Using similarity maps to promote conservation agriculture

A Conservation Agriculture suitability Map for Morocco

Conservation agriculture (CA) is key to creating and maintaining food and environmental security practices that can provide sustainable livelihoods in dry and arid regions. To make it work, it is crucial to have better data and information on agricultural land and its potential.

ICARDA launched a two-pronged Geospatial Science, Technology and Applications (GeSTA) pilot study using a ‘target’ area and ‘match’ location to better assess which areas in North Africa could be optimized for CA. Land similarity and other factors, including edaphic variations, regional climate, and bio-physical land features are compared and analyzed in the process.

The ‘match’ location in this case was Morocco. Its location in the northwestern region of the larger study encompasses the country’s most populous areas, along with a wide range of agro-climactic zones (including a Mediterranean clime), making it an ideal location. Additionally, while Morocco has been an early CA innovator (since the 1990s) — implementing field demonstrations that have reduced soil erosion, improved soil quality and yielded stable and higher crop yields — Moroccan farmers have yet to adopt these practices at large. It is therefore important that such suitability and similarity maps also include a socio-economic component. 

Because CA practices are increasingly information-driven and address a complex set of issues, decision-makers must have up-to-date information on a variety of factors. The pilot study seeks to develop spatial information to provide such key ‘decision-guiding’ informatics. To date, poor imaging (low-resolution), the lack of open-access data and information, and varied methods of data collection, if any, often mar the process.

Thus the program objectives were to:

  1. Develop regional level similarity maps for out-scaling based on the matching of bio-physical similarities identified from the pilot sites;
  2. Develop suitability maps to identify ideal areas for CA adoption in Morocco.

To create comprehensive data for CA implementation the project would answer questions like:

  • What is the spatial extent of area (in ha) suitable for CA?
  • How many farmers live in potentially suitable areas?
  • What are the agro- and socio-economic characteristics of the CA area?

Additional data, including, for example, the number of farmers and households in a region, machinery available, etc., and other factors could make the technology an excellent tool in facilitating greater CA adoption in the region.

The pilot study was funded through the Conservation Agriculture for North Africa (CANA) Project, Australian Centre for International Agricultural Research (ACIAR) and the Multi-National Geospatial Co-Production Program III-International Resource Management (INRM).