<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0187-7380</journal-id>
<journal-title><![CDATA[Revista fitotecnia mexicana]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. fitotec. mex]]></abbrev-journal-title>
<issn>0187-7380</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Mexicana de Fitogenética A.C.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0187-73802024000100070</article-id>
<article-id pub-id-type="doi">10.35196/rfm.2024.1.70</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Ecuación alométrica para estimar biomasa aérea de árboles de Pinus hartwegii Lindl. A partir de datos LiDAR]]></article-title>
<article-title xml:lang="en"><![CDATA[Allometric equation to estimate aboveground biomass of Pinus hartwegii Lindl. From LiDAR data]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Islas-Gutiérrez]]></surname>
<given-names><![CDATA[Fabián]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cruz-Juárez]]></surname>
<given-names><![CDATA[Eduardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Buendía-Rodríguez]]></surname>
<given-names><![CDATA[Enrique]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Guerra-De la Cruz]]></surname>
<given-names><![CDATA[Vidal]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pineda-Ojeda]]></surname>
<given-names><![CDATA[Tomás]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Flores-Ayala]]></surname>
<given-names><![CDATA[Eulogio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Carrillo-Anzures]]></surname>
<given-names><![CDATA[Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Acosta-Mireles]]></surname>
<given-names><![CDATA[Miguel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias Campo Experimental Valle de México ]]></institution>
<addr-line><![CDATA[Texcoco Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Tecolutla  ]]></institution>
<addr-line><![CDATA[Tecolutla Veracruz]]></addr-line>
<country>México</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias  ]]></institution>
<addr-line><![CDATA[Tlaxcala Tlaxcala]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2024</year>
</pub-date>
<volume>47</volume>
<numero>1</numero>
<fpage>70</fpage>
<lpage>79</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-73802024000100070&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-73802024000100070&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-73802024000100070&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Conocer el contenido de biomasa aérea de árboles individuales es importante en los esfuerzos para determinar la contribución de los bosques en el secuestro de carbono. Los datos LiDAR (Light Detection and Ranging) son una alternativa a las imágenes satelitales para estimar características del arbolado. Dada la importancia de los bosques de la vertiente oriental de la Cuenca del ex Lago de Texcoco para la captura de carbono, el objetivo del presente estudio fue evaluar modelos de regresión para la estimación de biomasa aérea en árboles individuales de Pinus hartwegii Lindl. a partir de datos LiDAR. En campo se midió el diámetro normal (Dn), la altura total (AT), altura de fuste limpio (AF) y el diámetro de copa (DC) de 60 árboles. Sobre un conjunto de datos LiDAR aerotransportados se identificaron esos árboles y se midieron las mismas variables (ATL, AFL y DCL, donde la letra L hace referencia a LiDAR), excepto el diámetro normal, ya que no es posible su medición directa con el LiDAR. Para conocer la biomasa aérea de los árboles se usó el Dn y una ecuación alométrica generada previamente por otros autores. Mediante la técnica de regresión se ajustaron siete modelos lineales y cinco no lineales eligiendo aquel con menor raíz del cuadrado medio del error, mayor R2adj y menor valor del criterio de información de Akaike, además de cumplir con los supuestos de regresión. El modelo seleccionado es de tipo exponencial, con las variables ATL y DCL para estimar la biomasa: RMSE = 406.70, R2adj = 0.8107 y AIC = 723.88.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Summary Knowing the aboveground biomass content of individual trees is important in efforts to determine forests contribution to carbon sequestration. LiDAR (Light Detection and Ranging) data are an alternative to satellite images to estimate tree attributes. Considering the importance of forestland on the eastern slopes of the former Texcoco Lake basin for carbon capture, this study aimed to assess regression models for the estimation of above-ground biomass in individual Pinus hartwegii Lindl. trees from LiDAR data. In the field the breast-height diameter (Dn), total height (AT), stem height (AF) and crown diameter (DC) of 60 trees were measured. Those trees were identified on an air-borne LiDAR dataset and the same variables were measured (namely ATL, AFL and DCL, where L stands for LiDAR), except for Dn since it is not possible to measure it directly from LiDAR. Above-ground tree biomass was determined based on Dn and an allometric equation previously developed by other authors. Using the regression technique seven linear and five nonlinear models were adjusted, choosing the one with the lowest mean square root of the error (RMSE), the largest R2adj and the lowest value of the Akaike information criterion, in addition to the compliance of regression assumptions. The selected model is exponential with ATL and DCL variables to estimate biomass: RMSE = 406.70, R2adj = 0.8107 and AIC = 723.88.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Pinus hartwegii Lindl.]]></kwd>
<kwd lng="es"><![CDATA[árboles individuales]]></kwd>
<kwd lng="es"><![CDATA[bosque templado]]></kwd>
<kwd lng="es"><![CDATA[inventario forestal]]></kwd>
<kwd lng="es"><![CDATA[LiDAR]]></kwd>
<kwd lng="es"><![CDATA[sensores remotos]]></kwd>
<kwd lng="en"><![CDATA[Pinus hartwegii Lindl.]]></kwd>
<kwd lng="en"><![CDATA[forest inventory]]></kwd>
<kwd lng="en"><![CDATA[individual trees]]></kwd>
<kwd lng="en"><![CDATA[LiDAR]]></kwd>
<kwd lng="en"><![CDATA[temperate forest]]></kwd>
<kwd lng="en"><![CDATA[remote sensors]]></kwd>
</kwd-group>
</article-meta>
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