{"id":25312,"date":"2025-11-24T15:06:55","date_gmt":"2025-11-24T14:06:55","guid":{"rendered":"https:\/\/www.yellowscan.com\/knowledge\/cuantificacion-del-consumo-de-combustible-en-incendios-de-brezales-con-lidar-uav\/"},"modified":"2025-11-24T15:08:16","modified_gmt":"2025-11-24T14:08:16","slug":"quantifying-fuel-consumption-in-heathland-fires-with-uav-lidar","status":"publish","type":"ys_knowledge","link":"https:\/\/www.yellowscan.com\/es\/knowledge\/quantifying-fuel-consumption-in-heathland-fires-with-uav-lidar\/","title":{"rendered":"Cuantificaci\u00f3n del consumo de combustible en incendios de brezales con LiDAR UAV"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"25312\" class=\"elementor elementor-25312 elementor-25265\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ca58d10 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ca58d10\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2a1f2be\" data-id=\"2a1f2be\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8a48bad elementor-widget elementor-widget-text-editor\" data-id=\"8a48bad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2 class=\"h3\">Desaf\u00edo<\/h2><p>El equipo de investigaci\u00f3n de la Universidad PXL de Ciencias Aplicadas y Artes llev\u00f3 a cabo este proyecto como parte de un esfuerzo m\u00e1s amplio por desarrollar m\u00e9todos cuantitativos para estimar los tipos y cargas de combustible en general y el consumo de combustible en las quemas prescritas en particular. Las evaluaciones tradicionales sobre el terreno llevaban mucho tiempo y a menudo eran imprecisas, por lo que resultaba dif\u00edcil evaluar el consumo de combustible en diversas estructuras de vegetaci\u00f3n. <\/p><p>El objetivo era explorar c\u00f3mo el LiDAR montado en UAV pod\u00eda servir como herramienta de alta resoluci\u00f3n y espacialmente expl\u00edcita para cuantificar los vol\u00famenes de combustible quemado durante los incendios prescritos. El equipo pretend\u00eda comparar la estructura de la vegetaci\u00f3n antes y despu\u00e9s del incendio y diferenciar el consumo de combustible por tipo de vegetaci\u00f3n: brezo, hierba y \u00e1rboles. <\/p><p>Para conseguirlo, necesitaban un m\u00e9todo que fuera r\u00e1pido, preciso y repetible. El flujo de trabajo deb\u00eda <\/p><ul><li>Capta la estructura de la vegetaci\u00f3n antes y despu\u00e9s de la quema,<\/li><li>Medir la p\u00e9rdida de altura y volumen como indicador del consumo de combustible, y<\/li><li>Clasifica autom\u00e1ticamente los tipos de vegetaci\u00f3n utilizando datos LiDAR y RGB.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-4e166c25 el-section-full el-section-img-x2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4e166c25\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-63b958bc\" data-id=\"63b958bc\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5fe5a0cf elementor-widget elementor-widget-image\" data-id=\"5fe5a0cf\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"525\" height=\"655\" src=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Vegetation-identification-based-on-superpixels.png\" class=\"attachment-large size-large wp-image-25278\" alt=\"Vegetation identification based on superpixels\" srcset=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Vegetation-identification-based-on-superpixels.png 525w, https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Vegetation-identification-based-on-superpixels-240x300.png 240w\" sizes=\"(max-width: 525px) 100vw, 525px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-672a8b4a el-img-caption elementor-widget elementor-widget-text-editor\" data-id=\"672a8b4a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: center;\">Identificaci\u00f3n de la vegetaci\u00f3n basada en superp\u00edxeles. Esta figura muestra el brezo dominante (de color morado) extendido por la zona de estudio, seguido de la hierba (amarillo) y los \u00e1rboles (marr\u00f3n) que s\u00f3lo aparecen localmente. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-2e9280a\" data-id=\"2e9280a\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5246089d elementor-widget elementor-widget-image\" data-id=\"5246089d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"303\" height=\"361\" src=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Orthophoto-after-the-prescribed-burn.png\" class=\"attachment-large size-large wp-image-25283\" alt=\"Orthophoto after the prescribed burn\" srcset=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Orthophoto-after-the-prescribed-burn.png 303w, https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Orthophoto-after-the-prescribed-burn-252x300.png 252w\" sizes=\"(max-width: 303px) 100vw, 303px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-61c3a3da el-img-caption elementor-widget elementor-widget-text-editor\" data-id=\"61c3a3da\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: center;\">Ortofoto tras la quema prescrita.