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Assessing Savanna Ecosystem Changes with Remote Sensing in East Africa

Assessing Savanna Ecosystem Changes with Remote Sensing in East Africa. Jiaguo Qi 1 ,Chuan Qin 1 , Gopal Alagarswamy 1 , Joseph Ogutu 2 , Mohamed Said 2 , Simon Mugatha 2 , Simon Mwansasu 3 , Pauline Noah 3 , Joseph Maitima 2 , Pius Z. Yanda 3

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Assessing Savanna Ecosystem Changes with Remote Sensing in East Africa

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  1. Assessing Savanna Ecosystem Changes with Remote Sensing in East Africa Jiaguo Qi1,Chuan Qin1 , Gopal Alagarswamy1, Joseph Ogutu2, Mohamed Said2, Simon Mugatha2, Simon Mwansasu3, Pauline Noah3, Joseph Maitima2, Pius Z. Yanda3 1. Michigan State University; 2. International Livestock Research Institute, Nairobi, Kenya; 3. University of Dar Es Salaam

  2. RATIONALE • Savannah system in E.A. is sensitive to disturbances • Climate change • Drought and flood • Pattern shifting • Human • Change in grazing intensity, fires, conversion

  3. OBJECTIVE • To assess phenological changes of savannah system in East Africa using remote sensing • Phenology is an important attribute as it • Reflects ecosystem dynamics • Shifts with changes in climate patterns • Changes with land use • Spatio-temporal pattern of phenology can have significant implications for human and climate systems

  4. DATA • Long term record (1982-2006) of remote sensing data • GIMMS (Global Inventory Modeling and Mapping Studies) NDVI (Normalized Difference Vegetation Index) data (Tucker, 2004 ) • Rainfall Data • CRU data • Land Cover • UMD Global Land Cover Classification (Hansen, 1998)

  5. METHODS • Extract phenological attributes • A linear/simple regression to examine the trends; • Quantify spatial patterns • Analyze the rainfall data to examine the relationship between climate and vegetation change Jönsson and Eklundh, 2002; Jönsson and Eklundh, 2004

  6. RESULTS • Large Integral - Productivity

  7. “Large Integral” Change (1982-2006)

  8. “Large Integral” Change (1982-2006) Finer resolution analyses: • Northern site in Kenya • Tarangire Park and surroundings in Tanzania 1 2

  9. Northern Kenya Site 1

  10. Northern Kenya Site • Land Cover type • Grassland/Shrubland • Phenology : Bi-modal season • 1st season • Start: March – April • End: June – July • 2nd season • Start: October-November • End: January - February 1982 1983 2005 2006

  11. Northern Kenya Site

  12. Tarangire Park in Tanzania Outside the park Tarangire Park

  13. Tarangire Park in Tanzania • Land Cover type • Wooded Grassland • Phenology : • Single-season • Start: November-December • End: May - June 1982 1983 2005 2006

  14. Tarangire Park in Tanzania

  15. Tarangire Park in Tanzania

  16. SUMMARY • Phenological Changes • Some places are bi-modal while others are uni-modal • May be a false alarm - Places of bi-modal seasons may show uni-modal in drought years  Change may not be long term • There is a shift from bi-modal towards unimodal in some places • It appears that climate is a dominant driver in Tanzania study site

  17. CONCLUSIONS • Phenology is an important indicator of ecosystems • Can be characterized with remotely sensed data • Shifts in spatial patterns of phenology are either an indicator of climate change or human land use changes, or combination of the two • There is a need to separate the two, which will be the work in the future

  18. Questions?

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