Multi-pronged abundance prediction of bee pests’ spatial proliferation in Kenya
Bee farming and beehealth are threatened by climate change, agricultural and agrochemicals intensification, and bee pests and diseases. Among these threats, bee pests have particularly been identified as a major obstacle to beehealth. Although previous studies have endeavoured to establish bee pests...
Main Authors: | David Masereti Makori, Elfatih M. Abdel-Rahman, John Odindi, Onisimo Mutanga, Tobias Landmann, Henri E.Z. Tonnang |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2024-04-01
|
Series: | International Journal of Applied Earth Observations and Geoinformation |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S156984322400092X |
Similar Items
-
The use of multisource spatial data for determining the proliferation of stingless bees in Kenya
by: David Masereti Makori, et al.
Published: (2022-12-01) -
Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models
by: David M. Makori, et al.
Published: (2017-02-01) -
Suitability of resampled multispectral datasets for mapping flowering plants in the Kenyan savannah.
by: David Masereti Makori, et al.
Published: (2020-01-01) -
Data-Driven Artificial Intelligence (AI) Algorithms for Modelling Potential Maize Yield under Maize–Legume Farming Systems in East Africa
by: Komi Mensah Agboka, et al.
Published: (2022-12-01) -
A Fuzzy-Based Model to Predict the Spatio-Temporal Performance of the <i>Dolichogenidea gelechiidivoris</i> Natural Enemy against <i>Tuta absoluta</i> under Climate Change
by: Komi Mensah Agboka, et al.
Published: (2022-08-01)