MONITORING OF TREES' HEALTH CONDITION USING A UAV EQUIPPED WITH LOW-COST DIGITAL CAMERA

Invasive insect pests and fungi, which are introduced accidentally to forests and affect tree growth and survival, constitute a serious threat for the forests and trees acting on climate change and its impacts. Thus, the need for early and accurate health determination process of forest regions, has significantly increased the interest in automatic monitoring methods. In this paper, in order to overcome the great variety of trees' characteristics and forests' heterogeneity that affects the diversity of their color and texture making the detection of diseases a difficult task, a methodology for individual tree detection applying energy minimization, visualizing HOG features across tree canopies and using a dynamically clustering method is proposed. Then, in order to achieve classification based on their health condition, multi-pyramid textural features are proposed and extracted. The experimental results presented use images of a forest area in Greece that include fir trees and show the great potential of the proposed methodology.