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Tracking the magnitude of climate change and variability with remote sensing data to improve targeting of climate smart agricultural technologies

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Title Tracking the magnitude of climate change and variability with remote sensing data to improve targeting of climate smart agricultural technologies
 
Creator Muthoni, Francis K.
 
Subject climate change
data analysis
remote sensing
climate-smart agriculture
 
Description Quantifying the magnitude and significance of climate change variables over space and time in Africa is challenging due to sparse distribution of weather stations and poor quality of existing data. Time series climate data generated from remote sensing platforms could provide plausible alternative for measuring the trends of climate change in data limiting context. This study utilise time series remote sensing data for rainfall, maximum temperature and minimum temperature to investigate the magnitude and significance of spatial-temporal trends over six countries in West Africa. A modified Mann-Kendall test and Theil-Sen's slope are utilised to test the significance and the magnitude of trends respectively for period between 1981 and 2017. June to September rainfall along the Sahel, Sudan and northern Guinea savanna agro-ecological zones revealed a significant increase (0.1 - 3 mm yr -1 ) that peaked in August. Extreme temperatures for period between August and October remained stable while significant positive trend (0.005 - 0.07°C yr -1 ) was observed in rest of months. Areas experiencing significant drying and warming trends are earmarked as priority for targeting appropriate climate smart agricultural technologies. The widespread significant increase of extreme temperatures justifies increased investments in measures to cope with heat stress.
 
Date 2019-07
2019-10-17T12:33:41Z
2019-10-17T12:33:41Z
 
Type Conference Paper
 
Identifier Muthoni, F. K. (2019). Tracking the magnitude of climate change and variability with remote sensing data to improve targeting of climate smart agricultural technologies. In 2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics). Istanbul, Turkey: IEEE, (p.1-4).
978-1-7281-2116-1
https://hdl.handle.net/10568/105453
https://doi.org/10.1109/agro-geoinformatics.2019.8820655
BIOMETRICS
 
Language en
 
Rights Copyrighted; all rights reserved
Limited Access
 
Format 1-4
 
Publisher Institute of Electrical and Electronics Engineers