<ul><li>Changes in vegetation and rainfall patterns  </li></ul><ul><li>in sub-Saharan Africa over the last decade  </li></...
Outline of the presentation <ul><ul><li>Outline of Geoland-2 and NARMA WP </li></ul></ul><ul><ul><li>Scope of this study <...
Outline of Geoland2 and NARMA WP <ul><ul><li>GEOLAND2 </li></ul></ul><ul><ul><li>Global Monitoring for Environment and Sec...
Outline of Geoland2 and NARMA WP <ul><ul><li>Environmental indicators of the environmental situation over Africa using Ear...
Scope of this study <ul><ul><li>Identify regions that are subject to temporal changes in land condition </li></ul></ul><ul...
Rainfall data  = 10-day rainfall from NOAA-CPC  FEWSNET (RFE 2.0);    spatial resolution: 8km, period: 2001-2010  10-day c...
A  standardised rainfall / max-NDVI anomalies  were calculated as the deviation from the long-term mean normalised by the ...
Methods: long-term trends A linear least squares regression  was used to examine temporal trends in a) annual rainfall/max...
Long-term rainfall trend (2001 – 2010)
Long-term rainfall trend (2001 – 2010) Sub-Saharan Africa (759 admin. regions) Positive trend (%) Number of polygons % of ...
Standardised Rainfall Anomaly (2001 - 2010)
Long-term trend in max-NDVI (2001 – 2010)
Max-NDVI anomalies (2001 – 2010)
<ul><ul><li>Long-term trends of NDVI and RFE were analyzed together according to the interpretive scheme </li></ul></ul>Co...
NDVI vs. RFE anomaly trends
SUMMARY:  Over the last decade, Central and Western Ethiopia has experienced climatic greening. The resulting vegetation i...
NDVI vs. RFE anomaly trends – Ethiopia  % of the area  % of the area
<ul><li>Rainfall pattern has a strong influence on the vegetation greenness and thus may mask human-induced land degradati...
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Changes_in_vegetation_and_rainfall_patterns_in_subSaharan_Africa_over_the_last_decade.ppt

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  • 16/06/2011
  • 27/07/11
  • 27/07/11
  • 27/07/11
  • To identify locations, intensity and duration of rainfall pattern over the period 2001 - 2010 a standardised rainfall / max-NDVI anomalies were calculated for each year, and for each pixel, as the deviation from the long-term mean normalised by the temporal standard deviation (SD) for the same period 16/06/2011
  • Regions with a statistically significant positive (increasing) rainfall trend over the last decade are located in West Africa, Central African Republic, Central Ethiopia and south-western part of the continent. Negative (decreasing) trends are indentified in several regions of tropical Africa, Nigeria and Madagascar. 16/06/2011
  • Changes_in_vegetation_and_rainfall_patterns_in_subSaharan_Africa_over_the_last_decade.ppt

