World Journal of Agricultural Research
ISSN (Print): 2333-0643 ISSN (Online): 2333-0678 Website: Editor-in-chief: Rener Luciano de Souza Ferraz
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World Journal of Agricultural Research. 2018, 6(4), 153-166
DOI: 10.12691/wjar-6-4-6
Open AccessArticle

Evaluating the Association between Climate Variability and Vegetation Dynamics by Using Remote Sensing Techniques: The Case of Upper Awash Basin, Ethiopia

Getachew Bayable Tiruneh1, , Berhan Gessesse2, Tulu Besha3 and Getachew Workineh4

1Department of Land Administration and Surveying, Oda Bultum University, Chiro, Ethiopia

2Remote Sensing Research Division, Entoto Observatory and Research Centre, Addis Ababa, Ethiopia

3Geodesy Research Division, Entoto Observatory and Research Centre, Addis Ababa, Ethiopia

4Department of Geography and Environmental Science, Debre Tabor University, Debre Tabor, Ethiopia

Pub. Date: December 28, 2018

Cite this paper:
Getachew Bayable Tiruneh, Berhan Gessesse, Tulu Besha and Getachew Workineh. Evaluating the Association between Climate Variability and Vegetation Dynamics by Using Remote Sensing Techniques: The Case of Upper Awash Basin, Ethiopia. World Journal of Agricultural Research. 2018; 6(4):153-166. doi: 10.12691/wjar-6-4-6


Examining the impact of climate variability on vegetation dynamics is the missing research element in Upper Awash Basin. Hence, the aim of this study was investigating climate variability and their impacts on vegetation dynamics. Monthly 250 meter resolution Moderate Imaging Spectro-radiometer (MODIS) Normalized difference vegetation Index (NDVI), 1kilometer resolution MODIS Land Surface Temperature (LST), rainfall data from 19 meteorological stations, and NINO3.4 (SSTA) were used for this study. A Mann Kendall (MK) trend test was used to determine the trend of each dataset using seasonal and annual time-series. Pearson correlation coefficient was also used to estimate the association between NDVI and climatic elements. Results of this study revealed that there was no significant change in the annual and seasonal NDVI, LST, Sea surface Temperature Anomaly (SSTA) and rainfall during the period 2001 to 2016, except NDVI in belg season. The correlation between NDVI and rainfall was positive (r = 0.51), strong positive (r= 0.62), low positive (r = 0.45) and low negative (r = -0.33) for annual, belg, bega and kiremit seasons, respectively. Similarly, the correlation between NDVI and LST was negative (r = - 0.58), strong negative (r= -0.67), negative (r = -0.5) and low positive (r = 0.41) for annual, belg, bega and kiremit seasons, respectively. On the other hand, the correlation between NDVI and SSTA was low negative (r = - 0.41), weak negative (r= -0.29), weak positive (r = 0.22) and low positive (r = 0.42) for annual, bega, belg as well as kiremit seasons, respectively.

climate variability LST NDVI RF SSTA upper awash basin

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