## 6 Olive Disease Detection and Pest Management  
Diseases detection is critical to preventing and limiting the loss of crop production and farm profits. Early detection of disease symptoms and their spatial extent can help contain the spread of the disease and production losses. Traditional field inspections are time-consuming, labor-intensive, and prone to human error. It can be challenging to detect the disease during the early stages when symptoms are not completely visible [182]. It is also difficult to map the spatial extent and severity of the disease spread with the traditional method of field scouting [122]. RS solves many of these problems if used to detect and monitor several diseases in different crops [183], showing itself capable of detecting diseases whose symptoms are well evident in the aerial part of the plant and those affecting the roots [184,185]. The research concerning the detection of olive disease symptoms by RS imagery has mainly focused, to our knowledge, on two diseases (Table 5): Verticillium Wilt (VW) caused by the soil-borne fungus _Verticillium Dahliae Kleb._ and Quick Decline Syndrome caused by the bacterium _Xyella fastidiosa_ Wells [186]_subsp. pauca_ (hereafter Xf). Verticillium is present in the soil, in favorable conditions, in the form of resistant survival structures called'microsclerotica' that can be stimulated to germinate by root exudates [187], generating hyphae that penetrate the roots, growing into their tissues until they reach the xylem vessels. The consequence is the spread of the fungus in the aerial parts of the plant, which causes a reduction in the water flow, inducing water stress and wilt symptoms [188, 189, 190]. In the Mediterranean area, VW's incidence and symptoms severity increase from late autumn to spring while sharply decreasing in summer, followed by a flare-up in the autumn months [191]. The most effective strategy against this disease involves using preventive control measures, in the pre- and post-planting stages [192], including irrigation management, weed control, tillage practices, soil solarization, etc. However, visual inspections to detect symptoms in the early stages are costly and time-consuming compared with the above practices, which might be more effective [191,193]. In addition, it is not conceivable to perform this strategy on each tree in olive groves of large areas [194]. The damages reported by the plant, including leaf chlorosis, defoliation, and reduced transpiration rate, can be remotely detected in the visible, Red Edge, NIR, and thermal regions of the electromagnetic spectrum [195]. In particular, the decrease of chlorophyll content in infected plants causes a higher reflectance in the visible (Green) and Red Edge, while the reduction in canopy density and leaf area corresponds to a decrease in spectral reflectance in the NIR. Furthermore, VW induces stomata closure, reducing evaporative cooling and causing an increase in leaf temperature detectable in thermal images [196]. In this regard, [PERSON] et al. [183] evaluated the use of thermal imagery and physiological indices derived from MS and hyperspectral sensors (mounted on UAV) for early detecting symptoms of infection caused by Verticillium in olive groves. This research showed that stomatal conductance is lower and canopy temperature variations are higher as the severity level of the disease increases. MS and hyperspectral sensors were used for calculating spectral indices related tree crown structure, epoxidation state of