AAG 2010 Washington DC Assessing Savanna Ecosystem Changes with Remote Sensing in East Africa Jiaguo Qi 1,Chuan Qin 1, Gopal Alagarswamy 1, Joseph Ogutu.

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Presentation transcript:

AAG 2010 Washington DC 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 1. Michigan State University; 2. International Livestock Research Institute, Nairobi, Kenya; 3. University of Dar Es Salaam

AAG 2010 Washington DC RATIONALE Savannah system in E.A. is sensitive to disturbances – Climate change Drought and flood Pattern shifting – Human Change in grazing intensity, fires, conversion

AAG 2010 Washington DC 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

AAG 2010 Washington DC DATA Long term record ( ) 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)

AAG 2010 Washington DC 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

AAG 2010 Washington DC RESULTS Large Integral - Productivity

AAG 2010 Washington DC “Large Integral” Change ( )

AAG 2010 Washington DC “Large Integral” Change ( ) Finer resolution analyses: 1.Northern site in Kenya 2.Tarangire Park and surroundings in Tanzania 1 2

AAG 2010 Washington DC Northern Kenya Site 1

AAG 2010 Washington DC Northern Kenya Site Land Cover type –Grassland/Shrubland Phenology : Bi-modal season –1 st season Start: March – April End: June – July –2 nd season Start: October-November End: January - February

AAG 2010 Washington DC Northern Kenya Site

AAG 2010 Washington DC Tarangire Park in Tanzania Tarangire Park Outside the park

AAG 2010 Washington DC Tarangire Park in Tanzania Land Cover type –Wooded Grassland Phenology : –Single-season Start: November-December End: May - June

AAG 2010 Washington DC Tarangire Park in Tanzania

AAG 2010 Washington DC Tarangire Park in Tanzania

AAG 2010 Washington DC 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

AAG 2010 Washington DC 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

AAG 2010 Washington DC Questions?