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dc.contributor.authorHernández Clemente, Rocío
dc.contributor.authorHornero, Alberto
dc.contributor.authorMöttus, Matti
dc.contributor.authorPenuelas, J.
dc.contributor.authorGonzález Dugo, V.
dc.contributor.authorJiménez, J. C.
dc.contributor.authorSuárez, L.
dc.contributor.authorAlonso, L.
dc.contributor.authorZarco-Tejada, Pablo J.
dc.date.accessioned2024-01-30T13:21:29Z
dc.date.available2024-01-30T13:21:29Z
dc.date.issued2019
dc.identifier.issn2198-6436
dc.identifier.urihttp://hdl.handle.net/10396/26846
dc.description.abstractPurpose of Review We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images. Recent Findings In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health. Summary The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.sourceCurrent Forestry Reports 5:169–183 (2019)es_ES
dc.subjectVegetation healthes_ES
dc.subjectHyperspectral and thermal dataes_ES
dc.subjectPhysiological indicatorses_ES
dc.subjectRadiative transfer modelses_ES
dc.subjectVegetation indiceses_ES
dc.titleEarly diagnosis of vegetation health from high-resolution hyperspectral and thermal imagery: lessons learned from empirical relationships and radiative transfer modellinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1007/s40725-019-00096-1es_ES
dc.relation.projectIDGobierno de España. QUERCUSATes_ES
dc.relation.projectIDGobierno de España. ESPECTRAMEDes_ES
dc.relation.projectIDUnión Europea. ERC-2013-SyG- 610028 IMBALANCE-P.es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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