Rulinda, C.M and Dilo, A. and Bijker, W. and Stein, A.
Characterising and quantifying vegetative drought in East Africa using fuzzy modelling and NDVI data.
Journal of Arid Environments, 78.
*** ISI Impact 1,623 ***
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Official URL: http://dx.doi.org/10.1016/j.jaridenv.2011.11.016
This study aims at improving the characterisation and quantification of vegetative drought as a vague spatial phenomenon. 10-day NOAA-AVHRR NDVI images of East Africa from September 2005 to April 2006 are used. Vegetative drought is characterised using a membership function to model the gradual transition between drought and non-drought classes.
Measures are implemented to quantify the areas and vagueness of vegetative drought, and to visualise its evolution in space and time. Results show a severe drought, affecting more than 60% of the vegetated area in the region. Different degrees of vagueness are observed in time, independently of the change of the transition range; the vagueness remains higher at the onset than at the termination of drought, reflecting a more gradual movement to drought and a crisper return to normal conditions.
The vagueness was the lowest at the drought peak. The mean-area is less vulnerable to the change of the transition range, compared to the core-area. A Crisp approach, using the median of the transition range as the threshold value, does not quantify the vagueness of vegetative drought. This method can also be used in other regions, or adapted to characterise and quantify other vague spatial phenomena.
|Research Group:||EWI-PS: Pervasive Systems, ITC-EOS: Earth Observation Science|
|Research Program:||CTIT-WiSe: Wireless and Sensor Systems|
|Research Project:||FREE: True-wireless mesh networks for transport and logistics|
|Uncontrolled Keywords:||Remote sensing data, Drought, Fuzzy set theory, Measures, Vague spatial objects|
|Deposited On:||15 February 2012|
|ISI Impact Factor:||1,623|
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