This paper introduces a dataset of aerial imagery captured during the 2022 cocoa growing season in the central-western region of Côte d'Ivoire. The images were acquired using a multispectral camera mounted on a DJI Phantom 4 unmanned aerial vehicle (UAV). The agricultural land surveyed encompasses 10 different types of cocoa-based agroforestry systems, each ranging from 2.6 ha to 8.3 ha, totaling 7638 images and covering 30 ha. The UAV mission was conducted at an altitude of 80 m, with a side overlap of 70 % and a front overlap of 80 %. This configuration achieved ground sampling distances (GSD) ranging from 4.2 to 4.6 cm providing high-resolution detailed imagery of those lands. These high-resolution RGB and multispectral images can be used to characterize the structural complexity of the systems as well as the abundance, and the health of the trees in these cocoa-based systems. It can be a valuable resource for researchers in the fields of ecology, agriculture, and environmental monitoring. The dataset supports a wide range of applications, from precision agriculture to sustainable cocoa land use management, making it a pivotal tool for enhancing agricultural practices and ecosystem management in Ivorian regions facing environmental and economic challenges.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11261247PMC
http://dx.doi.org/10.1016/j.dib.2024.110664DOI Listing

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