Atlas of climate risks and livelihood of farmers’
The Atlas of agricultural livelihood and climate risk was launched on the 9th of August and contains a multiplicity of innovative maps that are rarely produced at national level in such a harmonized manner. The Department of Agricultural Land Management (DALAM) and the National Agriculture and Forestry Research Institute (NAFRI), within Ministry of Agriculture and Forestry (MAF) have collaborated to produce these information and maps. Two projects, the SAMIS and the CIAT De-Risk, have deeply collaborated with DALAM and NAFRI to develop the present information. After nearly five years of fieldwork, GIS mapping, and text writing, the Atlas is a prime in the country.
This Atlas contains socio-economic and technical data, but not the usual ones that are collected through statistics. First, it helps identify areas where farmers are unable to satisfy their basic needs. This identify areas that require extensive and long-term interventions to improve farmers’ adaptive capacity. This means this Atlas can help donors and government to target interventions geographically.
In addition, areas suitable for the rolling out of new or improved agricultural practices can also be identified based on whether or not farmers have the resources needed for innovation and are able to take action to mitigate the impact of climate risks. This means this Atlas helps defining which intervention should target a certain area.
In summary, this Atlas provides leaders and development partners at all levels with the data needed to effectively plan climate change adaptation interventions. National teams are now able to independently use and access this information to help them manage agricultural production and promote the cultivation of high-quality produce.
The livelihood and climate risk data same data are also visible and downloadable in the Land Resources Information Management System. In the online system, every livelihood area is characterized by water, income, and food security, farm management practices, financial and natural resources, support infrastructure, access to ICT and farmers attitudes. This is the first time that a big data system like LRMIS is enabled to produce such an advanced visualization of the data.