Spatiotemporal reflectance blending in a wetland environment

Ryo Michishita, Lifan Chen, Jin Chen, Xiaolin Zhu, Bing Xu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)


To understand the mechanism of wetland cover change with both moderate spatial resolution and high temporal frequency, this research evaluates the applicability of a spatiotemporal reflectance blending model in the Poyang Lake area, China, using 9 time-series Landsat-5 Thematic Mapper images and 18 time-series Terra Moderate Resolution Imaging Spectroradiometer images acquired between July 2004 and November 2005. The customized blending model was developed based on the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). Reflectance of the moderate-resolution image pixels on the target dates can be predicted more accurately by the proposed customized model than the original ESTARFM. Water level on the input image acquisition dates strongly affected the accuracy of the blended reflectance. It was found that either of the image sets used as prior or posterior inputs are required when the difference of water level between the prior or posterior date and target date at Poyang Hydrological Station is <2.68 m to achieve blending accuracy with a mean average absolute difference of 4% between the observed and blended reflectance in all spectral bands.
Original languageEnglish
Pages (from-to)364-382
Number of pages19
JournalInternational Journal of Digital Earth
Issue number5
Publication statusPublished - 1 Jan 2015
Externally publishedYes


  • blending model
  • Landsat TM
  • multi-sensor
  • spatial-temporal reflectance
  • time-series

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Earth and Planetary Sciences(all)


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