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• W2890500853 abstract "Understanding ecological changes in native vegetation communities often requires information over long time periods (multiple decades). Tropical cyclones can have a major impact on woody vegetation structure across northern Australia, however understanding the impacts on woody vegetation structure is limited. Woody vegetation structural attributes such as height are used in ecological studies to identify long term changes and trends. LiDAR has been used to measure woody vegetation structure, however LiDAR datasets cover relatively small areas and historical coverage is restricted, limiting the use of this technology for monitoring long-term change. The Landsat archive spans multiple decades and is suitable for regional/continental assessment. Advances in predictive modelling using machine learning algorithms have enabled complex relationships between dependent and independent variables to be identified. The aim of this study is to develop a predictive model to estimate woody vegetation height from Landsat imagery to assist in understanding change through space and time. A LiDAR canopy height model was produced covering a range of vegetation communities in northern Australia (Darwin region) for use as the dependent variable. A random forest regression model was developed to predict mean LiDAR canopy height (30 m spatial resolution) from Landsat-5 Thematic Mapper (TM). Validation of the random forest model was undertaken on independent data (n = 30,500) resulting in an overall R2 = 0.53, RMSE of 2.8 m. Assessment of the RMSE within four broad vegetation communities ranged from 2.5 to 3.7 m with the two dominant communities in the study area Mangrove forests and Eucalyptus communities recording an RMSE value of 2.9 m and 2.5 m respectively. The model was also applied to Landsat-7 Enhanced Thematic Mapper Plus (ETM+) resulting in an R2 of 0.49, RMSE of 2.8 m. The model was then applied to all cloud free Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 Operational Land Imager (OLI) imagery (106/69 path/row) available between the months April, May and June for 1987 to 2016 to produce annual estimates (29 years) of canopy height. A number of time traces were produced to illustrate tree canopy height through time in the Darwin region which was severely impacted by cyclone (hurricane) Tracy on the 25th December 1974." @default.
• W2890500853 created "2018-09-27" @default.
• W2890500853 creator A5037737250 @default.
• W2890500853 creator A5048014874 @default.
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• W2890500853 date "2018-12-01" @default.
• W2890500853 modified "2023-09-26" @default.
• W2890500853 title "Modelling LiDAR derived tree canopy height from Landsat TM, ETM+ and OLI satellite imagery—A machine learning approach" @default.
• W2890500853 cites W1515414564 @default.
• W2890500853 cites W1720178141 @default.
• W2890500853 cites W1948133483 @default.
• W2890500853 cites W1949910136 @default.
• W2890500853 cites W1964217023 @default.
• W2890500853 cites W1964789567 @default.
• W2890500853 cites W1977670320 @default.
• W2890500853 cites W1978915895 @default.
• W2890500853 cites W1984671827 @default.
• W2890500853 cites W1985809628 @default.
• W2890500853 cites W1993151586 @default.
• W2890500853 cites W1998979050 @default.
• W2890500853 cites W1999091234 @default.
• W2890500853 cites W2000079684 @default.
• W2890500853 cites W2000102737 @default.
• W2890500853 cites W2001256577 @default.
• W2890500853 cites W2001666814 @default.
• W2890500853 cites W2008691741 @default.
• W2890500853 cites W2022858746 @default.
• W2890500853 cites W2024226821 @default.
• W2890500853 cites W2025286685 @default.
• W2890500853 cites W2028956118 @default.
• W2890500853 cites W2029984822 @default.
• W2890500853 cites W2030475138 @default.
• W2890500853 cites W2032258181 @default.
• W2890500853 cites W2033702892 @default.
• W2890500853 cites W2045102154 @default.
• W2890500853 cites W2046421861 @default.
• W2890500853 cites W2047239582 @default.
• W2890500853 cites W2059523177 @default.
• W2890500853 cites W2059663113 @default.
• W2890500853 cites W2060897350 @default.
• W2890500853 cites W2063623478 @default.
• W2890500853 cites W2066140232 @default.
• W2890500853 cites W2072633546 @default.
• W2890500853 cites W2072983685 @default.
• W2890500853 cites W2074416151 @default.
• W2890500853 cites W2091587061 @default.
• W2890500853 cites W2096102345 @default.
• W2890500853 cites W2098823605 @default.
• W2890500853 cites W2098919237 @default.
• W2890500853 cites W2101664201 @default.
• W2890500853 cites W2105770001 @default.
• W2890500853 cites W2106906152 @default.
• W2890500853 cites W2107583574 @default.
• W2890500853 cites W2111809230 @default.
• W2890500853 cites W2114230759 @default.
• W2890500853 cites W2117755198 @default.
• W2890500853 cites W2121315157 @default.
• W2890500853 cites W2121335883 @default.
• W2890500853 cites W2123689744 @default.
• W2890500853 cites W2125410201 @default.
• W2890500853 cites W2132108972 @default.
• W2890500853 cites W2132424470 @default.
• W2890500853 cites W2137933418 @default.
• W2890500853 cites W2138338114 @default.
• W2890500853 cites W2139086914 @default.
• W2890500853 cites W2143481518 @default.
• W2890500853 cites W2144433760 @default.
• W2890500853 cites W2145167036 @default.
• W2890500853 cites W2148750799 @default.
• W2890500853 cites W2150026442 @default.
• W2890500853 cites W2152430026 @default.
• W2890500853 cites W2152634225 @default.
• W2890500853 cites W2153598078 @default.
• W2890500853 cites W2155632266 @default.
• W2890500853 cites W2155863249 @default.
• W2890500853 cites W2168899452 @default.
• W2890500853 cites W2170244367 @default.
• W2890500853 cites W2180682969 @default.
• W2890500853 cites W2261059368 @default.
• W2890500853 cites W2273147317 @default.
• W2890500853 cites W2289402370 @default.
• W2890500853 cites W2313448762 @default.
• W2890500853 cites W2471874343 @default.
• W2890500853 cites W2566574403 @default.
• W2890500853 cites W2770851933 @default.
• W2890500853 cites W2911964244 @default.
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• W2890500853 doi "https://doi.org/10.1016/j.jag.2018.08.013" @default.
• W2890500853 hasPublicationYear "2018" @default.
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