## 6 Summary and Conclusions  
This paper presents a comprehensive overview of temperature-based models used for estimating evapotranspiration (ET). The discussion begins by introducing the surface energy balance concept and key variables, including sensible heat flux, ground heat flux, and latent heat flux. Subsequently, various temperature-based ET models are explored, emphasizing their strengths, weaknesses, and historical evolution. Over a retrospective analysis spanning 15 years, modifications proposed by researchers, validation studies, and intercomparisons among these models are synthesized. Additionally, the article investigates the impact of advancements in satellite missions on improving ET estimation models, highlighting the significance of emerging earth observation missions. The review of the existing work in the field of remote sensing related to ET estimation is a cornerstone for progress. The comprehensive examination of RS models allows for their deep understanding, for identifying their strengths and limitations, and for developing more robust and reliable ET estimation models.  
The performance of these models varies across different regions and environmental conditions. As such, classification and cross-comparison of these models are of substantial importance. This approach enables practitioners to select the most appropriate model for a specific set of conditions, enhancing the accuracy of ET estimates. It is important to acknowledge that no single ET estimation model is universally perfect. Different models excel under different scenarios and environmental conditions. Expanding on prior research efforts, this work provides support for the selection of models based on the specific requirements of a study area or application. The intercomparison between the ET models did not involve identical models, as the studies in question primarily employed different models. Nevertheless, it is essential to recognize that these studies were distinct in their objectives and methods. Despite this diversity, the overall crosscutting comparison can yield valuable insights and serve as a robust foundation for future investigations.  
One of the most promising aspects of the development of ET estimation models is using the most recent technologies and employing hybrid approaches. Emerging technologies, such as machine learning and advanced remote sensing techniques, can enhance the precision and accuracy of ET estimates. Hybrid models that combine the strengths of multiple approaches can harness the advantages of each method, leading to more robust and adaptable ET estimation tools.  
The emerging missions and advancements in the field of remote sensing will radically enhance the accuracy of the developed ET estimation models. More specifically, the new missions are equipped with technologically advanced optical and radar sensors with improved spatial and temporal resolutions and hold promising prospects for upgrading the precision and reliability of ET estimations.  
Resources Management project). The project reference is Ref. ESA-CIP-POE-DT-sp-LE-2021-882, and it falls under Budget Line E/A105-01-EarthScience Block 4.  
**Data Availability Statement**: Not applicable.  
**Conflicts of Interest**: [PERSON] was employed by Planetek Hellas, [PERSON] and [PERSON] were employed by Planetek Italia. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.