The resource mapping framework (RADIMA) is a tool for sub-national, county-level climate adaptation planning targeting the most vulnerable communities in developing countries, whose livelihoods may be reliant upon the effective management of natural resources. It allows the integration of community adaptive practice and climate change information into planning decisions at the local level by enabling natural resource information to be captured by local communities using a more detailed attribution model than that available in OpenStreetMap.
The granularity of data offered by the RADIMA application is also of value to the broader academic community. In particular, for research that focuses on adaptation and resilience of communities and the effects of climate change upon the natural resources from which these communities depend.
The importance of local knowledge in such a data capturing exercise cannot be underestimated, as land rights and planning decisions may stem directly from the data as represented in the system. In particular, the mapping of features based on topographic representation alone may not align with ownerships and rights information which may be essential to the resource management and to support advocacy. For example, the mis-representation of water sources in arid and semi-arid environments could have a profound effect upon any future climate change mitigation strategies. A significant challenge is to determine what level of crowd-sourcing and control is appropriate for the RADIMA application, as local people would not necessarily want their data to be edited by somebody who does not possess knowledge of the local area and rights-based information (i.e. who is perhaps on the other side of the world).
The depth of classification of land cover types is another example that presents its own set of challenges, such as the local and regional variability of pasture types, and their correct representation on the RADIMA map layer. By contrast, the question of accuracy and completeness arises as with any open-mapping framework. In the context of gaps in the data, do the gaps represent features that are missing from the map or do they genuinely represent the fact that no natural resource features exist at that location?
The challenges described above are discussed with examples across sub-Saharan Africa, together with the initiatives that are being taken to overcome them.
Further information: http://bit.ly/2t7fTg0