Downscaling Sentinel-3 Chlorophyll-a Concentration for Inland Lakes Based on Multivariate Analysis and Gradient Boosting Decision Trees Regression
DownscalingChlorophyll-a(Chl-a)concentration de rived from satellite image is crucial for refined applications such as water quality monitoring. However, the precision of downscaling is usually constrained by various environmental factors. In this paper, we develop a downscaling method for Chl-a concentration to improve precision, especially for inland lakes with different surrounding environment. The method downscales the Sentinel-3 Chl-a concentration from 300 mto30m,basedonthemultivariate analysis (MVA) and the gradient boosting decision tree (GBDT) model. Firstly, we analyzed 21 Chl-a concentration related indices to identify optimal factors for Chl-a concentration variability. Secondly, a GBDT model is constructed to convey the non-linear relationship between the optimal factors and Chl-a concentration at coarse resolution. Finally, fine-resolution Chl-a concentrations were produced by employing the model to refine cofactors for 12 distinct lakes. The results indicated that the proposed MVA-GBDT method effectively inferred the variability of Chl-a concentration with a mean RMSE of 4.505 mg/m3, an improvement of 5% 39%over other methods. Furthermore, for lakes with large water quality heterogeneity, the method led to a cross validation RMSE and a difference in accuracy of 5.371 mg/m3 and 0.866 mg/m3, respectively. In addition, this study examined the significance of the auxiliary factors and found that the NDCI and WST were the two most important factors for MVA-GBDT to detect Chl-a concentration distributions, particularly for NDCI in lakes with highnutrientcontrasts.Thesefindingscontributetothegeneration of fine-scale Chl-a concentrations in lakes and support related applications.
History
School affiliated with
- Department of Geography (Research Outputs)
Publication Title
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingVolume
16Pages/Article Number
7850 - 7865Publisher
IEEEExternal DOI
ISSN
1939-1404eISSN
2151-1535Date Accepted
2024-08-03Date of First Publication
2023-08-03Open Access Status
- Open Access
Will your conference paper be published in proceedings?
- N/A