dc.contributor.author |
Mwaniki, Purity Njeri |
|
dc.contributor.author |
Kuria, David Ndegwa |
|
dc.contributor.author |
Mundia, Charles N. |
|
dc.contributor.author |
Makokha, Godfrey Ouma |
|
dc.date.accessioned |
2018-05-22T10:24:21Z |
|
dc.date.available |
2018-05-22T10:24:21Z |
|
dc.date.issued |
2018-05-17 |
|
dc.identifier.citation |
doi: 10.11648/j.ajese.20180201.11 |
en_US |
dc.identifier.uri |
http://41.89.227.156:8080/xmlui/handle/123456789/741 |
|
dc.description.abstract |
This research analyses the changes in coverage Mt Kenya glaciers in a bid find what has been causing the retreat of
these glaciers. Optical Landsat data for 1984 to 2017 and Climatic data of the same years were used. Glaciers and forest coverage
were extracted from Landsat images and its thermal band was used to extract temperature data. Correlation with the respective
year’s climatic data and forest cover area were done to justify the assumption that the shrinkage in the glaciers coverage has been
caused by changes in climate and/or deforestation. Then using the historical EC Earth model climate data predictions for
1984-2017 and historical observed data for the same years, bias correction factors were computed and used to correct the future
model data for the years (2018-2045). Since the data was extracted for only four points around Mt Kenya, Interpolation was then
done to obtain the Precipitation and Temperature for the mountain peak (since the glaciers are found at the peak) using the IDW
technique. Prediction of glacier area coverage was then done using these interpolated climate data. In order to predict the future
glacier cover, linear equations of the form y = a1x1 + a2x2 +bo of the interpolated climate data (for 2018-2045) and computed
glacier areas for (1984-2017) were formed. The a1 a2 and bo in the equation are constants obtained from SPSS (a statistical
software). X1 and x2 are the predicted Temperature and Precipitation respectively. Predictions were done for RCP scenarios 8.5
and 4.5. The results of prediction showed that the current trend of glacier thinning is going to continue but at a slower rate
compared to the rapid melting that was observed for the period 1984-2017. However, Mt Kenya glaciers are likely to have
completely disappeared by the year 2100. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
American Journal of Environmental Science and Engineering |
en_US |
dc.relation.ispartofseries |
Volume 2;Issue 1 |
|
dc.subject |
Glaciers and Forest Coverage, Climate, Prediction |
en_US |
dc.title |
Analysis of Mt Kenya Glaciers Recession Using GIS and Remote Sensing |
en_US |
dc.type |
Article |
en_US |