Eco-climatic zones were produced taking into account land-surface and atmospheric characteristics (the photosynthetic activity,
the temperature of the earth?s surface, the atmospheric drying power, the rainfall, the potential evapotranspiration, the
length of growing period for plants, the surface elevation). Most of these features could be accurately predicted using satellite
data; some others needed a combination of remotely sensed and ground-based data. Remotely sensed data were acquired by NOAA-AVHRR
sensor and by Meteosat satellite. The AVHRR satellite data were available in dekadal images for a 13 year series from 1982-1994.
Meteosat imagery runs from 1988 to 1997.
The information layer was produced for FAO in January 1999 by Environmental Research Group Oxford (ERGO Ltd) in collaboration
with the Trypanosomosis and Land Use in Africa (TALA) research group at the Department of Zoology, University of Oxford.
For the definition of eco-climatic zone, the following satellite-derived measures of land-surface or atmospheric characteristics
? Normalised Difference Vegetation Index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) commonly used as
an indicator of vegetation cover (data from the Pathfinder Program, initially supplied by the NASA Global Inventory Monitoring
and Modelling Systems (GIMMS) group);
? A measure of ground surface temperature, derived using the Price split window technique, from two of the thermal channels
(Channel 4 and 5) of the same instrument that produces NDVI data (Price, 1984);
? A measure of middle infrared reflectance (allied to temperature but less susceptible to atmospheric interference) derived
from Channel 3 of the AVHRR data;
? A measure of Vapour Pressure Deficit also derived from the AVHRR channels 4 and 5 and ancillary processing;
? A measure of surface rainfall, the Cold Cloud Duration (CCD), derived from the METEOSAT satellite (from FAO ARTEMIS).
All the AVHRR satellite data were available in dekadal images for a 13 year series from 1982-1994. The CCD imagery runs
from 1988 to 1997. Each series was subjected to temporal Fourier analysis, re-sampled to 0.05 degree resolution and re-projected
to latitude/longitude (geographic) projection where necessary. Fourier processing extracts, from each multi-temporal data
stream, the characteristics of the annual, biannual and tri-annual components, details of which are given in Rogers, Hay
& Packer (1996). Mean values, and the amplitudes and phases (i.e. timing of the seasonal peaks) of the annual, bi-annual
and tri-annual cycles were recorded, together with the maximum, minimum and ranges (maximum - minimum) of each Fourier description
of the observed signal. The percentage of the total variance attributable to each of the three Fourier components (a measure
of the relative importance of each component) was also calculated for each parameter series.
Other datasets used for the definition of eco-climatic zone were:
? Digital Elevation Model (DEM) data were obtained from the GTOPO30 1km resolution, produced by the Global Land Information
System (GLIS) of the United States Geological Survey, Earth Resources Observation Systems (USGS, EROS) data centre.
The Eco-climatic zones were defined using the ADDAPIX software to provide unsupervised classifications of sub-Saharan Africa
based on elevation and 25 remotely sensed variables: the minimum, maximum, range, mean and Fourier component phase 1 of
each of NDVI, Channel 3, Price temperature, VPD, and CCD. This differs slightly from the ecozonation used in previous works
in the incorporation of the Fourier Phase 1 variable. This essentially quantifies the timing of the seasonal peak in the
annual cycle for each variable, and thus helps to differentiate between areas with similar eco-climatic characteristics
in the northern and southern hemisphere.