Airborne Vehicles Research Articles

THE SUPERSPECTRAL/HYPERSPATIAL WORLDVIEW-3 AS THE LINK BETWEEN SPACEBORNE HYPERSPECTRAL AND AIRBORNE HYPERSPATIAL SENSORS: THE CASE STUDY OF THE COMPLEX TROPICAL COAST

Abstract. Earth observation of complex scenes, such as coastal fringes, is based on a plethora of optical sensors constrained by trade-offs between spatial, spectral, temporal and radiometric resolution. The spaceborne hyperspectral EO-1 Hyperion sensor (decommissioned in 2017) was able to acquire imagery with 10 nm spectral (220 bands) at 30 m spatial resolutions over 1424.5 km2 scenes. Conversely, the widespread unmanned airborne vehicle (UAV) hyperspatial DJI Mavic Pro camera can collect only natural-coloured imagery of 100 nm spectral (3 bands) but at 0.1 m spatial resolution over ∼10 km2 scenes (with a single battery and calm meteo-marine conditions). The spaceborne WorldView-3 (WV3), featured by 60 nm spectral (16 bands) at 0.3 m spatial resolution (when pansharpened) over 1489.6 km2 scenes, has the capacity to bridge both sensors. This study aims at testing the spectral and spatial performances of the WV3 to discriminate 10 complex coastal classes, ranging from ocean, reefs and terrestrial vegetation in Moorea Island (French Polynesia). Our findings show that geometrically- and radiometrically-corrected 0.3-m 16-band WV3 bands competed with (30-m) 167-band Hyperion performance for classifying 10 coastal classes with 2-neuron artificial neural network modelling, while being able to segment objects seized by 0.1-m (3-band) UAV. Unifying superspectral and hyperspatial specificities, the WV3 also leverages hypertemporal resolution, that is to say 1-day temporal resolution, rivalling UAV’s one.

Identification of Ramularia Leaf Blight Cotton Disease Infection Levels by Multispectral, Multiscale UAV Imagery

The reduction of the production cost and negative environmental impacts by pesticide application to control cotton diseases depends on the infection patterns spatialized in the farm scale. Here, we evaluate the potential of three-band multispectral imagery from a multi-rotor unmanned airborne vehicle (UAV) platform for the detection of ramularia leaf blight from different flight heights in an experimental field. Increasing infection levels indicate the progressive degradation of the spectral vegetation signal, however, they were not sufficient to differentiate disease severity levels. At resolutions of ~5 cm (100 m) and ~15 cm (300 m) up to a ground spatial resolution of ~25 cm (500 m flight height), two-scaled infection levels can be detected for the best performing algorithm of four classifiers tested, with an overall accuracy of ~79% and a kappa index of ~0.51. Despite limited classification performance, the results show the potential interest of low-cost multispectral systems to monitor ramularia blight in cotton.

Autonomous Flight Take-off in Flapping Wing Aerial Vehicles

This paper presents the design and dynamic simulation of a jumping mechanism for flight initiation in flapping wing aerial vehicles to enhance their autonomous mobility. It is inspired by avian flyers that start flight by jumping using their hind limbs. A 4-bar linkage that performs the prescribed take-off maneuvers has been geometrically designed using dimensional synthesis by motion generation. The kinematic dimensions obtained thereof have been ascertained analytically. A magnetic latching solenoid actuator and its corresponding transmission mechanism has been proposed for jumping actuation due to its compact structure, and low power consumption with no heat nor electrical noise generation. After take-off, the necessity to sustain the aerial vehicle airborne by providing adequate supportive forces at low air speeds has been demonstrated by the prospect of unsteady aerodynamics. Fluid-structure interaction has been analyzed by co-simulation between ADAMSⓇ and MATLABⓇ/Simulink. The designed legs give an inclined take-off of about 64° and an initial speed of almost 2m/s with an angular deflection of 110° between the leg segments. Flight performance indicates an increase in lift/drag ratios with in both flapping rate and forward velocity up to some limit. The results also compared favorably with those from wind tunnel tests and previous analysis of related work. They all exhibited an increase in wing efficiency with decreasing mean angles of attack as the air vehicle approaches stable flight.

