Vegetation Change in North Africa through the analysis of satellite data, Professor Stephen Young Department of Geography, Salem State College IGC , Tunis, Tunisia – August 13, 2008

Vegetation Change in North Africa OUTLINE Why this research? Overview of Data Set & Methodology used. Overview of where land cover change is occurring. Overview of persistent vegetation change. Overview of the Driving Forces behind the changes.

Vegetation Change in North Africa Why this research?

Global Vegetation Change From 1982/83 to 1998/99

Why this research? Have already mapped vegetation change at the global scale and now focusing on the regional scale. Have researched Australia, East Asia, South Asia, and Southwest Asia – now looking at North Africa. Looking for strong temporal signals of PERSISTENT vegetation change. Trying to understand those signals in context with global environmental change.

Why this research? In particular Colleagues at this conference may be able to help me understand the vegetation changes which are occurring in North Africa.

Data Used GIMMS AVHRR land cover data NOAA / NASA AVHRR data – 8 km resolution Coarse resolution picks up broad change Normalized Difference Vegetation Index (NDVI) (NIR - red) / (NIR + red) High correlation with photosynthesis

Data Pre-Processing GIMMS AVHRR data Base data: NDVI 15-day MVC Re-composited: Monthly Max Composites, January 1982 – December 2003 Re-composited: Annual Average Composites Re-composited endpoints ( ) ÷ 2 = 1982/83 ( ) ÷ 2 = 2002/03

Global Scale NDVI GIMMS data Annual Average 1987

Desert Pixels & All Global Land Pixels

Data Used SPOT VEGETATION data (1km) SPOT IMAGE – 1 km resolution Finer resolution than GIMMS Normalized Difference Vegetation Index (NDVI) (NIR - red) / (NIR + red) High correlation with photosynthesis

Data Pre-Processing SPOT VEGETATION data Base data: NDVI 10-day MVC Re-composited: Monthly Max Composites, April 1998 – Dec 2006 Re-composited: Annual Average Composites 1998 used Jan, Feb, March of 1999 Re-composited endpoints ( ) ÷ 2 = 1998/99 ( ) ÷ 2 = 2005/06

SPOT VEGETATION NDVI Annual Average 2001

SPOT VEGETATION

Methodology Pairwise Comparison ( Univariate Differencing) GIMMS: 2002/03 minus 1982/83 = change SPOT: 2005/06 minus 1998/99 = change Percent Change (2002/03 minus 1982/83) / 1982/83 = Percent Change (2005/06 minus 1998/99) / 1998/99 = Percent Change Profiling Graphing change through the period

Results

All Africa Change GIMMS: 1982 to 2003

Table – All Africa Change Classification (% Change) # of Pixels % of Land Pixels Major Decrease (decrease > 20%) % Decrease (decrease 10 to 20%) % Minor Decrease (decrease 5 to 10%) % Little Change (between -5 and +5%) % Minor Increase (increase 5 to 10%) % Increase (increase 10 to 20%) % Major Increase (increase > 15%) % All Land Pixels %

North Africa Change GIMMS, 1982 to 2003

Table – North Africa Change Classification (% Change)# of Pixel% of Land Pixels Major Decrease (decrease > 20%) % Decrease (decrease 10 to 20%) % Minor Decrease (decrease 5 to 10%) % Little Change (between -5 and +5%) % Minor Increase (increase 5 to 15%) % Increase (increase 10 to 20%) % Major Increase (increase > 15%) % All Land Pixels %

Profiles of Change from 1982 to 2003

Vegetation Change in North Africa GIMMS Data Change is highly variable year to year Few Persistent Changes

All Africa Change SPOT: 1998/99 to 2005/06

North Africa – Areas of Decline

North Africa – Same Areas of Decline GIMMS Data, 1982/3 – 2002/3

Mesopotamian Wetlands, Iraq Areas of Decline GIMMS Data

India South Interior Karnataka Annual Integrated NDVI

India South Interior Karnataka Annual Integrated NDVI Annual Rainfall

North Africa – Areas of Increase 1 – West Nile Delta, 2 – North Central Algeria, 3 – Atlas Mountains, 4 – South Morocco

GIMMS Data – Western Nile Delta

Arc of Irrigation Temporal Profiles

3-year Running Average

Conclusions Unlike other parts of the world, patterns of declining photosynthesis (NDVI) in North Africa are highly variable – with few areas of persistent change. Climate must be the major driver of change for most of the region.

Conclusions Areas in Morocco indicated in the literature as suffering from desertification – also have patterns of great variability. The influence of human activity is hidden by strong climate variability.

Conclusions There are some regions in North Africa which do show signs of persistent increase. Like other regions of the world, the main driver of persistent increases in photosynthesis (NDVI) is agriculture and in particular related water resources. Future research will focus on analysing precipitation data for North Africa with NDVI data..

Thank You