The livestock database is in ArcView (shape) format. It is provided at diptank (community communiy level. The livestock included are cattle, goats, donkeys, horses and mules. Information on ecological zones (1-highveld, 2-middleveld, 3-lowveld, 4-Lubombo), and land tenure (1-communal land, 2-private land, 3-government farms) is also provided.

The Zimbabwe Administrative Boundaries digital map dataset was spearheaded by the Department of Surveyor General.

This is the database in Malawi, done by the Department of Land Resources Conseravation.

A map of Zambia showing National and District bounderies and locations of Townships.

Managed areas, such as national parks, forests, reserves, etc.

A map of the 2nd-level administrative boundaries (provinces) of Zimbabwe

A map of the national boundary of Zimbabwe

The yield forecast is realized at (sub-) national level up to the departmental level (or 3rd administrative boundary level e.g. RDP). The yield calculation is based on a yield model obtained from a statistical analysis (stepwise regression) which relates yield to explanatory agrometeorological variables. There are three kinds of explanatory variables. (i) The phenological variables. They are obtained by using the FAO AgroMetShell, a model based on the water balance which gives information on phenological stages of the crop during the growing season. (ii) The meteorological variables which consist of simple and cumulated actual rainfall. (iii) The remote sensed variables which are extracted from NOAA GAC images using WINDISP, an easy FAO image processing software. The models are calibrated on a long term average (for the case of Malawi this was 24 years from 1984 to 2007) and validated by leave-one-out cross validation. The yield forecast at departmental level (RDP) is compared with the average yield for each department on the long term average (in the case of Malawi from 1984 to 2007). The yield forecast map shows those relative yields. The yield forecast at national level which is the required final product, is obtained by aggregating the yield forecast at departmental level. It is indicated on the yield forecast map. The forecasted production is compared with production of the official statistics. Note that the method might slightly differ from one country to another, based upon the local availbility of data and requirements. The GMFS crop yield forecasts are generated once during the growing season. This product is covering Malawi countrywide.

This database shows the land use pattern for Swaziland. Over 70% of the land use used for grazing with large scale cultivation found predominantly in the Lowveld where sugarcane is grown.

This dataset presents the four administratives zones of Swaziland(Hhohho, Manzini, Lubombo and Shiselweni) and the 55 constituences (Tinkhundla).

The database shows land tenure system in the country. The three land tenure systems are Swazi Nation Land proper (SNL), Swazi Nation Land that was purchased from title deed land and Title Deed land )TDL). The database also gives the controling authority for the land parcels. Swazi Nation land is predominantly controled by cheifs.

A thematic map illustrating the national diversity of soil types covering the highest percentage of each mapping unit surveyed at a scale of 1:1 000 000.

A map of the 2nd-level administrative boundaries (provinces) of South Africa for 2006.