Chlorophyll-a Concentration Retrieval in Inland Water Based on Ensemble Learning
Using satellite data to monitor inland or water quality status is of great significance for ecological decision-making.The concentration of Chlorophyll-a(Chla)in Nansi lake,Shandong Province is retrieved by combining two ensemble learning algorithms,based on Sentinel-2 satellite data with high spatiotemporal resolution.The results show that Sentinel-2 data corrected for remote sensing reflectance are more suitable for water quality inversion.The XGBoost model performs optimally on the 5-fold cross-validation inversion results(R2=0.732 5,RMSE=9.168 1 μg/L),making the inversion results more realistic.Therefore,using this model to invert the Chla concentration in the Nansi lake can provide a better understanding of its spatiotemporal variability,and the conclusions of this paper can provide some reference for similar studies in other regions.
国家科技期刊平台
NSTL
万方数据
维普
