关键词: MODIS;陆面温度;时间序列重构;农田区域

Abstract:

Remote sensing data can be used to continuousely supervise the globle resources and environment by large area, and obtain more precise research results. NASAs Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST) data is an ideal and common data source due to its optimal temporal and spatial resolution. Meanwhile, the LST value is generally missing or abnormal for the impact from mixed pixels and cloud noises. To counter this phenomenon, taking Henan Province as studying eara and MODIS LST data as research object, the MODIS LST Time Series LST datum were reconstructed, which were the daily products of Henan Province in 2011 by harmonic analysis of time series method. The result indicated that the reconstructed data could remedy over 70% missing images, and the RMSE of more than 60% images were controlled within 3℃. Thus, a better reconstruction result was obtained. In addition, there was a great correlation between the reconstructed LST time series data and the actual meteorological data. And the correlation coefficient was about 0.8, which indicated that the reconstructed LST time series data could reflect the trend of temperature variation.

Key words: MODIS, LST, reconstruction of time\, series data, farmland area