SMALL-SCALE CROP MAPPING

The agricultural sector is the backbone of Kenya’s economy, contributing to approximately 30% of the GDP. Kenya’s agriculture is predominantly small-scale farming and is carried out on farms averaging less than a hectare, mostly for subsistence.Small-scale operations account for over 70% of agricultural production and meet about 75% of the national food demand. When mapping crops, it is important to map out these important demographics.

Small-scale crop mapping using Space data is one of the most effective ways in estimating the crop area, crop yields and to assess the food security situation in the country. This can be achieved by processing and analyzing Remote Sensing data. This data, however, requires high processing techniques with complex mathematical processes. The field of Artificial Intelligence/Machine Learning (AI/ML) uses data and algorithms to imitate the way that humans learn, gradually improving the accuracy of the results. The major focus of AI/ML is to extract information and actionable insight from data automatically by computational and statistical methods. Over the last decade there has been considerable progress in developing an AI/ML methodology for a variety of Earth Observation applications.
KSA is proposing a Research Chair to leverage on the potential of AI/ML in mapping crops under small scale farms. The Agency will be offering a RC award on the Small-Scale Crop Mapping application using AI/ML which is worth Ksh 2Million and with FOUR beneficiary Universities each to receive Ksh 500,000.