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Land Surface Phenology in a West African Savanna: Impact of Land Use, Land Cover and Fire

  • Ursula Gessner
  • Kim Knauer
  • Claudia Kuenzer
  • Stefan Dech
Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 22)

Abstract

Phenological change and variation have become increasingly relevant topics in global change science due to recognition of their importance for ecosystem functioning and biogeophysical processes. Remote sensing time series offer great potential for assessing phenological dynamics at landscape, regional and global scales. Even though a number of studies have investigated phenology, mostly with a focus on climatic variability, we do not yet have a detailed understanding of phenological cycles and respective biogeographical patterns. This is particularly true for biomes like the tropical savannas, which cover approximately one eighth of the global land surface. Savannas are often characterized by high human population density and growth, one example being the West African Sudanian Savanna. The phenological characteristics in these regions can be assumed to be particularly influenced by agricultural land use and fires, in addition to climatic variability. This study analyses the spatio-temporal patterns of land surface phenology in a Sudanian Savanna landscape of southern Burkina Faso based on time series of the Moderate Resolution Spectroradiometer (MODIS), and on multi-temporal Landsat data. The analyses focus on influences of fire, land use, and vegetation structure on phenological patterns, and disclose the effects of long-term fire frequency, as well as the short-term effects of burning on the vegetation dynamics observed in the following growing season. Possibilities of further improvements for remote sensing based analyses of land surface phenology are seen in using earth observation datasets of increased spatial and temporal resolution as well as in linking phenological metrics from remote sensing with actual biological events observed on the ground.

Keywords

Normalize Difference Vegetation Index Land Cover Type Fire Frequency Fire Season Woody Cover 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This study was funded by BMBF (German Federal Ministry of Education and Research) in the context of the project WASCAL (West African Science Service Center on Climate Change and Adapted Land Use) under FKZ 01LG1202D. We appreciate that NASA, the U.S. Geological Survey, and LP DAAC provide MODIS and Landsat data free of charge. We would also like to thank Lars Eklundh and Per Jönsson for the development and provision of TIMESAT and the anonymous reviewers for their valuable comments.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ursula Gessner
    • 1
  • Kim Knauer
    • 1
    • 2
  • Claudia Kuenzer
    • 1
  • Stefan Dech
    • 3
    • 4
  1. 1.German Remote Sensing Data Center, DFD, Earth Observation Center, EOCGerman Aerospace Center, DLROberpfaffenhofenGermany
  2. 2.Remote Sensing, Institute of Geology and GeographyUniversity of WuerzburgWuerzburgGermany
  3. 3.German Remote Sensing Data Center, DFDGerman Aerospace Center, DLRWesslingGermany
  4. 4.Institute for Geography and GeologyUniversity of WuerzburgWuerzburgGermany

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