An Automatic System for Reconstructing High-Quality Seasonal Landsat Time-Series

Abstract

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).

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.