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  • This represents the "départments" administrative divisions of Cameroon. The dataset is originally produced by the Institut national de cartographie (INC) and the descriptions are made on the basis of topographic maps (INC background) at a scale of 1:200 000. This layer represents a global view of the regions and does not correspond to official boundaries. There is no legal validation process for this data. The dataset was edited by FAO-CSI for topology/geometry validation, schema and coding system conformance to SALB-UN specifications. International borders were updated/validated against the official/recognized borders from the United Nations Geospatial Information Section.

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  • This is Gross Value Added for the Agriculture Forestry and Fishing industry which is section A in the International Standard Classification of All Economic Activities (ISIC) revision 4. It “includes the exploitation of vegetal and animal natural resources, comprising the activities of growing of crops, raising and breeding of animals, harvesting of timber and other plants, animals or animal products from a farm or their natural habitats”. (Final ISIC Revision 4, page 65). This section has three divisions, namely; the Crop and animal production, hunting and related service activities, Forestry and logging, and Fishing and aquaculture. **Table content** - Year - Indicator - Item - Value - Flag - UM

  • national crop production **Table content** - time - indicator - crop - value - flag - unit of measure **Value assigned to No-data**:m

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  • 2015 Farming Systems for Sub-Saharan Africa region at the continental level to capture current spatial extent of systems and provide a basis for updated analysis, trends, issues and strategic priorities for each system. In 2000 as part of the Joint FAO-World Bank Farming Systems and Poverty Study (Dixon et al 2001) separate broad-scale farming systems were identified for the six World Bank Development Regions of the world. The current dataset is an update of the 2000 study and identifies Farming Systems for Africa at the continental level to capture current spatial extent of systems and provide a basis for updated analysis, trends, issues and strategic priorities for each system. Within this context delineating major farming systems provides a framework to guide development and targeting of strategic agricultural policies and interventions to reduce poverty and promote the adoption of more sustainable land management practices. In the 2015 study Systems were identified using an iterative process and a series of classifiers/informants including: available natural resources ( water, land, soils, elevation, length of growing period); Population (agriculture, rural, urban and total); Copping and pasture extent; the dominant pattern of farming activities and household livelihoods; access to markets and trends; nutrition, and estimated farm size Perhaps John which were augmented with expert input. A multidisciplinary team of experts were associated with each farming system assisting in the identification and characterisation process along with the documentation of issues such are emergent properties, drivers of change and trends, and priorities for each system. The current work updates and expands on the analysis of Sub-Saharan Africa Farming Systems in Dixon 2001 study. Many farming systems exhibit a strong geographical pattern reflecting a mix of factors such as climate, soil and markets. At the continental level broadly similar farming systems share recognizable livelihood patterns and similar development pathways, infrastructure and policy needs.

  • This dataset contains information about the administrative "Arrondissements" of Cameroon. The dataset is produced by the Institut National de Cartographie (INC) and the descriptions are made on the basis of topographic maps (INC background) at a scale of 1:200 000. This layer represents a global view of the regions and does not correspond to official boundaries. There is no legal validation process for this data. The dataset was edited by FAO-CSI for topology/geometry validation, schema and coding system conformance to SALB-UN specifications. International borders were updated/validated against the official/recognized borders from the United Nations Geospatial Information Section.

  • This dataset represents the administrative regions of Cameroon. Boundaries of territorial areas gathering several administrative divisions, placed under the authority of Governors. The dataset was originally produced by the Institut National de Cartographie (INC) and the descriptions are made on the basis of topographic maps (INC background) at a scale of 1:200 000. This layer represents a global view of the regions and does not correspond to official boundaries. There is no legal validation process for this data. The dataset was edited by FAO-CSI for topology/geometry validation, schema and coding system conformance to SALB-UN specifications. International borders were updated/validated against the official/recognized borders from the United Nations Geospatial Information Section.

  • In the past, work and emplyment implied the same, but the 2013 ILO revised concepts and definitions differentiates employment from work. Some one can be working but not employed as is common with those in agric sector due to susistence nature. At the same time, economically active population includes the employed and the unemployed. Yet in the Ugandan situation, we cannot categorise unemployed by sector. The data for previous years was actually for working population and NOT economically active population. Therefore working population has been extracted for comparability and suggest that you change the indicators to "working population" and NOT "economically active population" as reflected. **Table content** - Year - Indicator - Sex - Agricultural - Value - Flag - Unit