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| Created: | Dec 10, 2025 at 8:21 a.m. (UTC) | |
| Last updated: | Dec 10, 2025 at 9:02 a.m. (UTC) | |
| Citation: | See how to cite this resource | |
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| Sharing Status: | Public |
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Abstract
National and international regulations enforce monitoring programmes of water quality to guide management actions of inland water ecosystems. Our study evaluates the effect of spectral and spatial resolutions on the estimation of chlorophyll-a concentrations in mountain lakes, and derives implications for addressing the adjacency effect, which is critical and understudied in small water bodies. Five lakes in Sierra Nevada (Spain) were repeatedly sampled during 2020, 2021 and 2023, and a total of 100 chlorophyll-a samples with suitable coincident satellite imagery were analyzed. Laboratory-obtained chlorophyll-a concentrations were modeled comparing up to 86 spectral indices and bands as predictors from three satellites: Sentinel-2 (12 bands, 20 m/pixel), Planet (8 bands, 3 m/pixel) and WorldView-3 (11 bands, 1.24 m/pixel). Our results showed that multivariate models for estimating chlorophyll-a using spectral indices did not perform significantly better than using bands alone. The best models always had multiple predictors and included green and near-infrared bands. Models based on Sentinel-2 and Planet (Radj² > 0.45) outperformed those of WorldView-3 (Radj² ~ 0.37), confirming that the latter performed worst despite higher spatial resolution. Regarding distance to shoreline, the Planet model showed the most consistent performance, with stable Radj² values and low RMSE even at 3 m from shore with a high level of accuracy (Radj² ~ 0.3; RMSE ~ 1.15 μg L⁻¹). Data and models are released to facilitate near-real-time monitoring of these vulnerable ecosystems, where field sampling is extremely challenging.
Subject Keywords
Coverage
Spatial
Temporal
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Content
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
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| Universidad de Granada | EVEREST project (PID2023-151939OB-I00); Proyectos de investigación aplicada del plan propio de investigacion y transferencia de la universidad de granada 2023 | |
| National Parks Autonomous Agency | NevadEO project (C‐EXP‐074‐UGR23); Spanish National Park Autonomous Agency action line | |
| National Parks Autonomous Agency | LACEN (OAPN 2403-S/2017) | |
| Ministry of Science spain through the life watch eric action line | LifeWatch-2019-10-UGR-01 | |
| Next Generation EU | BIOD22_001 | |
| Spanish Ministry of Universities | FPU19/04878 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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