Concerns about the temporal matching windows in satellite-ground synchronization for lacustrine environment mapping

Area of Science:

• Environmental Science
• Remote Sensing
• Hydrology

Background:

• Lacustrine environments are crucial for global ecosystems and water resources.
• Remote sensing data over four decades are used to monitor lake changes.
• Existing lake monitoring models use time windows of 0 to ±7 days, with potential accuracy issues.

Purpose of the Study:

• To investigate the impact of varying time intervals on long-term lake environment mapping.
• To assess how different time windows affect total suspended sediment (TSS) estimation models.
• To evaluate the reliability of existing time-series lacustrine products.

Main Methods:

• Analysis of publicly available field data and high-temporal-resolution sensor observations.
• Development of TSS estimation models using a 0 to ±7-day synchronous dataset.
• Evaluation of sequential variations in China's inland lakes across 0, ±3, and ±7-day time windows (2003-2024).

Main Results:

• Time intervals significantly influence dataset distribution, model accuracy, and spatiotemporal patterns.
• Quantitative deviations in time-series products were substantial, exceeding qualitative differences.
• Pixel-based spatial distribution was more sensitive to time window variations than trend changes.

Conclusions:

• Narrow time windows improve accuracy but face data availability challenges.
• Wide time windows can propagate errors, while dynamic windows offer a practical solution.
• The ±3-day time window is recommended for TSS estimation in inland lakes during stable periods.