**5. Conclusions and Outlook**

In this study, the correlation between data of ET derived from four eddy covariance sites in Italy (Renon in the Province of Bolzano, Monte Bondone and Lavarone in the Province of Trento and Bosco della Fontana in the Province of Mantova) and two indices— (1) the emissivity contrast index, or ECI; (2) the water stress index, or WDI—was assessed. Both indices were shown to correlate with in situ observations, which is good from the perspective of using remote-sensed data to monitor the state of vegetation from satellite. The correlation ECI-ET is influenced by the habitat heterogeneity and by the presence of snow/water in the surface. This could be critical, especially in areas covered by snow (e.g., mountain regions in winter), with surface water or with high environmental heterogeneity. The WDI showed generally fewer uncertainties in detecting the correct evolution of ET, in that the index is directly related to the thermodynamic parameters that govern ET and to the intensity of solar radiation. Furthermore, we believe that the synergistic use of

the ECI and WDI could lead to a more accurate ET estimation, bringing the benefits of both indices. Improvements on this side would also be greatly beneficial for providing a more accurate input to numerical weather and climate prediction models, for which, reliable estimates of fluxes over snow-covered terrain are still a challenging situation [67,68].

Further refinements can also be obtained from a more precise evaluation of ET from EC, taking into account timescales associated with different atmospheric conditions [69]. This is particularly applicable to the mountainous sites, where daily periodic flows, such as thermally driven slope wind and valley winds, are well established, and documented meteorological features of the mountain boundary layer [70–72]. This goal is among the scopes of the ongoing international cooperation effort TEAMx (Multi-Scale Transport and Exchange Processes in the Atmosphere over Mountains–Program and Experiment) through intensive field campaigns performed at selected target areas in the Alps, combining ground-based, airborne and remote sensing observations [73].

**Author Contributions:** Data curation, M.F.; Investigation, E.T. ; Methodology, G.G.; Supervision, D.R. and D.Z.; Writing—original draft, M.T.; Writing—review & editing, G.M., N.V. and C.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was carried out in the framework of the project 'OT4CLIMA', which was funded by the Italian Ministry of Education, University and Research (D.D. 2261 del 6.9.2018, PON R&I 2014-2020 and FSC). M.T. and D.R. were partially supported by the European Union's Horizon 2020 research and innovation program under gran<sup>t</sup> agreemen<sup>t</sup> No 862480 (SHOWCASE). DR was partially supported by the Horizon Europe project EarthBridge and by the H2020 COST Action CA17134 'Optical synergies for spatiotemporal sensing of scalable ecophysiological traits (SENSECO).

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.
