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SWOT Level 2 Lake Single-Pass Product: The L2_HR_LakeSP Data Preliminary Analysis for Water Level Monitoring.
- Source :
- Remote Sensing; Apr2024, Vol. 16 Issue 7, p1244, 12p
- Publication Year :
- 2024
-
Abstract
- The Surface Water and Ocean Topography (SWOT) mission, launched in December 2022, aims to address the crucial environmental goal of water monitoring to support preparedness for extreme events and facilitate adaptation to climate change on global and local scales. This mission will provide a comprehensive inventory of worldwide water resources, lakes, reservoir storage, and river dynamics. In this work, we carried out a preliminary assessment of SWOT's Lake product Level 2 version 1.1, also known as "L2_HR_LakeSP". The analysis was performed across six diverse lakes on three continents, revealing an average median bias of 0.08 m with respect to the considered reference, after suitable outlier removal. An overall precision of 0.22 m was found, combined with an average correlation of 68% between SWOT and reference time series. Moreover, the accuracy varied in the considered six lakes, since biases up to some decimeters were found for some of them; they could be due to residual inconsistencies between the vertical reference frame of SWOT and that of the considered reference. In summary, the first analysis of the "L2_HR_LakeSP" product, Version 1.1, demonstrated the promising potential of SWOT for monitoring seasonal variations in water levels. Nevertheless, notable anomalies were found in the water masks, particularly in higher latitudes, suggesting potential difficulties in accurately delineating water bodies in those regions. Additionally, a discernible reduction in accuracy was observed towards the end of the monitoring period. These preliminary findings indicate some issues that should be addressed in future investigations about the quality and potential of SWOT's lake products for advancing our understanding of global water dynamics. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 16
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 176594882
- Full Text :
- https://doi.org/10.3390/rs16071244