利用S-G滤波进行MODIS-EVI时间序列数据重构

基金项目: 国家自然科学基金资助项目(50721006)；资源与环境信息系统国家重点实验室自主研究课题资助项目

详细信息

Reconstruction of MODIS-EVI Time-Series Data with S-G Filter

¹China Institute of Water Resources and Hydropower Research,20 West Chegongzhuang Road,Beijing 100044,China;²Institute of Geographic Sciences and Natural Resources Research,CAS,A1 Fuxing Road,Beijing 100101,China

Funds: 国家自然科学基金资助项目(50721006)；资源与环境信息系统国家重点实验室自主研究课题资助项目

摘要: 采用S-G滤波方法对MOD13A2-EVI自2001~2007年间数据进行时间序列重构,以达到去云、消除离异值的目的,从而提高数据质量及可信度。对比重构前后数据发现,重构后的EVI数据在空间上更加一致,在时间维度上时序数据年间变化更加稳定。
- S-G滤波 /
- EVI /
- 时序数据 /
- 重构
Abstract: Vegetation index data has been widely used in kinds of research regarding global environmental change.Although EOS provides some kinds of VI data derived from AQUA/MODIS,residual noise still exists for the reason of cloud contamination,atmospheric variability,and some effect.Hence,the VI data is always discontinuity both in space and time,which is the main reason of the following errors.We reconstruct the MOD13A2-EVI time-series data from the year of 2001 to 2007 based on savitzky-golay filter using IDL.The reconstructed EVI data reduces the effect of cloud and some abnormal noises,makes the data more unanimous in space and more steady between years.
- savitzky-golay filter /
- EVI /
- time-series /
- reconstruction