Research Paper Moisture content estimation of Pinus radiata and Eucalyptus globulus from reconstructed leaf reflectance in the SWIR region Tito Arevalo-Ramirez a , Juan Villacr  es a , Andr  es Fuentes b , Pedro Reszka c , Fernando A. Auat Cheein a,* a Departamento de Ingenierı´a Electr onica, Universidad T ecnica Fedrico Santa Marı´a, Valparaiso, Chile b Departamento de Industrias, Universidad T ecnica Federico Santa Marı´a, Valparaiso, Chile c Facultad de Ingenierı´a y Ciencias, Universidad Adolfo Ib a~ nez, Santiago, Chile article info Article history: Received 7 November 2019 Received in revised form 25 February 2020 Accepted 4 March 2020 Published online 19 March 2020 Keywords: SWIR reconstruction Machine learning Spectral indices Fuel moisture content Equivalent water thickness Valparaı´so, a central-southern region in Chile, has one of the highest rates of wildfire occurrence in the country. The constant threat of fires is mainly due to its highly flam- mable forest plantation, composed of 97.5% Pinus radiata and Eucalyptus globulus. Fuel moisture content is one of the most relevant parameters for studying fire spreading and risk, and can be estimated from the reflectance of leaves in the short wave infra-red (SWIR) range, not easily available in most vision-based sensors. Therefore, this work addresses the problem of estimating the water content of leaves from the two previously mentioned species, without any knowledge of their spectrum in the SWIR band. To this end, and for validation purposes, the reflectance of 90 leaves per species, at five dehydration stages, were taken between 350 nm and 2500 nm (full spectrum). Then, two machine-learning regressors were trained with 70% of the data set to determine the unknown reflectance, in the range 1000 nme2500 nm. Results were validated with the remaining 30% of the data, achieving a root mean square error less than 9% in the spectrum estimation, and an error of 10% in spectral indices related to water content estimation. © 2020 IAgrE. Published by Elsevier Ltd. All rights reserved. 1. Introduction During the 2017 wildfire season, Chile was affected by severe fires that claimed the lives of 11 people, burned more than 550,000 ha and destroyed more than 1000 structures (Corporaci  on Nacional Forestal, 2018; G omez-Gonz alez, Ojeda, & Fernandes, 2018). Since 2017, Valparaı ´so has experienced an average of 909 fires per year. Valparaı ´so’s mediterranean climate, topography and vegetation make it one of the most fire prone regions in Chile (Corporaci  on Nacional Forestal, 2018; de la Barrera, Barraza, Favier, Ruiz, & Quense, 2018). Its Wildland Urban Interface (WUI) vegetation is primarily composed by two flammable species, Pinus radiata and Euca- lyptus globulus (Heilmayr, Echeverrı ´a, Fuentes, & Lambin, 2016; Reszka & Fuentes, 2015). These species represent 97.51% of * Corresponding author. E-mail address: fernando.auat@usm.cl (F.A. Auat Cheein). Available online at www.sciencedirect.com ScienceDirect journal homepage: www.elsevier.com/locate/issn/15375110 biosystems engineering 193 (2020) 187 e205 https://doi.org/10.1016/j.biosystemseng.2020.03.004 1537-5110/© 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.