Tree Detection and Localization Approach for UAV-based Forest Inspection

Abstract

This paper addressed an UAV-based solution for forest inspection from the aspect of data processing. Insect infected trees can be identified from aerial imagery. The forest inspection data processing divided into two main phases, which are tree detection and tree localization. For the tree detection task, the Deep Learning-based approach has been used. In this study, a conventional and active learning method have been used for the training. In order to map the detected trees from the video frame to geographical locations, a custom geo-localization algorithm has been developed. The proposed system loads the inspection video as an input and calculates and outputs the detected trees’ GPS coordinates. In the calculation Digital Elevation Model and camera parameters are used in addition to drone geo-data to calculate the tree positions.

Aerial object detection analysis: Challenges and preliminary results

“…Experiments are needed to determine the optimal distance between the object and the camera to recognize the object optimally. The previous study [1] also experienced the same thing. In their paper, they considered that the distance between the camera and the object needs to be considered in detail.…”

“…Computer vision will enable computers to retrieve information from images, videos, and other visual inputs. The role of computer vision in the development of technology has had a tremendous impact on almost all aspects of life [1].…”