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dc.contributor.authorRomán Fernández, José Raúl
dc.contributor.authorRodríguez Caballero, Emilio
dc.contributor.authorRodríguez Lozano, Borja
dc.contributor.authorRoncero Ramos, Beatriz
dc.contributor.authorChamizo de la Piedra, Sonia
dc.contributor.authorÁguila Carricondo, María del Pilar
dc.contributor.authorCantón Castilla, María Yolanda
dc.date.accessioned2020-01-17T12:18:45Z
dc.date.available2020-01-17T12:18:45Z
dc.date.issued2019-06-05
dc.identifier.issn2072-4292
dc.identifier.urihttp://hdl.handle.net/10835/7551
dc.description.abstractChlorophyll a concentration (Chla) is a well-proven proxy of biocrust development, photosynthetic organisms’ status, and recovery monitoring after environmental disturbances. However, laboratory methods for the analysis of chlorophyll require destructive sampling and are expensive and time consuming. Indirect estimation of chlorophyll a by means of soil surface reflectance analysis has been demonstrated to be an accurate, cheap, and quick alternative for chlorophyll retrieval information, especially in plants. However, its application to biocrusts has yet to be harnessed. In this study we evaluated the potential of soil surface reflectance measurements for non-destructive Chla quantification over a range of biocrust types and soils. Our results revealed that from the different spectral transformation methods and techniques, the first derivative of the reflectance and the continuum removal were the most accurate for Chla retrieval. Normalized difference values in the red-edge region and common broadband indexes (e.g., normalized difference vegetation index (NDVI)) were also sensitive to changes in Chla. However, such approaches should be carefully adapted to each specific biocrust type. On the other hand, the combination of spectral measurements with non-linear random forest (RF) models provided very good fits (R2 > 0.94) with a mean root mean square error (RMSE) of about 6.5 µg/g soil, and alleviated the need for a specific calibration for each crust type, opening a wide range of opportunities to advance our knowledge of biocrust responses to ongoing global change and degradation processes from anthropogenic disturbance.es_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBiocrustses_ES
dc.subjectbiological soil crustes_ES
dc.subjectchlorophyll quantificationes_ES
dc.subjecthyperspectrales_ES
dc.subjectrandom forestes_ES
dc.subjectremote sensinges_ES
dc.titleSpectral Response Analysis: An Indirect and Non-Destructive Methodology for the Chlorophyll Quantification of Biocrustses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/2072-4292/11/11/1350es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional