# UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health
## 1 Introduction  
Highly productive plantation forests are required to meet the timber and fibre demands of the Earth's population in a sustainable manner. A significant research effort is focussed on maximising the returns from global forest plantations through silvicultural practices [1; 2], tree breeding programmes [3; 4], improving forest nutrition [5], and developing remote sensing methods to enhance forest management [6; 7; 8]. Yields from intensively managed monoculture plantations face significant threats from unwanted organisms, the impact of extreme weather events, and increasingly from the adverse effects of air pollution [9; 10]. The frequency and severity of losses associated with these factors are expected to increase in many regions as the effects of climate change become more severe [11]. Tools to detect, quantify, and help mitigate the impacts of these damaging biotic and abiotic factors are essential for maximising plantation forest yields. In recent years, significant progress has beenmade towards the detection and monitoring of pests and diseases in trees and forests. These methods often use remote sensing and ground assessments to detect signs and symptoms of a stressor [12]. Surveillance procedures are required for a range of spatial scales to detect incursions and to inform effective forest management to mitigate negative effects on tree growth and the probability of tree mortality [13; 14]. Since the advent of civilian Earth-observing satellites suitable for vegetation monitoring, a significant body of research has used satellite imagery to quantify the spatial extent of insect outbreaks and tree mortality at regional and landscape scales using moderate (5-30 m) and coarse (\(\geq\)30 m) resolution imagery [15; 16; 17; 18]. More recently, research has established the utility of high-resolution (\(\leq\)5 m) satellite imagery [19; 20; 21] and imagery collected from manned aerial platforms [14; 22; 23] for monitoring tree health. This research has shown that sensors with finer spatial resolution offer greater accuracy for detecting and monitoring disease expression. This is especially true for early-stage outbreaks or those with a limited spatial extent that may only be apparent at the sub-stand or individual tree level. Unmanned aerial vehicles (UAVs) have emerged as a useful data source applicable to many forest management scenarios [24]. A growing number of studies have examined the use of UAVs for a wide range of applications including forest measurement [25; 26; 27; 28; 29; 30], informing silvicultural practice [31; 32], forest health monitoring [12; 33; 34; 35], and monitoring events such as fires [36; 37], wind damage [38], and harvesting [39]. The cost of these platforms and associated sensors are rapidly decreasing while their capabilities and sophistication are constantly improving. There are several appealing aspects of UAVs including greater flexibility due to ease of deployment and transportation, ability to capture extremely high resolution data, and the capacity to capture useful imagery even in the presence of cloud cover. UAVs cannot rival traditional platforms in terms of spatial extent; however, with appropriate processing and analysis frameworks, data from UAVs are likely to offer substantial opportunities to augment and enhance data collected from these more traditional platforms. A few studies have sought to develop methods linking UAV data and satellite imagery to provide an enhanced data product with utility beyond that of the component datasets. Imagery collected from UAVs has been used to calibrate measures of burn severity derived from Landsat 8 imagery following a wildfire with some success [40]. UAV imagery has also been used to augment satellite imagery to inform land managers about compliance with resource management policy in riparian habitats. The UAV imagery enhanced both the temporal and spatial resolution of the satellite imagery providing an effective tool for monitoring compliance and for conservation of endangered habitat [41].