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Author Villacres, J.; Arevalo-Ramirez, T.; Fuentes, A.; Reszka, P.; Cheein, F.A.
Title (up) Foliar Moisture Content from the Spectral Signature for Wildfire Risk Assessments in Valparaiso-Chile Type
Year 2019 Publication Sensors Abbreviated Journal Sensors
Volume 19 Issue 24 Pages 17 pp
Keywords fuel moisture content; wildland urban interface; leaves spectral signature
Abstract Fuel moisture content (FMC) proved to be one of the most relevant parameters for controlling fire behavior and risk, particularly at the wildland-urban interface (WUI). Data relating FMC to spectral indexes for different species are an important requirement identified by the wildfire safety community. In Valparaiso, the WUI is mainly composed of Eucalyptus Globulus and Pinus Radiata-commonly found in Mediterranean WUI areas-which represent the 97.51% of the forests plantation inventory. In this work we study the spectral signature of these species under different levels of FMC. In particular, we analyze the behavior of the spectral reflectance per each species at five dehydration stages, obtaining eighteen spectral indexes related to water content and, for Eucalyptus Globulus, the area of each leave-associated with the water content-is also computed. As the main outcome of this research, we provide a validated linear regression model associated with each spectral index and the fuel moisture content and moisture loss, per each species studied.
Address [Villacres, Juan; Arevalo-Ramirez, Tito; Cheein, Fernando Auat] Univ Tecn Federico Santa Maria, Dept Elect Engn, Valparaiso 2390123, Chile, Email: juan.villacres@sansano.usm.cl;
Corporate Author Thesis
Publisher Mdpi Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1424-8220 ISBN Medium
Area Expedition Conference
Notes WOS:000517961400138 Approved
Call Number UAI @ eduardo.moreno @ Serial 1119
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Author Arevalo-Ramirez, T.; Villacres, J.; Fuentes, A.; Reszka, P.; Cheein, F.A.A.
Title (up) Moisture content estimation of Pinus radiata and Eucalyptus globulus from reconstructed leaf reflectance in the SWIR region Type
Year 2020 Publication Biosystems Engineering Abbreviated Journal Biosyst. Eng.
Volume 193 Issue Pages 187-205
Keywords SWIR reconstruction; Machine learning; Spectral indices; Fuel moisture content; Equivalent water thickness
Abstract Valparaiso, 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 flammable 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 nm-2500 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. (C) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.
Address [Arevalo-Ramirez, Tito; Villacres, Juan; Auat Cheein, Fernando A.] Univ Tecn Fedrico Santa Maria, Dept Ingn Elect, Valparaiso, Chile, Email: fernando.auat@usm.cl
Corporate Author Thesis
Publisher Academic Press Inc Elsevier Science Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1537-5110 ISBN Medium
Area Expedition Conference
Notes WOS:000526114500016 Approved
Call Number UAI @ eduardo.moreno @ Serial 1150
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Author Villacres, J.; Fuentes, A.; Reszka, P.; Cheein, F.A.
Title (up) Retrieval of Vegetation Indices Related to Leaf Water Content from a Single Index: A Case Study of Eucalyptus globulus (Labill.) and Pinus radiata (D. Don.) Type
Year 2021 Publication Plants-Basel Abbreviated Journal Plants-Basel
Volume 10 Issue 4 Pages 697
Keywords fuel moisture content; vegetation indices; spectral reflectance; Eucalyptus globulus; Pinus radiata
Abstract The vegetation indices derived from spectral reflectance have served as an indicator of vegetation's biophysical and biochemical parameters. Some of these indices are capable of characterizing more than one parameter at a time. This study examines the feasibility of retrieving several spectral vegetation indices from a single index under the assumption that all these indices are correlated with water content. The models used are based on a linear regression adjusted with least squares. The spectral signatures of Eucalyptus globulus and Pinus radiata, which constitute 97.5% of the forest plantation in Valparaiso region in Chile, have been used to test and validate the proposed approach. The linear models were fitted with an independent data set from which their performance was assessed. The results suggest that from the Leaf Water Index, other spectral indices can be recovered with a root mean square error up to 0.02, a bias of 1.12%, and a coefficient of determination of 0.77. The latter encourages using a sensor with discrete wavelengths instead of a continuum spectrum to estimate the forestry's essential parameters.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2223-7747 ISBN Medium
Area Expedition Conference
Notes WOS:000643526900001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1370
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