cites W2069420657 @default.
• W3152756331 cites W2070510131 @default.
• W3152756331 cites W2070608504 @default.
• W3152756331 cites W2072432576 @default.
• W3152756331 cites W2075704050 @default.
• W3152756331 cites W2085232161 @default.
• W3152756331 cites W2087288327 @default.
• W3152756331 cites W2092924074 @default.
• W3152756331 cites W2092962792 @default.
• W3152756331 cites W2093355138 @default.
• W3152756331 cites W2093830434 @default.
• W3152756331 cites W2094605604 @default.
• W3152756331 cites W2097631297 @default.
• W3152756331 cites W2101365296 @default.
• W3152756331 cites W2106376825 @default.
• W3152756331 cites W2106780766 @default.
• W3152756331 cites W2109201676 @default.
• W3152756331 cites W2109427031 @default.
• W3152756331 cites W2111363125 @default.
• W3152756331 cites W2113508837 @default.
• W3152756331 cites W2114191733 @default.
• W3152756331 cites W2115127147 @default.

• next