remote sensing Technical Note Remote Sensing of Ecosystem Water Use Efficiency: A Review of Direct and Indirect Estimation Methods Wanyuan Cai , Sana Ullah , Lei Yan and Yi Lin *   Citation: Cai, W.; Ullah, S.; Yan, L.; Lin, Y. Remote Sensing of Ecosystem Water Use Efficiency: A Review of Direct and Indirect Estimation Methods. Remote Sens. 2021, 13, 2393. https://doi.org/10.3390/rs13122393 Academic Editors: Praveena Krishnan and Shusen Wang Received: 21 May 2021 Accepted: 17 June 2021 Published: 18 June 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Beijing Key Lab of Spatial Information Integration and 3S Application, Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China; caiwy@pku.edu.cn (W.C.); sana_ullah@pku.edu.cn (S.U.); lyan@pku.edu.cn (L.Y.) * Correspondence: yi.lin@pku.edu.cn; Tel.: +86-010-62751191 Abstract: Water use efficiency (WUE) is a key index for understanding the ecosystem of carbon–water coupling. The undistinguishable carbon–water coupling mechanism and uncertainties of indirect methods by remote sensing products and process models render challenges for WUE remote sensing. In this paper, current progress in direct and indirect methods of WUE estimation by remote sensing is reviewed. Indirect methods based on gross primary production (GPP)/evapotranspiration (ET) from ground observation, processed models and remote sensing are the main ways to estimate WUE in which carbon and water cycles are independent processes. Various empirical models based on meteorological variables and remote sensed vegetation indices to estimate WUE proved the ability of remotely sensed data for WUE estimating. The analytical model provides a mechanistic opportunity for WUE estimation on an ecosystem scale, while the hypothesis has yet to be validated and applied for the shorter time scales. An optimized response of canopy conductance to atmospheric vapor pressure deficit (VPD) in an analytical model inverted from the conductance model has been also challenged. Partitioning transpiration (T) and evaporation (E) is a more complex phenomenon than that stated in the analytic model and needs a more precise remote sensing retrieval algorithm as well as ground validation, which is an opportunity for remote sensing to extrapolate WUE estimation from sites to a regional scale. Although studies on controlling the mechanism of environmental factors have provided an opportunity to improve WUE remote sensing, the mismatch in the spatial and temporal resolution of meteorological products and remote sensing data, as well as the uncertainty of meteorological reanalysis data, add further challenges. Therefore, improving the remote sensing- based methods of GPP and ET, developing high-quality meteorological forcing datasets and building mechanistic remote sensing models directly acting on carbon–water cycle coupling are possible ways to improve WUE remote sensing. Improvement in direct WUE remote sensing methods or remote sensing-driven ecosystem analysis methods can promote a better understanding of the global ecosystem carbon–water coupling mechanisms and vegetation functions–climate feedbacks to serve for the future global carbon neutrality. Keywords: ecosystem water use efficiency; carbon–water cycle coupling; flux measurement; remote sensing; carbon neutrality 1. Introduction Water use efficiency (WUE) is a key metric of carbon–water coupling maintaining the trade-off between photosynthesis and water vapor loss on plant function, which is often defined as the ratio of gross primary production (GPP) and evapotranspiration (ET) on the ecosystem scale [1–6]. Previous studies have reported that the global forest WUE shows an upward trend with the rise in atmospheric carbon dioxide concentration as shown in Figure 1a,c [7,8]. However, based on satellite observations, the global average WUE has showed a significant downward trend before 2010, which is possibly due to the change in land use, and this phenomenon is improved during 2011–2014 as shown in Figure 1b[9]. Remote Sens. 2021, 13, 2393. https://doi.org/10.3390/rs13122393 https://www.mdpi.com/journal/remotesensing