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A new development in mobile app to match land use with it’s potential

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Farmers, development organizations, extension workers and national governments will soon have an opportunity to share, access and apply the best available knowledge and information to determine the agricultural productivity and erosion risk level of land at field, regional, and national scale using the new Land Potential Knowledge System (LandPKS) mobile application

Leveraging the emerging trends in mobile phone technology, the LandPKS mobile phone app allows users principally farmers to make accurate farm decisions on the potential of their land in terms of crop production; types and soil erosion risk based on soil features, and also produces knowledge for aiding decision making in sustainable land management practices. The LandPKS mobile app facilitates the integration of local and scientific information and knowledge through crowdsourcing and innovative support system that provides users with robust information with similar characteristics to their land from other places around the world to be able to make farm decisions on production. Currently, LandPKS users get information on relative productivity and erosion risk for maize and grass.

The LandPKS mobile app relies on various sources of global datasets including Digital Elevation Model (DEM) maps, derivatives (slope, curvature, aspect, and land forms), weather data (precipitation, land surface temperature, and solar radiation), wind (NCEP/NCAR reanalysis) soil data (depth, texture, toxicity, workability, rock fragment, content etc), land cover, and land use maps among other datasets. The LandPKS project has made considerable effort to partner with different organizations such as African Technology Policy Studies (ATPS), Regional Centre for Mapping of resources for Development (RCMRD), and Northern Rangelands Trust (NRT). Another supporting partner is The Africa Soil Information system (AfSIS) who is providing soil database for validating maize predictions.

The partners have been holding several fortnightly meetings to ensure that the success of the LandPKS project is fully achieved. ATPS is working with LandPKS to provide policy briefs, develop a LandPKS stakeholders mapping and communication outreach strategy where ATPS will be greatly involved in the implementation of the project.

So far, the LandPKS mobile app has progressed to providing relative grass and maize productivity estimates. However, validation, and testing of model’s confidence levels on both maize and grass are still on going. Proper predictions are determined by the understanding and accuracy of the user, light source and soil conditions (wet or dry). The LandPKS soil colour app (an important feature of the app) is still under development.

In spite of the enormous progress made with the development of the app, there remain some challenges that need to be addressed like; inadequate data availability in Africa, unwillingness of institutions to share data, as well as sparse data in arid and semi-arid land (ASAL) where the knowledge system is being piloted. Predictions are therefore relative estimates. Following several feedbacks and information input, the LandPKS mobile app inte rface and capabilities are being modified using higher resolution datasets(30m) to improve the accuracy in predictions.

In future, the app will incorporate local knowledge on working practices (indigenous knowledge), globally connect users with similar needs/problems, and improvement of the models predictive capabilities through use of artificial intelligence. This will be one development of its kind that will contribute to sustainable food production, reduction in soil erosion risk and increase income opportunities for future generations.

For inquiries on collaboration and funding support, please do kindly contact:
The Executive Director,
African Technology Policy Studies Network (ATPS),
3rd Floor, The Chancery Building, Valley Road,
P.O. Box 10081- 00100 GPO, Nairobi, Kenya,
Telephone: +254 (0) 20-2714092; Mobile: +254 (0) 713 161 928; Fax +254-20-2714028

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