Assessing drivers of vegetation changes in drylands from time series of earth observation data

R. Fensholt, S. Horion, T. Tagesson, A. Ehammer, K. Grogan, F. Tian, S. Huber, J. Verbesselt, S.D. Prince, C.J. Tucker, K. Rasmussen

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

15 Citations (Scopus)

Abstract

This chapter summarizes methods of inferring information about drivers of global dryland vegetation changes observed from remote sensing time series data covering from the 1980s until present time. Earth observation (EO) based time series of vegetation metrics, sea surface temperature (SST) (both from the AVHRR (Advanced Very High Resolution Radiometer) series of instruments) and precipitation data (blended satellite/rain gauge) are used for determining the mechanisms of observed changes. EO-based methods to better distinguish between climate and human induced (land use) vegetation changes are reviewed. The techniques presented include trend analysis based on the Rain-Use Efficiency (RUE) and the Residual Trend Analysis (RESTREND) and the methodological challenges related to the use of these. Finally, teleconnections between global sea surface temperature (SST) anomalies and dryland vegetation productivity are illustrated and the associated predictive capabilities are discussed.
Original languageEnglish
Title of host publicationRemote Sensing Time Series : Revealing Land Surface Dynamics
EditorsC. Kuenzer, S. Dech, W. Wagner
Pages183-202
Number of pages458
DOIs
Publication statusPublished - 2015

Publication series

NameRemote sensing and digital image processing
PublisherSpringer International Publishing
Number22

Fingerprint

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

Cite this