This chapter summarizes approaches to the detection of dryland vegetation change and methods for observing spatio-temporal trends from space. An overview of suitable long-term Earth Observation (EO) based datasets for assessment of global dryland vegetation trends is provided and a status map of contemporary greening and browning trends for global drylands is presented. The vegetation metrics suitable for per-pixel temporal trend analysis is discussed, including seasonal parameterisation and the appropriate choice of trend indicators. Recent methods designed to overcome assumptions of long-term linearity in time series analysis (Breaks For Additive Season and Trend(BFAST)) are discussed. Finally, the importance of the spatial scale when performing temporal trend analysis is introduced and a method for image downscaling (Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM)) is presented.
CITATION STYLE
Fensholt, R., Horion, S., Tagesson, T., Ehammer, A., Grogan, K., Tian, F., … Rasmussen, K. (2015). Assessment of vegetation trends in drylands from time series of earth observation data. In Remote Sensing and Digital Image Processing (Vol. 22, pp. 159–182). Springer International Publishing. https://doi.org/10.1007/978-3-319-15967-6_8
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