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-765207b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"765207b\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-167652d\" data-id=\"167652d\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-01476bb elementor-widget elementor-widget-text-editor\" data-id=\"01476bb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2 class=\"h3\">Soluci\u00f3n<\/h2><p>Para cumplir estos requisitos, los investigadores utilizaron el sistema <a href=\"https:\/\/www.yellowscan.com\/es\/products\/surveyor_ultra\/\">YellowScan Surveyor Ultra<\/a> V2, montado en un UAV DJI Matrice 300 RTK. El sistema Surveyor Ultra proporcion\u00f3 nubes de puntos 3D de alta densidad capaces de captar detalles tanto del dosel como de debajo del dosel. <\/p><p>La planificaci\u00f3n de la misi\u00f3n dur\u00f3 un d\u00eda, seguido de medio d\u00eda de adquisici\u00f3n de datos y medio d\u00eda de procesamiento inicial en <a href=\"https:\/\/www.yellowscan.com\/es\/productos\/cloudstation\/\">YellowScan CloudStation<\/a>. El postprocesamiento se complet\u00f3 en el software R, donde la clasificaci\u00f3n Superpixel permiti\u00f3 la segmentaci\u00f3n automatizada del tipo de vegetaci\u00f3n y el c\u00e1lculo preciso de los \u00edndices de consumo de combustible. El flujo de trabajo completo, incluido el an\u00e1lisis estad\u00edstico, se complet\u00f3 en dos semanas.  <\/p><p>Se realizaron dos vuelos, uno antes y otro despu\u00e9s de la quema prescrita, cada uno a una altitud de 70 metros AGL y una velocidad de 5 m\/s, cubriendo un brezal de 1,3 hect\u00e1reas. La perfecta compatibilidad del Surveyor Ultra con el software YellowScan CloudStation y R garantiz\u00f3 una transici\u00f3n coherente y eficaz de la recogida de datos al an\u00e1lisis cuantitativo. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5ee7ade0 el-section-img-x1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5ee7ade0\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5b51e6da\" data-id=\"5b51e6da\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-44b9979c elementor-widget elementor-widget-image\" data-id=\"44b9979c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"493\" height=\"288\" src=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Slice-depicting-vegetation-structure-before-and-after-the-prescribed-burn.png\" class=\"attachment-large size-large wp-image-25288\" alt=\"Slice depicting vegetation structure before and after the prescribed burn\" srcset=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Slice-depicting-vegetation-structure-before-and-after-the-prescribed-burn.png 493w, https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Slice-depicting-vegetation-structure-before-and-after-the-prescribed-burn-300x175.png 300w\" sizes=\"(max-width: 493px) 100vw, 493px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a7c7ca9 el-img-caption elementor-widget elementor-widget-text-editor\" data-id=\"a7c7ca9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: center;\">Corte que representa la estructura de la vegetaci\u00f3n antes (morado) y despu\u00e9s (verde) de la quema prescrita. La diferencia vertical puede utilizarse como indicador del consumo de combustible. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-612566d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"612566d\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-928ff35\" data-id=\"928ff35\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-9b0f752 elementor-widget elementor-widget-text-editor\" data-id=\"9b0f752\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2 class=\"h3\">Par\u00e1metros de la misi\u00f3n<\/h2><ul><li><strong>Tama\u00f1o de la encuesta<\/strong>: sistema de brezales de 1,3 ha<\/li><li><strong>Duraci\u00f3n<\/strong>: Planificaci\u00f3n 1 d\u00eda, adquisici\u00f3n 0,5 d\u00edas, procesamiento 0,5 d\u00edas (procesamiento completo, incluida la clasificaci\u00f3n de superp\u00edxeles y el c\u00e1lculo de los \u00edndices de consumo de combustible en el software R: 2 semanas).<\/li><li><strong>Vuelos<\/strong>: 2 (antes y despu\u00e9s del incendio)<\/li><li><strong>Altitud y velocidad de vuelo<\/strong>: 70 m AGL a 5 m\/s<\/li><li><strong>Equipamiento<\/strong>: Sistema LiDAR <a href=\"https:\/\/www.yellowscan.com\/es\/products\/surveyor_ultra\/\">YellowScan Surveyor Ultra<\/a> V2, DJI Matrice 300 RTK, <a href=\"https:\/\/www.yellowscan.com\/es\/productos\/cloudstation\/\">YellowScan CloudStation<\/a>, postprocesado en software R<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-73f89813 el-section-img-x1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"73f89813\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-55014712\" data-id=\"55014712\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-40a0dace elementor-widget elementor-widget-image\" data-id=\"40a0dace\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"770\" height=\"241\" src=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Slice-depicting-vegetation-structure-before-and-after-the-prescribed-burn_02.png\" class=\"attachment-large size-large wp-image-25293\" alt=\"Pointcloud slice showing the trees who did not burn.