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Spectral unmixing approach in hyperspectral remote sensing: a tool for oil palm mapping

Desmezclado espectral en percepción remota hiperespectral: una herramienta para el mapeo de palma aceitera

dc.creatorVargas, Hector
dc.creatorCamacho Velasco, Ariolfo
dc.creatorArguello, Henry
dc.date2019-05-15
dc.date.accessioned2021-03-18T21:12:26Z
dc.date.available2021-03-18T21:12:26Z
dc.identifierhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1228
dc.identifier10.22430/22565337.1228
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/11781
dc.descriptionOil palm plantations typically span large areas; therefore, remote sensing has become a useful tool for advanced oil palm monitoring. This work reviews and evaluates two approaches to analyze oil palm plantations based on hyperspectral remote sensing data: linear spectral unmixing and spectral variability. Moreover, a computational framework based on spectral unmixing for the estimation of fractional abundances of oil palm plantations is proposed in this study. Such approach also considers the spectral variability of hyperspectral image signatures. More specifically, the proposed computational framework modifies the linear mixing model by introducing a weighting vector, so that the spectral bands that contribute the least to the estimation of erroneous fractional abundances can be identified. This approach improves palm detection as it allows to differentiate them from other materials in terms of fractional abundances. Experimental results obtained from hyperspectral remote sensing data in the range 410-990 nm show improvements of 8.18 % in User Accuracy (Uacc) in the identification of oil palms by the proposed framework with respect to traditional unmixing methods. Thus, the proposed method achieved a 95% Uacc. This confirms the capabilities of the proposed computational framework and facilitates the management and monitoring of large areas of oil palm plantations.en-US
dc.descriptionLas plantaciones de palma de aceite típicamente abarcan grandes áreas, por esto, la teledetección remota se ha convertido en una herramienta útil para el monitoreo avanzado de este cultivo. Este trabajo revisa y evalúa dos enfoques para analizar las plantaciones de palma de aceite a partir de datos de teledetección remota hiperespectral: desmezclado espectral lineal y variabilidad espectral. Además, se propone un marco computacional basado en el desmezclado espectral para la estimación de las fracciones de abundancias de cultivos de palma de aceite. Este enfoque también considera la variabilidad espectral de las firmas en las imágenes hiperespectrales. El marco computacional propuesto modifica el modelo de mezcla lineal mediante la introducción de un vector de pesos, de manera que se puedan identificar las bandas espectrales que menos contribuyen a la estimación de fracciones de abundancias erróneas. Este enfoque aprovecha la detección de los árboles de palma de aceite, ya que permite diferenciarlos de otros materiales en términos de fracciones de abundancia. Los resultados experimentales obtenidos a partir de datos de teledetección remota hiperespectral en el rango de 410-990 nm, muestran mejoras de un 8.18 % en la métrica de Precisión del Usuario (Uacc) en la identificación de palmas de aceite por el marco propuesto con respecto a los métodos tradicionales de desmezclado espectral; el método propuesto logró un 95 % de Uacc. Esto confirma las capacidades del marco computacional formulado y facilita la gestión y el monitoreo de grandes áreas de plantaciones de palma de aceite.es-ES
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dc.languageeng
dc.publisherInstituto Tecnológico Metropolitano (ITM)en-US
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1228/1192
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1228/1290
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1228/1398
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dc.rightsCopyright (c) 2019 TecnoLógicasen-US
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0en-US
dc.sourceTecnoLógicas; Vol. 22 No. 45 (2019); 129-143en-US
dc.sourceTecnoLógicas; Vol. 22 Núm. 45 (2019); 129-143es-ES
dc.source2256-5337
dc.source0123-7799
dc.subjectHyperspectralen-US
dc.subjectSpectral Variabilityen-US
dc.subjectUnmixingen-US
dc.subjectEndmemberen-US
dc.subjectAbundanceen-US
dc.subjectOil palmen-US
dc.subjectHiperespectrales-ES
dc.subjectVariabilidad Espectrales-ES
dc.subjectDesmezcladoes-ES
dc.subjectFirmas Purases-ES
dc.subjectAbundanciases-ES
dc.subjectPalma de Aceitees-ES
dc.titleSpectral unmixing approach in hyperspectral remote sensing: a tool for oil palm mappingen-US
dc.titleDesmezclado espectral en percepción remota hiperespectral: una herramienta para el mapeo de palma aceiteraes-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeResearch Papersen-US
dc.typeArtículos de investigaciónes-ES


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