Avo-AirDB: An avocado UAV Database for agricultural image segmentation and classification

Khalid El Amraoui; Mouataz Lghoul; Ayoub Ezzaki; Lhoussaine Masmoudi; Majid Hadri; Hicham Elbelrhiti; Aziz Abdou Simo

doi:10.1016/j.dib.2022.108738

Avo-AirDB: An avocado UAV Database for agricultural image segmentation and classification

Data Brief. 2022 Nov 9:45:108738. doi: 10.1016/j.dib.2022.108738. eCollection 2022 Dec.

Authors

Khalid El Amraoui¹, Mouataz Lghoul¹, Ayoub Ezzaki¹, Lhoussaine Masmoudi¹, Majid Hadri¹, Hicham Elbelrhiti², Aziz Abdou Simo³

Affiliations

¹ LCS Laboratory, Physics Dept. faculty of science, Mohammed 5 university in Rabat, 4 ibn Battouta Street, Rabat, Morocco.
² Department of Fundamental and Applied Sciences (DSFA), Hassan II Agronomic and Veterinary Institute, BP 6202 Madinat Al Irfan, Rabat, Morocco.
³ ABAZ company, Allal tazi, Kenitra, Morocco.

Abstract

Unmanned aerial vehicles (UAVs) with on-board cameras have the advantage of providing Bird-view images (Aerial images). This type of image is considered as a rich source of information especially for intelligent agriculture. A dataset of 984 aerial images of avocado threes is made publicly available with a ground resolution of 2.7 cm per pixel. It has been collected from over 113 Hectares of an avocado farm in ALLAL TAZI region of Morocco using a DJI Phantom 4 Pro UAV. It comprises original bird view and annotated images. The dataset is available at https://data.mendeley.com/datasets/tvhh83r3hj/2.

Keywords: Avocado; Dataset; Digital agriculture; Unmanned aerial vehicles.