Opportunistic Spectrum Access for UAV Communications Towards Ultra Dense Networks

The growing popularity of unmanned aerial vehicle (UAV) attracts significant research interests and applications including low-altitude and airborne vehicles. Since there is no declared spectrum allocated to UAV communications, opportunistic transmission has been commonly considered as an important way for supporting UAV communications. When sharing the same spectrum with other users such as satellites and mobile base stations, accurate spectrum sensing and allocation are of critical importance for UAV communications to avoid serious interference. As the UAVs can constantly move to different locations with various spectrum environments, the spectrum decision may be invalid only in a short period, leading to require fast spectrum sensing. Furthermore, an UAV needs to predict possible temporal and spatial vacations of the spectrum. In this case, the spectrum prediction has a high dimensional state space which is notoriously difficult to solve. In this paper, some other issues such as how to determine the spectrum processing time and how to detect the primary signals with high priority to avoid interference, are also discussed. Finally, a fast spectrum sensing algorithm is proposed to improve the energy detection performance by optimizing the error estimation and a constant ratio of missed detection. Our proposed algorithm does not require high computational capability and can achieve relatively accurate sensing in low signal-to-noise ratio scenarios.

Određivanje pozicije akustičkih izvora korišćenjem spektralne analize višeg reda za određivanje vremena nailaska signala

The localization of various acoustic sources in a battlefield (such as weapon rounds, mortars, rockets, mines, improvised explosive devices, vehicle-borne improvised explosive devices and airborne vehicles) nowadays has a significant history. In acoustic source localization systems of multiple sensors, networked and placed at known positions are used to detect signals emitted from the source and perform localization of the source. Time of arrival estimation of the gun fire shock waves at large distances is significant when the purpose is the gun localization. At large distances shock wave signal is significantly deformed and therefore it is relatively difficult to accurately estimate the time of arrival. In this paper methods for TOA estimation are proposed, which are based on cumulants of the acoustic signal which originate from distant gunfire events. Localization of acoustic sources is performed in two steps by time difference estimation of acoustic signal arrival and using Discrete Probability Density method for positioning. Numerous field experiments have been conducted in order to verify performance of the proposed approach.

Laser propagation transmission properties characteristics between airborne communication terminal and unmanned aerial vehicle target in complex atmospheric background

Clouds, aerosols and atmospheric molecules are major components of the atmosphere. In the fields of atmospheric physics such as target detection, wireless optical communication and remote sensing, these atmospheric components have a strong attenuation effect on laser transmission. Based on the successive scattering method for solving the radiative transfer equation, the laser transmission model between airborne wireless optical communication terminal and ground-to-air unmanned aerial vehicle (UAV) target in complex atmospheric background is established in this paper. Considering the fact that cirrus cloud, atmospheric molecules and aerosols exist in the real atmospheric background, the variations of direct transmission power, first-order scattering transmission power of 1.55 μm laser emitted by the airborne wireless optical communication terminal with UAV target height are calculated numerically under complex atmospheric background. The effects of the aircraft located at different locations, effective radius of ice crystal particles in cirrus cloud, as well as the horizontal distance between the aircraft and UAV target on received laser transmission power are also analyzed. In the first three examples (i.e., aircraft is above, below, and inside cirrus cloud), laser direct transmission power (LDTP) is much larger than first-order scattering transmission power (FSTP); when the UAV target rises into the cloud, the FSTP is significantly enhanced as a result of the effect of diffraction light. The fourth example is for calculating the variations of LDTP and FSTP with UAV target height for different effective radii of ice crystals. The results show that the LDTP decreases with the increase of effective radius, whereas the FSTP presents an opposite scenario. The fifth example is for calculating the variations of LDTP and FSTP with UAV target height for different horizontal distances. The results show that the LDTP and FSTP decrease with the increase of the horizontal distance, which is obviously realistic. In summary, it is concluded that the laser transmitted power through cirrus clouds is strongly dependent on aircraft position: above, below, or inside cirrus cloud; the horizontal distance between the aircraft and UVA target, and effective radii of ice crystals have great influences on LDTP and FSTP. Compared with the atmosphere above the clouds, the molecules and aerosols below the clouds make the laser power have a strong attenuation. The results given in this paper provide theoretical support for further studying the laser communication experiment in ground-to-air links, UAV formation, command and networking technology in complex atmospheric background.

