Detecting canopy damage caused by Uromycladium acaciae on South African Black Wattle forest compartments using moderate resolution satellite imagery

Muhammad Sheik Oumar, Kabir Peerbhay, Ilaria Germishuizen, Onisimo Mutanga, Zakariyyaa Oumar

Abstract


Uromycladium acaciae, also known as wattle rust, is a rust fungus that has adversely impacted black wattle (Acacia mearnsii) in South Africa. This study assessed the potential of the Landsat 8 multispectral sensor to detect canopy damage caused by wattle rust on two plantation farms near Richmond, KwaZulu-Natal. The Landsat 8 bands and vegetation indices detected forest canopy damage caused by Uromycladium acaciae with an accuracy of 88.24% utilising seven bands and the Partial Least Squares Discriminate Analysis (PLS-DA) algorithm. Additionally, the model was optimised using the Variable Importance in Projection (VIP) method which only selected the most influential bands in the model. The coastal aerosol band (430nm-450nm), red band (640nm-670nm), near infrared (850nm-880nm) and NDVI were exclusively used in the optimised model and an accuracy of 82.35% was produced. The study highlighted the potential of remote sensing to detect canopy damage caused by a rust fungus and contributes towards a monitoring framework for analysing trends using freely available Landsat 8 imagery.


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