Laipelt et al. (2025) Assessing the Performance of Multiple Satellite-Based Evapotranspiration Models over Tropical Forests

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-12-22
• Authors: Leonardo Laipelt, Ayan Santos Fleischmann, Anderson Ruhoff
• DOI: 10.3390/rs18010030

Research Groups

Not specified in the provided text.

Short Summary

This study evaluates the performance of four remote sensing-based evapotranspiration (ET) models in tropical forests, comparing their estimations against flux tower observations and assessing their response to deforestation. The findings demonstrate that these models show good agreement with observations and can effectively monitor ET and the impacts of deforestation on a global scale.

Objective

• To evaluate the performance of four remote sensing-based evapotranspiration (ET) models (SSEBop, geeSEBAL, PT-JPL, and T-SEB) in tropical forests.
• To compare model estimations against flux tower observations and assess uncertainty driven by different meteorological input forcings.
• To conduct a spatial–temporal analysis of models’ response to the impact of deforestation on ET patterns.

Study Configuration

• Spatial Scale: Global scale, focusing on tropical forests across Africa, America, and Asia.
• Temporal Scale: Long-term, with a spatial–temporal analysis of ET patterns.

Methodology and Data

• Models used: SSEBop, geeSEBAL, PT-JPL, T-SEB (remote sensing-based ET models).
• Data sources: Remote sensing data, flux tower observations, meteorological input forcings (e.g., ERA5-Land).

Main Results

• Good agreement was found between modeled and observed ET using the most accurate meteorological input dataset, with Root Mean Square Errors (RMSEs) ranging from 1.1 to 1.3 mm/day for ERA5-Land.
• The deforestation analysis for sites in Africa, America, and Asia revealed that the models consistently demonstrated the impact of deforestation on ET, although performance varied due to different deforestation patterns.
• Long-term results showed different model responses to forest removal, highlighting individual model uncertainties and underscoring the necessity of multi-model approaches for more accurate information.
• Current high-resolution remote sensing models can effectively monitor ET in tropical forests on a global scale, particularly for assessing deforestation impacts in data-scarce regions.

Contributions

• Provides a comprehensive evaluation of the performance of four widely used remote sensing-based ET models in complex tropical forest ecosystems.
• Quantifies the agreement between modeled and observed ET, demonstrating the effectiveness of these models for global monitoring.
• Assesses the uncertainty in model outputs driven by different meteorological input forcings.
• Offers a spatial–temporal analysis of the impact of deforestation on ET patterns across multiple continents.
• Highlights the utility of high-resolution remote sensing models for monitoring ET and deforestation impacts in data-scarce tropical regions.
• Emphasizes the importance of multi-model approaches to address uncertainties in long-term ET monitoring.

Funding

Not specified in the provided text.

Citation

@article{Laipelt2025Assessing,
  author = {Laipelt, Leonardo and Fleischmann, Ayan Santos and Ruhoff, Anderson},
  title = {Assessing the Performance of Multiple Satellite-Based Evapotranspiration Models over Tropical Forests},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs18010030},
  url = {https://doi.org/10.3390/rs18010030}
}