Journal of Agriculture and Horticulture Research(JAHR)

Forest Engineer, Istanbul, Turkey

Publications

• Research Article   
  Accuracy of Deep Learning-Based Satellite Image Analysis in Early Detection of Insect Infestation-Induced Tree Mortality: A Comparative Analysis with Conventional Remote Sensing Methods
  Author(s): Kaan Alper*
  
  Bark beetles, exacerbated by drought and temperature increases intensified by climate change, have caused unprecedented levels of tree mortality in coniferous forests of the Northern Hemisphere over the past decade. Early-stage detection of infestation foci — particularly during the green-attack phase, when no visual symptoms are yet apparent in the foliage — is critically important for preventing outbreak spread and reducing economic losses. This study aims to systematically and comparatively examine the accuracy of deep learning-based satellite image analysis in the early detection of insect infestation-induced tree mortality against commonly employed conventional remote sensing methods. The research was conducted in the Bohemian Forest on’ndaki Ips typographus NDVI/NDMI thresholding, Random Forest, Support Vector Machines, and Maximum Likelihood classification wit.. Read More»
  

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