West Afria USGS land use land cover circa 1975, 2000, and 2013
In order to map and monitor changes in West Africa's land resources, we defined 26 general LULC classes. We selected fairly broad classes of LULC that could be readily identified on Landsat satellite imagery. A manual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The manual method lends itself well for several reasons. First, it can accommodate working with images from different satellite systems and formats. Second, it allows expert interpreters to integrate local knowledge with the many dimensions of information contained in images. Third, photo-interpreters can work around problems of seasonal differences from image to image, as well as differences in illumination and atmospheric effects. Furthermore, the human interpreter can effectively distinguish real LULC changes from many of the ephemeral factors such as annual grass fires. The interpretation was verified where possible using high resolution commercial satellite imagery. We also reviewed thousands of aerial photographs acquired by the project in six countries between 2000 and 2006. USGS EROS scientists developed a special tool called the Rapid Land Cover Mapper (RLCM). It is a vector-raster hybrid approach that lends itself to time-series LULC mapping. Conceptually, it is based on the traditional dot grid method for calculating areas that has long been employed by foresters and other users of imagery. The tool first generates a digital dot grid for a given study area. Then it overlays that dot grid on an image within ESRI's ArcMap GIS software. Using standard photo-interpretation skills, the analyst identifies the discrete LULC class for each dot, and labels each point according to the appropriate class. The RLCM tool facilitates both the selection and attribution of dots within a common LULC class. It also facilitates the management of multiple time period classifications for the study area. Once the dot grid matrix is completely classified for a given time period, a raster LULC map can be generated. The same process can be applied to different time periods and the resulting maps can be compared to assess change over time. For most countries, the country teams used 2-km spacing, which produces a 2-km resolution raster map. The analyst first completes the point attribution for each Landsat image covering the country, usually starting with the most recent period (e.g., 2010). The attributed points (color-coded by LULC class) are then superimposed on co-registered images from an earlier period (e.g., Landsat Thematic Mapper from 1985). Each point is re-evaluated to determine if its attribution should remain the same (no LULC change) or be reclassified due to a change in land use or land cover. The completed set of points represents a dense, systematic sample of LULC classes for a second period. The approach can be repeated a third time using Landsat Multispectral Scanner imagery from 1972. Each point can be considered the center of a pixel. The final step is to convert the grid of points to a grid of pixels. Each pixel is color-coded to produce the final product -- a raster map showing the distribution and patterns of LULC classes for the country. Using completed LULC raster maps from two or three periods, one can then produce change maps and statistics that characterize the trends in LULC for each country, and begin to construct models of LULC change for future scenarios. The project provided AGRHYMET and the 17 participating countries with a comprehensive satellite data archive of West Africa from the 1960s to 2013. Most of the countries have completed their national LULC maps for the 1975, 2000 and 2010 periods. Final editing and validation has been completed for all countries except Mali and Chad (in progress for the 1975 maps). Thousands of recent aerial photographs and high resolution satellite images were used to guide the image interpretation and mapping process, and verify results. Initial LULC maps were produced by national teams from each country. To date, we have conducted an independent, detailed review of every map classification, drawing upon many years of field experience mapping LULC in the Sahel and with reference to high resolution imagery. In concurrence with the individual country teams, we have edited and revised the initial LULC maps to produce, what we believe, is a map of very high accuracy and consistency both within countries and across national borders. We are in the process of conducting a more quantitative evaluation of the LULC mapping accuracy by comparing the mapped classes to an independent classification using randomly sampled high resolution imagery.The West Africa Land Use and Land Cover Trends Project represents an effort to document and quantify the impacts, detailed in both time and space, of the environmental and land resource trends that are sweeping across West Africa. The project was carried out through the AGRHYMET Regional Center in Niamey, Niger, with partners from 17 participating countries, the Sahel Institute (INSAH), the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS), and with major support from the U.S. Agency for International Development (USAID) West Africa Regional Program. USGS EROS provided AGRHYMET and participating countries satellite image coverage (from the Corona and Landsat satellite systems) of most of West Africa at four periods in time: the 1970s, 2000s and 2010s. The project trained environmental scientists from 17 West African countries in the analysis of this rich image archive, enabling them to map and quantify land use and land cover (LULC) changes that have occurred across the region. The results provide a much better understanding of the LULC patterns and trends in each participating country. The overarching goal of the West Africa Land Use and Land Cover Trends Project is to promote the awareness of the trends and use of spatial information about natural resource trends among national and regional decision-makers. This heightened level of awareness will help them formulate sound and sustainable policy responses, leading to better natural resource management, conservation, food security, and human well being. The results of this project will be shared with West Africa's political leaders, environmental decision-makers, and the broader scientific community in countries throughout the region. For a complete description of project visit http://eros.usgs.gov/westafrica
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