    1. 1. <ul><li>Changes in vegetation and rainfall patterns </li></ul><ul><li>in sub-Saharan Africa over the last decade </li></ul><ul><li>observed by satellites </li></ul><ul><li>a national and sub-national synthesis </li></ul><ul><li>Hoscilo, A., Balzter, H., Bartholomé, E., Boschetti, M., </li></ul><ul><li>Brivio, P.A. and Brink, A. </li></ul><ul><li>email: ah165@le.ac.uk ; University of Leicester, UK </li></ul>
    2. 2. Outline of the presentation <ul><ul><li>Outline of Geoland-2 and NARMA WP </li></ul></ul><ul><ul><li>Scope of this study </li></ul></ul><ul><ul><li>Earth Observation data </li></ul></ul><ul><ul><li>Long-term trend and anomalies in rainfall and vegetation </li></ul></ul><ul><ul><li>Conceptual model of coupling rainfall and vegetation trends </li></ul></ul><ul><ul><li>Identifying areas sensitive to climate variability and human impacts </li></ul></ul><ul><ul><li>National and sub-national synthesis for Ethiopia </li></ul></ul><ul><ul><li>Conclusion </li></ul></ul>
    3. 3. Outline of Geoland2 and NARMA WP <ul><ul><li>GEOLAND2 </li></ul></ul><ul><ul><li>Global Monitoring for Environment and Security (GMES) </li></ul></ul><ul><ul><li>Contribution to GEOSS </li></ul></ul><ul><ul><li>Developing the land monitoring core service </li></ul></ul><ul><ul><li>http:/www.gmes-geoland.info/ </li></ul></ul>
    4. 4. Outline of Geoland2 and NARMA WP <ul><ul><li>Environmental indicators of the environmental situation over Africa using Earth Observation data </li></ul></ul><ul><ul><li>Verify robustness, reliability and sustainability of the indicators in order to gain user acceptance and feedback from end-users (i.e. DG-AIDCO and African partners) </li></ul></ul><ul><ul><li>Natural Resource Monitoring for Africa (NARMA) </li></ul></ul><ul><ul><li>Work Package </li></ul></ul>
    5. 5. Scope of this study <ul><ul><li>Identify regions that are subject to temporal changes in land condition </li></ul></ul><ul><ul><li>Focus on inter-annual anomalies and long-term trends in vegetation and rainfall </li></ul></ul><ul><ul><li>Identify the areas particularly sensitivity to climate variability or human impacts </li></ul></ul><ul><ul><li>Integrate Earth Observation data into a Country Environmental Profile document, based on which the European Commission services analyse the overall situation of each country of sub-Saharan Arica </li></ul></ul>
    6. 6. Rainfall data = 10-day rainfall from NOAA-CPC FEWSNET (RFE 2.0); spatial resolution: 8km, period: 2001-2010 10-day composite aggregated into annual rainfall (mm/year) Normalised Difference Vegetation Index (NDVI) 10-day NDVI composite derived from SPOT Vegetation GVT4 Africa spatial resolution: 1km, period 2001-2010 Max-NDVI derived for each year Data aggregated for a calendar year (January to December) Analysis performed at pixel level and summarised for administrative regions: administrative divisions level-2 integrated with the level-3 for Sudan and the DR of Congo Earth Observation data
    7. 7. A standardised rainfall / max-NDVI anomalies were calculated as the deviation from the long-term mean normalised by the temporal standard deviation (SD) for the same period. Zn anomaly (i,j) = ( Zn (i,j) – Zmean (2001-2010) (i,j) ) / Zσ (2001-2010) (i,j) Zn – annual rainfall (mm/year) or max-NDVI for the year n (from 2001 to 2010) Zmean – long-term mean annual rainfall/max-NDVI for the period 2001 - 2010 Zσ – long-term standard deviation of annual rainfall / max-NDVI over the period 2001 - 2010 i, j – pixel index Interpretation of rainfall anomalies (RA): dry condition: moderately dry if -1.0 < RA < -1.49 severely dry if -1.5 < RA < -1.99 extremely dry if RA ≤ -2.0 wet condition: moderately wet if 1.0 < RA < 1.49 severely wet if 1.5 < RA < 1.99 extremely wet if RA ≥ 2.0 Methods: standardised anomalies
    8. 8. Methods: long-term trends A linear least squares regression was used to examine temporal trends in a) annual rainfall/max-NDVI and b) standardised rainfall/max-NDVI anomalies A t-test was applied to determine whether the negative or positive slope of the trend line was statistically significant : t-test = m (i,j) / se(m) (i,j) m – estimated slope coefficient se(m) – standard error values for the coefficient m (i, j) – pixels
    9. 9. Long-term rainfall trend (2001 – 2010)
    10. 10. Long-term rainfall trend (2001 – 2010) Sub-Saharan Africa (759 admin. regions) Positive trend (%) Number of polygons % of the total no of polygons 0.1_10 116 15.3 10_20 40 5.3 20_30 49 6.5 30_40 28 3.7 40_50 30 4.0 >50 124 16.3 Sub-Saharan Africa (759 admin. regions) Negative trend (%) Number of polygons % of the total no of polygons 0.1_10 82 10.8 10_20 24 3.2 20_30 17 2.2 30_40 4 0.5 40_50 9 1.2 >50 14 1.8
    11. 11. Standardised Rainfall Anomaly (2001 - 2010)
    12. 12. Long-term trend in max-NDVI (2001 – 2010)
    13. 13. Max-NDVI anomalies (2001 – 2010)
    14. 14. <ul><ul><li>Long-term trends of NDVI and RFE were analyzed together according to the interpretive scheme </li></ul></ul>Conceptual model of NDVI vs. RFE anomaly trends Anomalous greening Anomalous degradation Climatic greening Climatic degradation 0,1 -0,1 -0,1 0,1 NDVI pos. trend RFE pos. trend NDVI neg. trend RFE neg. trend stability stability X = NDVI trend slope Y = RFE trend slope 1 3 2 4
    15. 15. NDVI vs. RFE anomaly trends
    16. 16. SUMMARY: Over the last decade, Central and Western Ethiopia has experienced climatic greening. The resulting vegetation improvement is associated with an increasing long-term trend in rainfall. However, in some locations of North and Eastern Ethiopia, the vegetation condition has deteriorated despite a significant increase in rainfall, resulting in anomalous degradation. This condition has been largely unfavourable for vegetation development and crop production. Overall climatic greening has affected more than 3% (36,400 km 2 ) of Ethiopia, whereas anomalous degradation distressed almost 2% (more than 20,400 km 2 ) of the country. NDVI vs. RFE anomaly trends – Ethiopia
    17. 17. NDVI vs. RFE anomaly trends – Ethiopia % of the area % of the area
    18. 18. <ul><li>Rainfall pattern has a strong influence on the vegetation greenness and thus may mask human-induced land degradation (often affecting smaller areas). </li></ul><ul><li>The proposed approach can be used to: </li></ul><ul><li>- identify locations for closer inspection and possible need for action </li></ul><ul><li>- understand the mechanism leading to the land condition in the region </li></ul><ul><li>compare across regions and provide a national and sub-national synthesis of land condition, which can be easily incorporated in Country Environmental Profile documents. </li></ul>Conclusion
    19. 19. Thank You!

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