Cluster Computing

, Volume 22, Supplement 1, pp 2357–2370 | Cite as

Low-quality multivariate spatio-temporal serial data preprocessing

  • Tao Yu
  • Le Li
  • Lajiao ChenEmail author
  • Weijing SongEmail author


As the accumulation of spatio-temporal data, the low-quality problems of multivariate spatio-temporal data become clear and mainly present that numerous missing data, high noise of time series and great different spatial scale of spatiotemporal data. Aimed at the low-quality problems of multivariate spatio-temporal series, we propose three methods to process them, firstly, using improved non-local means (NLM) algorithm and nonlinear regression analysis method to achieve incomplete data imputation; secondly, using NLM algorithm to deal with Gaussian white noise in time series; thirdly, using the Gaussian pyramid method to zoom the spatial scale for multivariate spatial data. Besides, we compare with traditional methods using quantitative evaluation indices to measure the performance, including K-nearest and wavelet threshold. The experimental simulations indicate that the interpolating accuracy of the two proposed algorithms are higher than K-nearest neighbor algorithm and the effect of denoising using NLM algorithm is obviously better than wavelet threshold method. The experiment results further indicate that the Gaussian pyramid method effectively achieves spatial scale transformation of multivariate spatial data and keeps the local detail characteristics of spatial data with better visual expression effect.


Spatio-temporal data Low-quality Incomplete data interpolation Gaussian pyramid 


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© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Institute of Network Science and CyberspaceTsinghua UniversityBeijingPeople’s Republic of China
  2. 2.Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingPeople’s Republic of China
  3. 3.Ji’nan City Planning Consultation Service CenterJinanPeople’s Republic of China
  4. 4.College of Computer ScienceChina University of GeosciencesWuhanPeople’s Republic of China

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