DESIGN AND IMPLEMENTATION OF NONLINEAR PID CONTROLLER FOR A QUADROTOR CONTROL

The following article represents the control of an unmanned airborne vehicle (Quadcopter), using nonlinear PID controllers in order to control the altitude, as well as the attitudes (pitch, roll and yaw) of the Quadcopter. Two approaches have been proposed for adjusting the parameters of a PID controller. Foremost, the PID controller gains are settled in an ideal way by using a reference model strategy. In the moment approach, these parameters are adjusted Nonlinear PID. MATLAB/Simulink has been utilized to test and compare the execution of the controllers gotten. The obtained results using the nonlinear PID controllers show the efficiency of the proposed controllers it present a response with less error and minimal over shoot compared to the results of classical PID controller.

Comparative assessment of structural indicators of Ukraine industry and the European Union

A comparative analysis of the structural advantages of the industry of Ukraine and the EU member states in terms of the share of industry in: output of the economy, gross value added of the economy, exports of airborne vehicles, as well as the efficiency indicator (the share of airborne emissions in the industry). The place of Ukraine among EU member states is determined on the set of relative and absolute indicators of functioning of the industrial sector of the economy. A detailed comparative estimation of the structure of the airborne assets of the industry of Ukraine and Poland was conducted.

IMPACT FORCE OF FLOOD-BORNE VEHICLES

Tsunami, hurricane storm surge, and waves generate debris such as shipping containers, wood logs, and vehicles. Impact forces exerted on structures in the inundation zone by such debris might result in severe structural damage of structures. Thus, reliable prediction of debris impact force is essential for the safe design and risk assessment of structures in the inundation zone. In this study, we carried out full-scale air-borne and flood-borne vehicle impact experiments. The experimental results enable characterization of the vehicle impact and prove the applicability of a theoretical equation (Haehnel and Daly, (2004)) in which the impact force of debris is estimated by using the impact velocity, axial stiffness, and mass of the debris. In addition, by analyzing NHTSA (National Highway Traffic Safety Administration)’s experimental data, a list of axial stiffness for various types of vehicles was constructed, which is important in predicting the flood-borne vehicle impact force.

A Comparison of Stateless Position-based Packet Routing Algorithms for FANETs

Scalable routing for wireless communication systems is a compelling and challenging task. To this aim, routing algorithms exploiting geographic information have been proposed. These algorithms refer to nodes by their location, rather than their address, and use those coordinates to route greedily towards a destination. With the advent of unmanned airborne vehicle (UAV) technology, a lot of research effort has been devoted to extend position-based packet routing proposals to three dimensional environments. In this context, Flying Ad-hoc Networks (FANETs), comprised of autonomous flying vehicles, pose several issues. This work focuses on the state-of-the-art, stateless geographic packet routing protocols conceived or adapted for three-dimensional network scenarios. Proposals are evaluated over a common scenario through a comprehensive comparative analysis.

A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos

Multi-Object Tracking (MOT) in airborne videos is a challenging problem due to the uncertain airborne vehicle motion, vibrations of the mounted camera, unreliable detections, changes of size, appearance and motion of the moving objects and occlusions caused by the interaction between moving and static objects in the scene. To deal with these problems, this work proposes a four-stage hierarchical association framework for multiple object tracking in airborne video. The proposed framework combines Data Association-based Tracking (DAT) methods and target tracking using a compressive tracking approach, to robustly track objects in complex airborne surveillance scenes. In each association stage, different sets of tracklets and detections are associated to efficiently handle local tracklet generation, local trajectory construction, global drifting tracklet correction and global fragmented tracklet linking. Experiments with challenging airborne videos show significant tracking improvement compared to existing state-of-the-art methods.

Design of a New Non-Singular Robust Control Using Synergetic Theory for DC-DC Buck Converter

DOI: 10.26650/electrica.2018.03052 DC-DC converters control has gained much attention because of their broad uses in various fields, ranging from hand-held calculators to sophisticated airborne vehicles. Robustness in control systems, in spite of parametric variations, is an absolute requirement in many such applications. We propose a new controller to realize a robust performance despite the uncertainties on system parameter values. The controller employs an adaptive non-singular finite-time synergetic control method to tackle disturbances, which enhances the robustness and enables better performance during the transient phase compared to the terminal sliding mode control. A finite-time convergence is therefore achieved, while Lyapunov synthesis guarantees stability. Extensive simulation results of the DC-DC converter under harsh operating conditions confirm the effectiveness of the proposed controller.

