A Systematic Review of Remote Sensing Techniques for Monitoring Pests and Diseases in Tree Crops

Tree crops are essential agroecosystems that contribute to global food security and economic development by providing a variety of fruits, nuts, and other edible products. However, the sustained production of these crops is increasingly threatened by pest and disease (P&D) pressure. Remote sensing (RS) techniques provide non-invasive, scalable tools for monitoring the physiological responses of crops to biotic stressors and for integrated P&D management frameworks. Despite their increased use in recent decades, there remains limited clarity regarding the frameworks, parameters, and spectral variables used to assess tree crop health. This is because earlier reviews focused primarily on food crops and forest trees, paying little attention to tree crops. To fill this gap, we conducted the first systematic review of the peer-reviewed literature to evaluate the scope, opportunities, and methodological approaches for RS applications across a wide spectrum of tree crops. Our findings show that research using RS techniques in tree crop health monitoring has grown consistently since 1974, with studies focusing on citrus, oil palm, olives, and rubber trees accounting for more than half of the reviewed literature (52.73%). Spectral indices derived from both hyperspectral and multispectral data, analysed using machine learning and statistical models, were the dominant approach for monitoring P&D dynamics in tree crops. Geographically, most studies have been concentrated in North America and Eurasia, with limited application in tropical tree crops. Extending the use of RS techniques to economically important tropical tree crops will not only support adaptive responses to biotic threats but also improve yields and sustainability across tree-crop systems worldwide.