\" srcset=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Slice-depicting-vegetation-structure-before-and-after-the-prescribed-burn_02.png 770w, https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Slice-depicting-vegetation-structure-before-and-after-the-prescribed-burn_02-300x94.png 300w, https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/Slice-depicting-vegetation-structure-before-and-after-the-prescribed-burn_02-768x240.png 768w\" sizes=\"(max-width: 770px) 100vw, 770px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-22246152 el-img-caption elementor-widget elementor-widget-text-editor\" data-id=\"22246152\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: center;\">Corte que representa la estructura de la vegetaci\u00f3n antes (morado) y despu\u00e9s (verde) de la quema prescrita. La diferencia vertical puede utilizarse como indicador del consumo de combustible. Puede verse que el arbolado y la vegetaci\u00f3n del sotobosque no ardieron.  <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-fee1854 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fee1854\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-0fc7d4a\" data-id=\"0fc7d4a\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a8f0286 elementor-widget elementor-widget-text-editor\" data-id=\"a8f0286\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2 class=\"h3\">Resultados<\/h2><p>El <a href=\"https:\/\/www.yellowscan.com\/es\/products\/surveyor_ultra\/\">YellowScan Surveyor<\/a> Ultra permiti\u00f3 una medici\u00f3n precisa y r\u00e1pida de la estructura de la vegetaci\u00f3n antes y despu\u00e9s de la quema prescrita, lo que permiti\u00f3 al equipo cuantificar el consumo de combustible con gran precisi\u00f3n espacial. Mediante la segmentaci\u00f3n Superpixel, se clasificaron tres tipos de vegetaci\u00f3n (pastizales, brezos y \u00e1rboles con vegetaci\u00f3n de sotobosque) con una precisi\u00f3n del 97,8%. <\/p><p>El an\u00e1lisis del consumo de combustible revel\u00f3 claras diferencias entre los tipos de vegetaci\u00f3n. El brezo mostr\u00f3 la mayor reducci\u00f3n media de altura (0,165 \u00b1 0,102 m), mientras que la hierba (0,089 \u00b1 0,088 m) y la vegetaci\u00f3n arb\u00f3rea del sotobosque (0,091 \u00b1 0,068 m) mostraron un consumo menor. El an\u00e1lisis estad\u00edstico confirm\u00f3 que todas las diferencias entre tipos de vegetaci\u00f3n eran significativas (p &lt; 0,001).  <\/p><p>Esta metodolog\u00eda proporciona pruebas cuantitativas para desarrollar protocolos de quema prescrita espec\u00edficos para la vegetaci\u00f3n y destaca la importancia de recopilar datos de teledetecci\u00f3n antes y despu\u00e9s del incendio para que las estrategias de gesti\u00f3n de incendios forestales sean eficaces.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-604d6048 elm-testimonial elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"604d6048\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6930d381\" data-id=\"6930d381\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4de5aa2e elm-testimonial__text elementor-widget elementor-widget-text-editor\" data-id=\"4de5aa2e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>El YellowScan Surveyor Ultra permiti\u00f3 medir con precisi\u00f3n y rapidez la estructura de la vegetaci\u00f3n antes y despu\u00e9s de la quema prescrita, lo que nos permiti\u00f3 cuantificar el consumo de combustible con una precisi\u00f3n espacial ultraelevada.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-1a5adcf2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1a5adcf2\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-386e231a\" data-id=\"386e231a\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6ff5e48e elm-testimonial__img elementor-widget elementor-widget-image\" data-id=\"6ff5e48e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"218\" height=\"231\" src=\"https:\/\/www.yellowscan.com\/wp-content\/uploads\/2025\/11\/sam_ottoy.jpg\" class=\"attachment-large size-large wp-image-25298\" alt=\"Sam Ottoy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-3072efdf\" data-id=\"3072efdf\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-3c7a8096 elementor-widget elementor-widget-text-editor\" data-id=\"3c7a8096\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<strong><span class=\"elm-testimonials__name\">Sam Ottoy<\/span><\/strong>\n\n<span class=\"elm-testimonials__role\"><em>PXL Universidad de Ciencias Aplicadas y Artes Director de proyecto<\/em>\n<\/span>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"featured_media":25270,"menu_order":9,"template":"","meta":{"_acf_changed":false,"content-type":""},"categories":[87],"class_list":["post-25312","ys_knowledge","type-ys_knowledge","status-publish","has-post-thumbnail","hentry","category-success-story"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Cuantificaci\u00f3n del consumo de combustible en incendios de brezales con UAV LiDAR<\/title>\n<meta name=\"description\" content=\"Descubre c\u00f3mo el LiDAR UAV mide con precisi\u00f3n el consumo de combustible en las quemas prescritas, con an\u00e1lisis de vegetaci\u00f3n de alta resoluci\u00f3n.\" \/>\n<meta name=\"robots\" content=\"index, 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