Comparative assessment of Two Source of Landsat TM vegetative fraction coverage for modeling urban latent heat fluxes

摘要: Traditional methods for the extraction of VFC using vegetation indices were found to have large uncertainty due its sensitive surface heterogeneous characteristic. This study presents an improved Spectral Mixture Analysis (SMA) approach Landsat TM data map modeling urban heat fluxes, in case Beijing, China. Two widely used models (Two-Source model (TSEB) and Pixel Component Arranging Comparing Algorithm (PCACA)) adopted evaluation. A comparative analysis between NDVI-derived SMA-derived showed that latter achieved more accurate values complex regions, with better accuracy 1.61% Root mean squared error (RMSE) 1.03% Mean absolute (MAE). Moreover, could be utilized produce a higher precision latent fluxes relative when as input both TSEB PCACA model.