Aerial images (UAV) of burned and unburned olive trees
Published: 28 January 2025| Version 1 | DOI: 10.17632/83kpndkrb2.1
Contributor:
Christos VasilakosDescription
Dataset includes 3624 images of burned and unburned olive trees. These images are subsets of UAV images acquired by (a) Phantom-4 PRO RTK, (b) Phantom-4 Multispectral RTK (RGB sensor), and (c) Lidar L1 (using the optical spectrum sensor) mounted on a MATRICE 300 RTK (DJI. The aforementioned flights were conducted at various altitudes, resulting in data with different Ground Sampling Distances (GSDs). The burned trees were identified by visual interpretation of UAV images and field trips in two states: either partially burned, where part of the canopy was damaged while the remaining portion stayed healthy (green foliage), or fully damaged, where the entire canopy was affected.
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Institutions
University of the Aegean School of Social Sciences
Categories
Machine Learning, Image Classification, Agricultural Land, Olive