Correlation Analysis of Evapotranspiration, Emissivity Contrast and Water Deficit Indices: A Case Study in Four Eddy Covariance Sites in Italy with Different Environmental Habitats

Michele Torresani (), Guido Masiello, Nadia Vendrame, Giacomo Gerosa, Marco Falocchi, Enrico Tomelleri, Carmine Serio, Duccio Rocchini and Dino Zardi
Additional contact information
Michele Torresani: Faculty of Science and Technology, Free University of Bolzano/Bozen, Piazza Università/Universitätsplatz 1, 39100 Bolzano/Bozen, Italy
Guido Masiello: School of Engineering, University of Basilicata, Via Ateneo Lucano 10, 85100 Potenza, Italy
Nadia Vendrame: Center Agriculture Food Environment (C3A), University of Trento, 38010 San Michele All’Adige, Italy
Giacomo Gerosa: Department of Mathematics and Physics, Università Cattolica del Sacro Cuore, 25121 Brescia, Italy
Marco Falocchi: Cisma S.r.l., Via Ipazia 2 c/o NOI Techpark, 39100 Bolzano, Italy
Enrico Tomelleri: Faculty of Science and Technology, Free University of Bolzano/Bozen, Piazza Università/Universitätsplatz 1, 39100 Bolzano/Bozen, Italy
Carmine Serio: School of Engineering, University of Basilicata, Via Ateneo Lucano 10, 85100 Potenza, Italy
Duccio Rocchini: BIOME Lab., Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, Via Irnerio 42, 40126 Bologna, Italy
Dino Zardi: Department of Civil, Environmental and Mechanical Engineering, University of Trento, 38123 Trento, Italy

Land, 2022, vol. 11, issue 11, 1-16

Abstract: Evapotranspiration (ET) represents one of the essential processes controlling the exchange of energy by terrestrial vegetation, providing a strong connection between energy and water fluxes. Different methodologies have been developed in order to measure it at different spatial scales, ranging from individual plants to an entire watershed. In the last few years, several methods and approaches based on remotely sensed data have been developed over different ecosystems for the estimation of ET. In the present work, we outline the correlation between ET measured at four eddy covariance (EC) sites in Italy (situated either in forest or in grassland ecosystems) and (1) the emissivity contrast index (ECI) based on emissivity data from thermal infrared spectral channels of the MODIS and ASTER satellite sensors (CAMEL data-set); (2) the water deficit index (WDI), defined as the difference between the surface and dew point temperature modeled by the ECMWF (European Centre for Medium-Range Weather Forecasts) data. The analysis covers a time-series of 1 to 7 years depending on the site. The results showed that both the ECI and WDI correlate to the ET calculated through EC. In the relationship WDI-ET, the coefficient of determination ranges, depending on the study area, between 0.5 and 0.9, whereas it ranges between 0.5 and 0.7 when ET was correlated to the ECI. The slope and the sign of the latter relationship is influenced by the vegetation habitat, the snow cover (particularly in winter months) and the environmental heterogeneity of the area (calculated in this study through the concept of the spectral variation hypothesis using Rao’s Q heterogeneity index).

Keywords: emissivity; evapotranspiration; heterogeneity; Rao’s Q index; spectral variation hypothesis; thermal infrared (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2073-445X/11/11/1903/pdf (application/pdf)
https://www.mdpi.com/2073-445X/11/11/1903/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:11:p:1903-:d:954140

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().