Predicting stem borer density in maize using RapidEye data and generalized linear models

Remote sensing can help improve decision-making in the integrated pest management of stemborers

Abstract

Maize stemborers are the most injurious biotic constraints to the production of maize in sub-Saharan Africa:

The International Centre of Insect Physiology and Ecology (icipe) and partners explored the value of using high-resolution, large-area image data to predict per field maize stemborer larval densities in two study sites in Kenya.

The study concludes that remote sensing can help improve decision-making in the integrated pest management of stemborers.

This work is part of the ‘Impact of Biological Control of Stem Borers on Maize and Sorghum Production in East and Southern Africa project’ which is funded by the UK Department for International Development.

Citation

Abdel-Rahman E.M., Landmann T., Kyalo R., Ong’amo G., Mwalusepo S., Suleiman S. and Le Ru B.P. (2017) Predicting stem borer density in maize using RapidEye data and generalized linear models. International Journal of Applied Earth Observation and Geoinformation 7 61–74. doi: 10.1016/j.jag.2016.1012.1008.

Predicting stem borer density in maize using RapidEye data and generalized linear models

Updates to this page

Published 31 January 2017