Abstract
Land surface temperature (LST) is one of the key parameters in the atmosphere-land energy and water transfers. An understanding of the spatial and temporal variations of land surface temperature is important to broad research fields, including climate, vegetation, hydrology, etc. In this paper, the cloud contamination of MODIS LST product was analyzed first, and showed that there are numerous data gaps in MODIS 8-day composite LST product, indicating the necessity of data interpolation. Then the Harmonic Analysis of Time-Series (HANTS) algorithm was applied to the LST time-series to rebuild cloud-free images and to distill harmonic components. According to the harmonic characters and reconstruct LST, the spatial and temporal variations of land surface temperature in the Yangtze River Delta were studied.
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