ArticleScientific data2024
Satellite-ground synchronous in-situ dataset of water optical parameters and surface temperature for typical lakes in China.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- BOLM high resolution land use and land cover dataset and benchmark results for the rapidly developing City of Dhaka Bangladesh.Scientific reports · 2025Article
- A bio-optical database for the remote sensing of water quality in BRAZil coAstal and inland waters (BRAZA).Scientific data · 2025Article
- Satellite-ground synchronous in-situ dataset of water optical parameters and surface temperature for typical lakes in China.Scientific data · 2024Article
- From compaction to coexistence: A review of chassis engineering for intelligent agricultural machinery in complex paddy field ecosystems.Science progressReview
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Remote sensing technology has the potential to enhance the lake's large-scale and long-term dynamic monitoring capabilities significantly. High-quality in-situ datasets are essential for improving the accuracy and reliability of remote sensing retrieval of lake ecosystems. This dataset provides satellite-ground synchronized in-situ data on water multi-parameters for typical lakes in China spanning the period between 2020 and 2023. It includes quality-checked water optical parameters (remote sensing reflectance (Rrs), chlorophyll-a (Chl-a), total suspended matter (TSM) and Secchi disk depth (SDD)), and water surface temperature (WST) data. It encompasses 586 sampling points across 18 lakes. The dataset exhibits two significant highlights: Firstly, synchronous observations from multiple satellites are coordinated during the data collection effectively supporting the retrieval and validation of water remote sensing products. Secondly, it encompasses diverse data types, collecting synchronous measurements of Rrs and various parameters. This dataset will continuously update, substantially enhancing regional and global lake monitoring capabilities through satellite remote sensing data.
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Registered trials
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