Monitoring river morphology & bank erosion using UAV imagery – A case study of the river Buëch, Hautes-Alpes, France

River morphology dynamics and river bank erosion were mapped using multi-temporal images acquired in June 2014 and June 2015 by an Unmanned Airborne Vehicle (UAV). The selected study sites are located in two dynamic parts of the floodplain of the river Buëch in the Hautes-Alpes province in south-eastern France. The images were processed using the Structure from Motion algorithm into high spatial resolution OrthoMosaics of 5 cm pixel size and DEMs (Digital Elevation Model) of 10 cm pixel size. The positional and vertical accuracy of the UAV products were evaluated using Real Time Kinematic GPS (RTK-GPS) points measurements of markers laid out in the floodplain during image acquisition. Obtained accuracies are centimeters to decimeters. River morphology such as channel displacements, gravel bank displacement and avulsions were evaluated using the OrthoMosaics. The Buëch river shows mainly braided river properties but at locations some meandering river properties were observed. Bank erosion volume calculations were made by comparing the high spatial resolution DEMs of 2014 and 2015. Accuracy of bank erosion assessment was evaluated using RTK-GPS transects of known sites of bank erosion. Bank retreat could be mapped at centimeter to decimeter detail but sometimes hampered by overhanging vegetation, water glitter and shadows. Our conclusions are that time-series of high spatial resolution UAV images can be acquired in a flexible and easy way, the individual images can nowadays be processed in a straightforward way into suitable products i.e. OrthoMosaics and DEMs which are valuable products for land administrators having a responsibility to survey and monitor rivers and control them. Accuracy of the UAV products is high in XYZ direction and sufficient for river monitoring purposes and for designing management measures.

Addressing uncertainties in interpreting soil surface changes by multitemporal high‐resolution topography data across scales

AbstractExtensive amounts of water erosion combined with the magnitude of on‐site and off‐site impacts have led to considerable reduction in soil fertility and increased production costs in agriculture. Digital elevation models are a useful and established tool to better understand surface processes and to quantify damages. Ongoing developments in camera‐based 3D reconstruction allow non‐expert users to produce high‐quality elevation models. Multitemporal surveys allow geomorphic change detection serving as a valuable tool for geomorphologists and erosion researchers. Despite various benefits, these recent developments are accompanied by novel challenges in the form of small‐scale nonerosive surface processes (e.g., swelling/shrinking, consolidation/compaction, and aggregate breakdown). If neglected, these alterations can sum up to distinct errors in soil loss quantification.However, as yet, there have been no studies discussing their influence on surface data sets in erosion research. We present an across‐scales approach of visualising and quantifying detailed soil physical changes and their influence on surface morphology at submillimetre resolution.The data sets were acquired at field scale from an unmanned airborne vehicle, at plot scale during an artificial rainfall simulation on an agricultural site, and at microplot scale in a laboratory set‐up. Resulting high‐precision data sets enable the desired insights in soil movements and surface alterations without preceding particle transport and soil loss. Surface changes sum up to 260 m3/ha on an Andalusian test site and could be falsely interpreted as soil loss (of 286 t/ha). These results recommend cautious interpretation of high‐resolution topography in soil erosion research.

Technical Report: Unmanned Helicopter Solution for Survey-Grade Lidar and Hyperspectral Mapping

Recent development of light-weight unmanned airborne vehicles (UAV) and miniaturization of sensors provide new possibilities for remote sensing and high-resolution mapping. Mini-UAV platforms are emerging, but powerful UAV platforms of higher payload capacity are required to carry the sensors for survey-grade mapping. In this paper, we demonstrate a technological solution and application of two different payloads for highly accurate and detailed mapping. The unmanned airborne system (UAS) comprises a Scout B1-100 autonomously operating UAV helicopter powered by a gasoline two-stroke engine with maximum take-off weight of 75 kg. The UAV allows for integrating of up to 18 kg of a customized payload. Our technological solution comprises two types of payload completely independent of the platform. The first payload contains a VUX-1 laser scanner (Riegl, Austria) and a Sony A6000 E-Mount photo camera. The second payload integrates a hyperspectral push-broom scanner AISA Kestrel 10 (Specim, Finland). The two payloads need to be alternated if mapping with both is required. Both payloads include an inertial navigation system xNAV550 (Oxford Technical Solutions Ltd., United Kingdom), a separate data link, and a power supply unit. Such a constellation allowed for achieving high accuracy of the flight line post-processing in two test missions. The standard deviation was 0.02 m (XY) and 0.025 m (Z), respectively. The intended application of the UAS was for high-resolution mapping and monitoring of landscape dynamics (landslides, erosion, flooding, or crops growth). The legal regulations for such UAV applications in Switzerland and Slovakia are also discussed.

