Artículo
Measuring land surface temperature, near-infrared and short-wave infrared reflectance for estimation of water availability in vegetation
Fecha de publicación:
01/2021
Editorial:
Elsevier
Revista:
MethodsX
e-ISSN:
2215-0161
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The vegetation water status is a crucial variable for modelling of drought impact, vegetation productivity and water fluxes. Methods for spatial estimation of this variable still need to be improved. The integration of remotely sensed data of land surface temperature (LST) and water vegetation indices based on near-infrared (NIR) and short-wave infrared (SWIR) reflectance for estimation of vegetation water content and water available for evapotranspiration require more analysis. This study contains a detailed method and measurements of LST, NIR and SWIR reflectance of soybean, corn and barley taken in field campaigns in central Argentine Pampas and laboratory with a ST PRO Raytek (8–14 µm) and a spectrometer SVC HR-1024i (0.35 and 2.5 µm). Also, relative water content of leaves was measured in laboratory during the dehydration process. This method and dataset could be also used for researching other wavelengths between 0.35 and 2.5 µm as indicator of water vegetation status (e.g. solar-induced chlorophyll fluorescence, photosynthesis). • Procedures useful to measure field spectra of vegetation are presented. • Not only the traditional method to measure leaves spectra in laboratory, but also in field were applied. • The method allows the integration of spectra and thermal data as a proxy of vegetation water status.
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos(CCT - TANDIL)
Articulos de CTRO CIENTIFICO TECNOLOGICO CONICET - TANDIL
Articulos de CTRO CIENTIFICO TECNOLOGICO CONICET - TANDIL
Citación
Holzman, Mauro Ezequiel; Rivas, Raúl Eduardo; Bayala, Martin Ignacio; Pasapera, José; Measuring land surface temperature, near-infrared and short-wave infrared reflectance for estimation of water availability in vegetation; Elsevier; MethodsX; 8; 1-2021; 1-4
Compartir
Altmétricas