In contrast to the discrete land use and land cover classes, land productivity is a continuous variable, which represents land cover through vegetation density and vigor. Land productivity can indicate the land’s ability to support and sustain life and is useful for identifying land degradation. A common measure of land productivity is derived from time series of the Normalized Difference Vegetation Index (NDVI), which is a greenness index obtained from satellite-measured reflectances of the land. The index represents the differences in reflectance between green vegetation and bare ground. It senses the presence and vigor of green vegetation using the plant chlorophyll-absorbing red and the non-absorbing near-infrared (NIR) portions of the electromagnetic spectrum. NDVI is calculated as (Tucker, 1979):
NDVI is a numerical measure ranging from 0 (low) to 1 (high). Because the NDVI is strongly related to the absorption of energy for photosynthesis by chlorophyll pigments of green plants, it can be used as a proxy for the amount of green biomass (Huete and others, 2016).
Range of land productivity with the land cover class "savanna"
Different land cover types represented by a mean annual NDVI of around 0.45
On a regional scale, land productivity follows the climatic gradient. With the exception of the moist coastal regions on the Gulf of Guinea, rainfall is a major constraining factor of land productivity in West Africa. Rainfall decreases from south to north — so does land productivity. Climate is not the only driver of land productivity. Soils, topography, land use and management also play a role in modulating land productivity at finer scales. While land productivity is associated with land use and land cover to some extent — e.g., the class “bare soil” has consistently very low land productivity whereas the class “forest” typically has high land productivity — it also cuts across land use and land cover classes and captures within-class variability. Particularly in the land cover class “savanna,” land productivity varies widely from place to place.
Land productivity varies not only in space, but also in time. This variability in land productivity occurs at different time scales, from seasonal to interannual, in response to the variability in rainfall. Moving from the Gulf of Guinea, which receives adequate rainfall for vegetation activity year round, to the north, the difference between dry and wet season becomes increasingly marked. Thus, in the semiarid Sudan and Sahel zones, the vegetation cover appears lush and green during the wet season. In the dry season, the herbaceous cover dries out, whereas some — but not all — of the woody species retain their green leaves. In addition to this seasonal ebb and flow, rainfall and the vigor of the vegetation cover also vary between years. As a rule, the lower the long-term mean annual rainfall, the more variable and unpredictable it is from year to year (see climate section).
The land productivity map of West Africa was produced from 15 years (2001–2015) of 250-m spatial resolution MODIS NDVI data. From each year of data, which comprises 72 observation periods per year, the value of the maximum NDVI was retained. The maxima of the 15 years were then averaged to create a mean maximum NDVI image. This simplistic technique is adequate for eliminating many of the atmospheric effects that influence the satellite-measured reflectances throughout the years and minimizes the impact of the seasonal variability in rainfall. The resulting map provides an overview of the spatial pattern of land productivity in West Africa and a basis for identifying areas of high and low productivity.
Longitudinal cross-section of West Africa showing land productivity gradient
While the regional-scale map (top of the page) emphasizes the north-south land productivity gradient, three smaller subsets zoom in on finer-scale patterns. Subset 1 highlights the stark contrast in land productivity between the built-up area of the city of Kumasi in Ghana and the surrounding forest zone. Subset 2 shows a dune-interdune landscape aligned east-to-west in northern Burkina Faso, in which the lower-lying interdune spaces are occupied by unproductive steppes in contrast to the much more productive open savannas on the sandy soils that cap the stabilized dunes. Subset 3 illustrates the impact of land management on land productivity at three large sylvopastoral reserves in central Senegal (Doli, Mbégué and Siné Saloum), which form higher productivity areas against the surrounding agricultural land that blur where agriculture is encroaching into the reserves.
Landscapes of West Africa: A Window on a Changing World
In contrast to the discrete land use and land cover classes, land productivity is a continuous variable, which represents land cover through vegetation density and vigor. Land productivity can indicate the land’s ability to support and sustain life and is useful for identifying land degradation. A common measure of land productivity is derived from time series of the Normalized Difference Vegetation Index (NDVI), which is a greenness index obtained from satellite-measured reflectances of the land. The index represents the differences in reflectance between green vegetation and bare ground. It senses the presence and vigor of green vegetation using the plant chlorophyll-absorbing red and the non-absorbing near-infrared (NIR) portions of the electromagnetic spectrum. NDVI is calculated as (Tucker, 1979):
NDVI is a numerical measure ranging from 0 (low) to 1 (high). Because the NDVI is strongly related to the absorption of energy for photosynthesis by chlorophyll pigments of green plants, it can be used as a proxy for the amount of green biomass (Huete and others, 2016).
Range of land productivity with the land cover class "savanna"
Different land cover types represented by a mean annual NDVI of around 0.45
On a regional scale, land productivity follows the climatic gradient. With the exception of the moist coastal regions on the Gulf of Guinea, rainfall is a major constraining factor of land productivity in West Africa. Rainfall decreases from south to north — so does land productivity. Climate is not the only driver of land productivity. Soils, topography, land use and management also play a role in modulating land productivity at finer scales. While land productivity is associated with land use and land cover to some extent — e.g., the class “bare soil” has consistently very low land productivity whereas the class “forest” typically has high land productivity — it also cuts across land use and land cover classes and captures within-class variability. Particularly in the land cover class “savanna,” land productivity varies widely from place to place.
Land productivity varies not only in space, but also in time. This variability in land productivity occurs at different time scales, from seasonal to interannual, in response to the variability in rainfall. Moving from the Gulf of Guinea, which receives adequate rainfall for vegetation activity year round, to the north, the difference between dry and wet season becomes increasingly marked. Thus, in the semiarid Sudan and Sahel zones, the vegetation cover appears lush and green during the wet season. In the dry season, the herbaceous cover dries out, whereas some — but not all — of the woody species retain their green leaves. In addition to this seasonal ebb and flow, rainfall and the vigor of the vegetation cover also vary between years. As a rule, the lower the long-term mean annual rainfall, the more variable and unpredictable it is from year to year (see climate section).
The land productivity map of West Africa was produced from 15 years (2001–2015) of 250-m spatial resolution MODIS NDVI data. From each year of data, which comprises 72 observation periods per year, the value of the maximum NDVI was retained. The maxima of the 15 years were then averaged to create a mean maximum NDVI image. This simplistic technique is adequate for eliminating many of the atmospheric effects that influence the satellite-measured reflectances throughout the years and minimizes the impact of the seasonal variability in rainfall. The resulting map provides an overview of the spatial pattern of land productivity in West Africa and a basis for identifying areas of high and low productivity.
Longitudinal cross-section of West Africa showing land productivity gradient
While the regional-scale map (top of the page) emphasizes the north-south land productivity gradient, three smaller subsets zoom in on finer-scale patterns. Subset 1 highlights the stark contrast in land productivity between the built-up area of the city of Kumasi in Ghana and the surrounding forest zone. Subset 2 shows a dune-interdune landscape aligned east-to-west in northern Burkina Faso, in which the lower-lying interdune spaces are occupied by unproductive steppes in contrast to the much more productive open savannas on the sandy soils that cap the stabilized dunes. Subset 3 illustrates the impact of land management on land productivity at three large sylvopastoral reserves in central Senegal (Doli, Mbégué and Siné Saloum), which form higher productivity areas against the surrounding agricultural land that blur where agriculture is encroaching into the reserves.