Monitoring height and greenness of non-woody floodplain vegetation with UAV time series

Vegetation in river floodplains has important functions for biodiversity, but can also have a negative influence on flood safety. Floodplain vegetation is becoming increasingly heterogeneous in space and time as a result of river restoration projects. To document the spatio-temporal patterns of the floodplain vegetation, the need arises for efficient monitoring techniques. Monitoring is commonly performed by mapping floodplains based on single-epoch remote sensing data, thereby not considering seasonal dynamics of vegetation. The rising availability of unmanned airborne vehicles (UAV) increases monitoring frequency potential. Therefore, we aimed to evaluate the performance of multi-temporal high-spatial-resolution imagery, collected with a UAV, to record the dynamics in floodplain vegetation height and greenness over a growing season. Since the classification accuracy of current airborne surveys remains insufficient for low vegetation types, we focussed on seasonal variation of herbaceous and grassy vegetation with a height up to 3 m. Field reference data on vegetation height were collected six times during one year in 28 field plots within a single floodplain along the Waal River, the main distributary of the Rhine River in the Netherlands. Simultaneously with each field survey, we recorded UAV true-colour and false-colour imagery from which normalized digital surface models (nDSMs) and a consumer-grade camera vegetation index (CGCVI) were calculated. We observed that: (1) the accuracy of a UAV-derived digital terrain model (DTM) varies over the growing season and is most accurate during winter when the vegetation is dormant, (2) vegetation height can be determined from the nDSMs in leaf-on conditions via linear regression (RSME = 0.17–0.33 m), (3) the multitemporal nDSMs yielded meaningful temporal profiles of greenness and vegetation height and (4) herbaceous vegetation shows hysteresis for greenness and vegetation height, but no clear hysteresis was observed for grassland vegetation. These results show the high potential of using UAV-borne sensors for increasing the classification accuracy of low floodplain vegetation within the framework of floodplain monitoring.

(Invited) Electrochemical Generation of Fuels: Matching Research and Application for Advanced Water Splitting and Other Technologies

Electrochemistry is becoming increasingly important in transitioning from primarily fossil fuel based energy sources to more renewable options. This challenge will require a combination of solutions, depending on geography, the mix of renewables, and other factors. The intermittent nature of wind, solar, and other forms of renewable energy, as well as demand fluctuations which do not match the generation capacity, drives the need for modular, distributed energy storage solutions, where electrochemistry can be ideal. However, for very long storage times, conversion of energy to a chemical fuel is often the most practical solution. Electrochemical generation of fuels such as hydrogen, ammonia, and CO2-derived hydrocarbons are all related and have similar R&D challenges. In addition, all of these chemicals have different advantages and disadvantages, and have benefits in different scenarios. This talk will focus on some of the considerations in developing a new electrochemical device, and research challenges applicable to low temperature electrochemical fuel generation. While fundamental research in understanding electrocatalytic reactions at the molecular level is valuable from a basic science perspective, understanding the application requirements for each market, and pricing structure vs. scale, can guide application of this research to the next logical stage. There is a large application space for fuels and industrial chemicals with widely varying price points based on scale and requirements. For example, different ground vehicle classes (consumer vehicles, heavy duty trucks, fork trucks, industrial equipment etc.,) may each be best served by different fuels depending on power and range requirements as well as customer preferences. Ships and airborne vehicles may have different optimal solutions. Smaller scale or emerging markets such as unmanned vehicles may also serve as easier market entry points. At the materials discovery stage, all of the above reactions require catalyst design and fundamental understanding in order to achieve high activity and efficiency. Specifically for ammonia and carbon-based fuels, selectivity is a key issue, and structural approaches to control the active site and competition for binding sites are being pursued. Beyond the catalyst, the electrode structure and integration also need to be designed for optimal performance, including effective fluid flow and catalyst access. While the individual catalyst composition and structures will be different, all of these pathways involve hydrogen or oxygen evolution reactions and ion exchange membranes, and can both leverage and inform electrolysis research. Proton’s work in these areas will be discussed, as well as key needs for additional research and collaborations between applied and fundamental science.

