Tree Crowns Segmentation and Classification in Overlapping Orchards Based on Satellite Images and Unsupervised Learning Algorithms.

Abstract

Smart agriculture is a new concept that combines agriculture and new technologies to improve the yield's quality and quantity as well as facilitate many tasks for farmers in managing orchards. An essential factor in smart agriculture is tree crown segmentation, which helps farmers automatically monitor their orchards and get information about each tree. However, one of the main problems, in this case, is when the trees are close to each other, which means that it would be difficult for the algorithm to delineate the crowns correctly. This paper used satellite images and machine learning algorithms to segment and classify trees in overlapping orchards. The data used are images from the Moroccan Mohammed VI satellite, and the study region is the OUARGHA citrus orchard located in Morocco. Our approach starts by segmenting the rows inside the parcel and finding all the trees there, getting their canopies, and classifying them by size. In general, the model inputs the parcel's image and other field measurements to classify the trees into three classes: missing/weak, normal, or big. Finally, the results are visualized in a map containing all the trees with their classes. For the results, we obtained a score of 0.93 F-measure in rows segmentation. Additionally, several field comparisons were performed to validate the classification, dozens of trees were compared and the results were very good. This paper aims to help farmers to quickly and automatically classify trees by crown size, even if there are overlapping orchards, in order to easily monitor each tree's health and understand the tree's distribution in the field.

Plant phenotyping relevance

衛星画像と機械学習により樹冠を分割し、個々の樹木を樹冠サイズ・生育状態で分類する手法が研究の中心で、現地比較による検証も行っているため。

Code and data availability

The paper uses proprietary Mohammed VI satellite imagery of the OUARGHA orchard and field measurements, with no public data, code, model, or supplement availability statement anywhere in the supplied blocks. QGIS is only a generic tool, not a paper-specific asset.

No evidence-backed public reproduction asset is currently recorded.