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Lars Eklundh

Professor

Personal photograph

High resolution mapping of vegetation dynamics from Sentinel-2

Author

  • Lars Eklundh
  • Martin Sjöström
  • Jonas Ardö
  • Per Jönsson

Summary, in English

The aim of this work is to develop and test a method for generation of information on vegetation dynamics from high-spatial resolution data, such as Sentinel-2. In order to accomplish this, Sentinel-2 data were simulated from existing SPOT HRG and HRVIR scenes over Sweden. We used TIMESAT, a well-tested computer package for generating smooth seasonal profiles and generation of seasonality parameters, like start and end, length, amplitude, integrated values, seasonal maximum, derivatives, etc. The processing works on a pixel-by-pixel basis and is resistant to clouds and noise. Data gaps are handled, and quality information can be included to increase the fidelity of the fits. The pilot study demonstrated that TIMESAT was successful in fitting smooth model functions to the data, and generating seasonality parameters for the test area at 10 × 10 m resolution. We conclude that TIMESAT will be useful for generating vegetation dynamics data from high-spatial resolution data such as Sentinel-2. The smooth seasonal profiles will be extremely useful for driving high-resolution biophysical vegetation models, and the seasonality parameters will be excellent for change detection, and for studying trends in vegetation productivity and seasonality.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • MERGE: ModElling the Regional and Global Earth system

Publishing year

2012-12-19

Language

English

Publication/Series

European Space Agency, (Special Publication) ESA SP

Volume

707 SP

Document type

Conference paper

Topic

  • Physical Geography
  • Remote Sensing

Conference name

1st Sentinel-2 Preparatory Symposium

Conference date

2012-04-23 - 2012-04-27

Conference place

Frascati, Italy

Status

Published

ISBN/ISSN/Other

  • ISSN: 0379-6566
  • ISBN: 9789290922711