Improving the Positional Accuracy of the Airborne Vehicle during Its Motion along the Predetermined Path

The method of improving the positional accuracy of the airborne vehicle that moves along a great circle path is considered due to the analytical three-dimensional projection of its current coordinate position, determined from the measurements of the satellite navigation system under the conditions of high-amplitude noise to the true guide path.

Radiometric Correction of Close-Range Spectral Image Blocks Captured Using an Unmanned Aerial Vehicle with a Radiometric Block Adjustment

Unmanned airborne vehicles (UAV) equipped with novel, miniaturized, 2D frame format hyper- and multispectral cameras make it possible to conduct remote sensing measurements cost-efficiently, with greater accuracy and detail. In the mapping process, the area of interest is covered by multiple, overlapping, small-format 2D images, which provide redundant information about the object. Radiometric correction of spectral image data is important for eliminating any external disturbance from the captured data. Corrections should include sensor, atmosphere and view/illumination geometry (bidirectional reflectance distribution function—BRDF) related disturbances. An additional complication is that UAV remote sensing campaigns are often carried out under difficult conditions, with varying illumination conditions and cloudiness. We have developed a global optimization approach for the radiometric correction of UAV image blocks, a radiometric block adjustment. The objective of this study was to implement and assess a combined adjustment approach, including comprehensive consideration of weighting of various observations. An empirical study was carried out using imagery captured using a hyperspectral 2D frame format camera of winter wheat crops. The dataset included four separate flights captured during a 2.5 h time period under sunny weather conditions. As outputs, we calculated orthophoto mosaics using the most nadir images and sampled multiple-view hyperspectral spectra for vegetation sample points utilizing multiple images in the dataset. The method provided an automated tool for radiometric correction, compensating for efficiently radiometric disturbances in the images. The global homogeneity factor improved from 12–16% to 4–6% with the corrections, and a reduction in disturbances could be observed in the spectra of the object points sampled from multiple overlapping images. Residuals in the grey and white reflectance panels were less than 5% of the reflectance for most of the spectral bands.

Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft

Climate-related extended outbreaks and range shifts of destructive bark beetle species pose a serious threat to urban boreal forests in North America and Fennoscandia. Recent developments in low-cost remote sensing technologies offer an attractive means for early detection and management of environmental change. They are of great interest to the actors responsible for monitoring and managing forest health. The objective of this investigation was to develop, assess, and compare automated remote sensing procedures based on novel, low-cost hyperspectral imaging technology for the identification of bark beetle infestations at the individual tree level in urban forests. A hyperspectral camera based on a tunable Fabry-Pérot interferometer was operated from a small, unmanned airborne vehicle (UAV) platform and a small Cessna-type aircraft platform. This study compared aspects of using UAV datasets with a spatial extent of a few hectares (ha) and a ground sample distance (GSD) of 10–12 cm to the aircraft data covering areas of several km2 and having a GSD of 50 cm. An empirical assessment of the automated identification of mature Norway spruce (Picea abies L. Karst.) trees suffering from infestation (representing different colonization phases) by the European spruce bark beetle (Ips typographus L.) was carried out in the urban forests of Lahti, a city in southern Finland. Individual spruces were classified as healthy, infested, or dead. For the entire test area, the best aircraft data results for overall accuracy were 79% (Cohen’s kappa: 0.54) when using three crown color classes (green as healthy, yellow as infested, and gray as dead). For two color classes (healthy, dead) in the same area, the best overall accuracy was 93% (kappa: 0.77). The finer resolution UAV dataset provided better results, with an overall accuracy of 81% (kappa: 0.70), compared to the aircraft results of 73% (kappa: 0.56) in a smaller sub-area. The results showed that novel, low-cost remote sensing technologies based on individual tree analysis and calibrated remote sensing imagery offer great potential for affordable and timely assessments of the health condition of vulnerable urban forests.