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Assessment of Vegetation Trends in Drylands from Time Series of Earth Observation Data

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Book cover Remote Sensing Time Series

Part of the book series: Remote Sensing and Digital Image Processing ((RDIP,volume 22))

Abstract

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.

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Acknowledgements

This book chapter is written within the frame of the project entitled Earth Observation based Vegetation productivity and Land Degradation Trends in Global Drylands. The project is funded by the Danish Council for Independent Research (DFF) Sapere Aude programme.

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Authors and Affiliations

  1. Section of Geography, Department of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen, Copenhagen K, Denmark

    Rasmus Fensholt, Stephanie Horion, Torbern Tagesson, Andrea Ehammer, Kenneth Grogan, Feng Tian & Kjeld Rasmussen

  2. DHI GRAS, Copenhagen K, Denmark

    Silvia Huber

  3. Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Wageningen, The Netherlands

    Jan Verbesselt

  4. Department of Geographical Sciences, University of Maryland, College Park, MD, USA

    Stephen D. Prince

  5. NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Compton J. Tucker

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  1. Rasmus Fensholt
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Correspondence to Rasmus Fensholt .

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Editors and Affiliations

  1. German Remote Sensing Data Center, DFD, German Aerospace Center, DLR, Wessling, Germany

    Claudia Kuenzer

  2. German Remote Sensing Data Center, DFD, German Aerospace Center, DLR, Wessling, Germany

    Stefan Dech

  3. Department of Geodesy and Geoinformation, Vienna University of Technology, Vienna, Austria

    Wolfgang Wagner

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Fensholt, R. et al. (2015). Assessment of Vegetation Trends in Drylands from Time Series of Earth Observation Data. In: Kuenzer, C., Dech, S., Wagner, W. (eds) Remote Sensing Time Series. Remote Sensing and Digital Image Processing, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-15967-6_8

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