Apr 14, 2020

Suitability of resampled multispectral datasets for mapping flowering plants in the Kenyan savannah

BioRxiv : the Preprint Server for Biology
David Masereti MakoriS. M. Raina


Pollination services and honeybee health in general are important in the African savannahs particularly to farmers who often rely on honeybee products as a supplementary source of income. Therefore, it is imperative to understand the floral cycle, abundance and spatial distribution of melliferous plants in the African savannah landscapes. Furthermore, placement of apiaries in the landscapes could benefit from information on spatiotemporal patterns of flowering plants, by optimising honeybees' foraging behaviours, which could improve apiary productivity. This study sought to assess the suitability of simulated multispectral data for mapping melliferous (flowering) plants in the African savannahs. Bi-temporal AISA Eagle hyperspectral images, resampled to four sensors (i.e. WorldView-2, RapidEye, Spot-6 and Sentinel-2) spatial and spectral resolutions, and a 10-cm ultra-high spatial resolution aerial imagery coinciding with onset and peak flowering periods were used in this study. Ground reference data was collected at the time of imagery capture. The advanced machine learning random forest (RF) classifier was used to map the flowering plants at a landscape scale and a classification accuracy validated using 30% independent test s...Continue Reading

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Mentioned in this Paper

RNA Polymerase II
DNA-Directed RNA Polymerase
Transcription, Genetic
DNA, Ribosomal
Gene Expression
Recombinant DNA
Cell Nucleolus

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