Dataset Open Access

L4B - Maximum tree height map for the Brazilian Amazon

Gorgens, Eric Bastos; Nunes, Matheus Henrique; Jackson, Tobias; Coomes, David; Keller, Michael; Reis, Cristiano Rodrigues; Valbuena, Rubén; Rosette, Jacqueline; Almeida, Danilo Roberti Alves; Gimenez, Bruno; Cantinho, Roberta; Motta, Alline Zagnolli; Assis, Mauro; Pereira, Francisca Rocha de Souza; Spanner, Gustavo; Higuchi, Niro; Ometto, Jean Pierre


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    <dct:title>L4B - Maximum tree height map for the Brazilian Amazon</dct:title>
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    <dcat:keyword>Tropical forest</dcat:keyword>
    <dcat:keyword>Amazon</dcat:keyword>
    <dcat:keyword>Height</dcat:keyword>
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    <dct:description>&lt;p&gt;Maximum tree height distribution estimated by the Random Forest model based on the environmental variables.&amp;nbsp;To explore the influence and importance of the environmental variables for development in tree height, we employed Random Forest modeling, which consists of generating a large number of regression trees, each constructed considering a random data subset. The regression trees are used to identify the best sequence to split the solution space to estimate the output. Were considered 18 environmental variables: (1) fraction of absorbed photosynthetically active radiation (FAPAR; in %); (2) elevation above sea level (Elevation; in m);&amp;nbsp; (3) the component of the horizontal wind towards east, i.e. zonal velocity (u-speed ; in m s&lt;sup&gt;-1&lt;/sup&gt;); (4) the component of the horizontal wind towards north, i.e. meridional velocity (v-speed ; in m s&lt;sup&gt;-1&lt;/sup&gt;); (5) the number of days not affected by cloud cover (clear days; in days yr&lt;sup&gt;-1&lt;/sup&gt;); (6) the number of days with precipitation above 20 mm (days &amp;gt; 20mm; in days yr&lt;sup&gt;-1&lt;/sup&gt;&amp;nbsp;); (7) the number of months with precipitation below 100 mm (months &amp;lt; 100mm; in months yr&lt;sup&gt;-1&lt;/sup&gt;&amp;nbsp;) ; (8) lightning frequency (flashes rate); (9) annual precipitation (in mm); (10) potential evapotranspiration (in mm); (11) coefficient of variation of precipitation (precipitation seasonality; in %); (12) amount of precipitation on the wettest month (precip. wettest; in mm); (13) amount of precipitation on the driest month (precip. driest; in mm); (14) mean annual temperature (in &amp;deg;C); (15)&amp;nbsp; standard deviation of temperature (temp. seasonality; in &amp;deg;C); (16) annual maximum temperature (in &amp;deg;C); (17) soil clay content (in %); and (18) soil water content (in %).&amp;nbsp;&lt;/p&gt;</dct:description>
    <dct:description>Funding was provided by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Brasil (CAPES; Finance Code 001); Conselho Nacional de Desenvolvi­mento Científico e Tecnológico (Processes 403297/2016-8 and 301661/2019-7); Amazon Fund (grant 14.2.0929.1); Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM); Instituto Nacional de Pesquisas Espaciais (INPE); São Paulo Research Foundation (#2018/21338-3 and #2019/14697-0); INCT-Madeiras da Amazônia and Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics), as part of DOE's Terrestrial Ecosystem Science Program – Contract No. DE-AC02-05CH11231; National Academy of Sciences and US Agency for International Development (grant AID-OAA-A-11-00012); Royal Society University Research Fellowship (URF\R\191014).</dct:description>
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