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

Fensholt, Rasmus ; Horion, Stephanie ; Tagesson, Torbern LU ; Ehammer, Andrea ; Grogan, Kenneth ; Tian, Feng LU ; Huber, Silvia ; Verbesselt, Jan ; Prince, Stephen D. and Tucker, Compton J. , et al. (2015) In Remote Sensing and Digital Image Processing 22. p.183-202
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... (More)

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.

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publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Remote Sensing and Digital Image Processing
series title
Remote Sensing and Digital Image Processing
volume
22
pages
20 pages
publisher
Springer
external identifiers
  • scopus:84980010201
ISSN
2215-1842
1567-3200
DOI
10.1007/978-3-319-15967-6_9
language
English
LU publication?
no
id
8b75103c-a1b3-4509-acc2-35c16e176ee8
date added to LUP
2018-06-08 13:53:08
date last changed
2024-06-11 16:23:27
@inbook{8b75103c-a1b3-4509-acc2-35c16e176ee8,
  abstract     = {{<p>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.</p>}},
  author       = {{Fensholt, Rasmus and Horion, Stephanie and Tagesson, Torbern and Ehammer, Andrea and Grogan, Kenneth and Tian, Feng and Huber, Silvia and Verbesselt, Jan and Prince, Stephen D. and Tucker, Compton J. and Rasmussen, Kjeld}},
  booktitle    = {{Remote Sensing and Digital Image Processing}},
  issn         = {{2215-1842}},
  language     = {{eng}},
  month        = {{01}},
  pages        = {{183--202}},
  publisher    = {{Springer}},
  series       = {{Remote Sensing and Digital Image Processing}},
  title        = {{Assessing drivers of vegetation changes in drylands from time series of earth observation data}},
  url          = {{https://lup.lub.lu.se/search/files/45734289/Fensholt_et_al_2015_book_chapters_EARSel.pdf}},
  doi          = {{10.1007/978-3-319-15967-6_9}},
  volume       = {{22}},
  year         = {{2015}},
}