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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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.4036988", 
  "language": "eng", 
  "title": "L4B - Maximum tree height map for the Brazilian Amazon", 
  "issued": {
    "date-parts": [
      [
        2020, 
        9, 
        18
      ]
    ]
  }, 
  "abstract": "<p>Maximum tree height distribution estimated by the Random Forest model based on the environmental variables.&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);&nbsp; (3) the component of the horizontal wind towards east, i.e. zonal velocity (u-speed ; in m s<sup>-1</sup>); (4) the component of the horizontal wind towards north, i.e. meridional velocity (v-speed ; in m s<sup>-1</sup>); (5) the number of days not affected by cloud cover (clear days; in days yr<sup>-1</sup>); (6) the number of days with precipitation above 20 mm (days &gt; 20mm; in days yr<sup>-1</sup>&nbsp;); (7) the number of months with precipitation below 100 mm (months &lt; 100mm; in months yr<sup>-1</sup>&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 &deg;C); (15)&nbsp; standard deviation of temperature (temp. seasonality; in &deg;C); (16) annual maximum temperature (in &deg;C); (17) soil clay content (in %); and (18) soil water content (in %).&nbsp;</p>", 
  "author": [
    {
      "family": "Gorgens, Eric Bastos"
    }, 
    {
      "family": "Nunes, Matheus Henrique"
    }, 
    {
      "family": "Jackson, Tobias"
    }, 
    {
      "family": "Coomes, David"
    }, 
    {
      "family": "Keller, Michael"
    }, 
    {
      "family": "Reis, Cristiano Rodrigues"
    }, 
    {
      "family": "Valbuena, Rub\u00e9n"
    }, 
    {
      "family": "Rosette, Jacqueline"
    }, 
    {
      "family": "Almeida, Danilo Roberti Alves"
    }, 
    {
      "family": "Gimenez, Bruno"
    }, 
    {
      "family": "Cantinho, Roberta"
    }, 
    {
      "family": "Motta, Alline Zagnolli"
    }, 
    {
      "family": "Assis, Mauro"
    }, 
    {
      "family": "Pereira, Francisca Rocha de Souza"
    }, 
    {
      "family": "Spanner, Gustavo"
    }, 
    {
      "family": "Higuchi, Niro"
    }, 
    {
      "family": "Ometto, Jean Pierre"
    }
  ], 
  "note": "Funding was provided by the Coordena\u00e7\u00e3o\u00a0de Aperfei\u00e7oamento de Pessoal de N\u00edvel\u00a0Superior Brasil\u00a0(CAPES; Finance Code 001); Conselho Nacional de Desenvolvi\u00admento Cient\u00edfico e Tecnol\u00f3gico (Processes 403297/2016-8 and 301661/2019-7); Amazon Fund (grant 14.2.0929.1); Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM);\u00a0Instituto Nacional de Pesquisas Espaciais (INPE); S\u00e3o Paulo Research Foundation (#2018/21338-3 and #2019/14697-0); INCT-Madeiras da Amaz\u00f4nia and Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics), as part of DOE's Terrestrial Ecosystem Science Program \u2013 Contract No. DE-AC02-05CH11231; National Academy of\u00a0Sciences and US Agency for International Development (grant AID-OAA-A-11-00012); Royal Society University Research Fellowship (URF\\R\\191014).", 
  "version": "v1", 
  "type": "dataset", 
  "id": "4036988"
}
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