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    Author(s): Xiaolin Zhu; Eileen H. Helmer; Jin Chen; Desheng Liu
    Date: 2018
    Source: Book
    Publication Series: Book Chapter
    Station: International Institute of Tropical Forestry
    PDF: Download Publication  (727.0 KB)

    Description

    Seasonal time series data from satellites are highly desired by researchers from different fields to study our Earth system. Seasonal time series data contain the temporal aspects of natural phenomena on the land surface, which are extremely helpful for discriminating different land cover types (Zhu and Liu, 2014), monitoring vegetation dynamics (Shen et al., 2011), estimating crop yields (Johnson et al., 2016), assessing environmental threats (Garrity et al., 2013), exploring human-nature interactions (Zhu and Woodcock, 2014a), and revealing ecology-climate feedbacks (Piao et al., 2015).

    Publication Notes

    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Zhu, Xiaolin; Helmer, Eileen H.; Chen, Jin; Liu, Desheng. 2018. An Automatic System for Reconstructing High-Quality Seasonal Landsat Time-Series. In: Qihao Weng, Ed. Remote Sensing: Time Series Image Processing. Taylor and Francis Series in Imaging Science. CRC Press, Boca Raton: 25-42. Chapter 2.

    Keywords

    seasonal variation, time series, vegetation dynamics, remote sensing, landsat.

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