Assessment of vegetation trends in drylands from time series of earth observation data

Rasmus Fensholt, Stephanie Horion, Torbern Tagesson, Andrea Ehammer, Kenneth Grogan, Feng Tian, Silvia Huber, Jan Verbesselt, Stephen D. Prince, Compton J. Tucker, Kjeld Rasmussen

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

803 Downloads (Pure)

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.

Original languageEnglish
Title of host publicationRemote Sensing and Digital Image Processing
PublisherSpringer
Pages159-182
Number of pages24
DOIs
Publication statusPublished - 2015 Jan 1
Externally publishedYes

Publication series

NameRemote Sensing and Digital Image Processing
Volume22
ISSN (Print)1567-3200
ISSN (Electronic)2215-1842

Subject classification (UKÄ)

  • Physical Geography

Fingerprint

Dive into the research topics of 'Assessment of vegetation trends in drylands from time series of earth observation data'. Together they form a unique fingerprint.

Cite this