Applications Of Unmanned Aerial Systems Research Articles

On-the-Fly Olive Tree Counting Using a UAS and Cloud Services

Unmanned aerial systems (UAS) are becoming a common tool for aerial sensing applications. Nevertheless, sensed data need further processing before becoming useful information. This processing requires large computing power and time before delivery. In this paper, we present a parallel architecture that includes an unmanned aerial vehicle (UAV), a small embedded computer on board, a communication link to the Internet, and a cloud service with the aim to provide useful real-time information directly to the end-users. The potential of parallelism as a solution in remote sensing has not been addressed for a distributed architecture that includes the UAV processors. The architecture is demonstrated for a specific problem: the counting of olive trees in a crop field where the trees are regularly spaced from each other. During the flight, the embedded computer is able to process individual images on board the UAV and provide the total count. The tree counting algorithm obtains an F 1 score of 99.09 % for a sequence of ten images with 332 olive trees. The detected trees are geolocated and can be visualized on the Internet seconds after the take-off of the flight, with no further processing required. This is a use case to demonstrate near real-time results obtained from UAS usage. Other more complex UAS applications, such as tree inventories, search and rescue, fire detection, or stock breeding, can potentially benefit from this architecture and obtain faster outcomes, accessible while the UAV is still on flight.

Monitoring opencast mine restorations using Unmanned Aerial System (UAS) imagery

Open-pit mine is still an unavoidable activity but can become unsustainable without the restoration of degraded sites. Monitoring the restoration after extractive activities is a legal requirement for mine companies and public administrations in many countries, involving financial provisions for environmental liabilities. The objective of this contribution is to present a rigorous, low-cost and easy-to-use application of Unmanned Aerial Systems (UAS) for supporting opencast mining and restoration monitoring, complementing the inspections with very high (<10 cm) spatial resolution multispectral imagery, and improving any restoration documentation with detailed land cover maps. The potential of UAS as a tool to control restoration works is presented in a calcareous quarry that has undergone different post-mining restoration actions in the last 20 years, representing 4 reclaimed stages. We used a small (<2 kg) drone equipped with a multispectral sensor, along with field spectroradiometer measurements that were used to radiometrically correct the UAS sensor data. Imagery was processed with photogrammetric and Remote Sensing and Geographical Information Systems software, resulting in spectral information, vegetation and soil indices, structural information and land cover maps. Spectral data and land cover classification, which were validated through ground-truth plots, aided in the detection and quantification of mine waste dumping, bare soil and other land cover extension. Moreover, plant formations and vegetation development were evaluated, allowing a quantitative, but at the same time visual and intuitive comparison with the surrounding reference systems. The protocol resulting from this research constitutes a pipeline solution intended for the implementation by public administrations and privates companies for precisely evaluating restoration dynamics in an expedient manner at a very affordable budget. Furthermore, the proposed solution prevents subjective interpretations by providing objective data, which integrate new technologies at the service of scientists, environmental managers and decision makers.

Species-Level Vegetation Mapping in a Himalayan Treeline Ecotone Using Unmanned Aerial System (UAS) Imagery

Understanding ecological patterns and response to climate change requires unbiased data on species distribution. This can be challenging, especially in biodiverse but extreme environments like the Himalaya. This study presents the results of the first ever application of Unmanned Aerial Systems (UAS) imagery for species-level mapping of vegetation in the Himalaya following a hierarchical Geographic Object Based Image Analysis (GEOBIA) method. The first level of classification separated green vegetated objects from the rest with overall accuracy of 95%. At the second level, seven cover types were identified (including four woody vegetation species). For this, the suitability of various spectral, shape and textural features were tested for classifying them using an ensemble decision tree algorithm. Spectral features alone yielded ~70% accuracy (kappa 0.66) whereas adding textural and shape features marginally improved the accuracy (73%) but at the cost of a substantial increase in processing time. Contrast in plant morphological traits was the key to distinguishing nearby stands as different species. Hence, broad-leaved versus fine needle leaved vegetation were mapped more accurately than structurally similar classes such as Rhododendron anthopogon versus non-photosynthetic vegetation. Results highlight the potential and limitations of the suggested UAS-GEOBIA approach for detailed mapping of plant communities and suggests future research directions.

Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity

From our traditional boat-based horizontal perspective, marine megafauna behavioral observations are typically limited to animal surfacings. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noisy and risky. The emergence of commercial small unmanned aerial systems (UAS) has significantly reduced these constraints, and provide a stable, relatively quiet and inexpensive platform that enables replicate observations for prolonged periods with minimal disturbance. The potential of UAS for behavioral observation appears immense, yet quantitative methods of video analysis and proof of utility as an observational tool are required. We use UAS footage of gray whales foraging in coastal waters of Oregon, USA to develop analysis methods, assess behavioral impacts caused by UAS, determine the change in observation time enabled by UAS, and describe unique behaviors observed via UAS. Boat-based behavioral observations from 53 gray whale sightings between May and October 2016 were compared to behavioral data extracted from video analysis of UAS flights during those sightings. We used a DJI Phantom 3 Pro or 4 Advanced, recorded video from an altitude ≥25m, and detected no behavioral response by whales to the UAS. Two experienced whale ethologists conducted UAS video behavioral analysis, including tabulation of whale behavior states and events, and whale surface time and whale visible time (total time the whale was visible including underwater). UAS provided three times more observational capacity than boat-based observations alone (300 vs. 103 minutes). When observation time is accounted for, UAS data provided greater observations of all primary behavior states (travel, forage, social, rest) relative to boat-based data, especially forage, which increased by three times. Furthermore, UAS enable documentation of multiple novel gray whale foraging tactics (e.g., headstands: n=58; side-swimming: n=17; jaw snapping and flexing: n= 10) and 33 social events (nursing, pair coordinated surfacings) not identified in the field. This study demonstrates the significant added value of UAS to marine megafauna behavior and ecological studies. With technological advances, robust study designs, and effective analytical tools, we foresee increased UAS applications to marine megafauna studies to elucidate foraging strategies, habitat associations, social patterns, and response to human disturbance.

Use of a Value Model to Ethically Govern Various Applications of Small UAS

Widespread use of small unmanned aircraft systems is becoming prominent in the US. From structural health monitoring to journalism, small unmanned aerial systems (sUAS) are allowing people to gain a view of their surroundings and conduct their jobs in ways like never before. With this come many ethical concerns that must be addressed before the sight of a sUAS flying overhead is a widely acceptable occurrence to a majority of the population. Currently, UAS operations used in civil airspace are governed by the Federal Aviation Administration (FAA) Part 107 rules, but these regulations do not address certain ethical considerations. This paper will use the concept of a value model to quantify these ethical concerns so that they may be encoded into the design of a UAS and evaluation of missions before the missions are conducted. This could prove valuable in addressing the ethical challenges that are faced when implementing unmanned aerial systems (UAS) operations into the airspace, especially when UASs are in airspace in densely populated areas.

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

ABSTRACTSpatially distributed high-resolution data of land surface temperature (LST) and evapotranspiration (ET) are important information for crop water management and other applications in the agricultural sector. While satellite data can provide LST high-resolution data of 100 m, the current development of unmanned aerial systems (UAS) and affordable low-weight thermal cameras allows LST and subsequent ET to be derived at resolutions down to centimetre scale.In this study, UAS-based images in the thermal infrared (TIR) and visible spectral range were collected over a managed temperate grassland in July 2016 at the Terrestrial Environmental Observatories Networks TERENO preAlpine observatory site at Fendt, Germany. The UAS set-up included a lightweight thermal camera (Optris Pi Lightweight) and a regular digital camera (Sony α 6000) that allowed for the acquisition of thermal and optical images with a ground resolution of 5 cm and 1 cm, respectively. Three TIR-based ET models of different complexity were applied and the resulting ET estimates were compared to the Eddy covariance (EC) observations of turbulent energy fluxes and also to the evaporative fraction. While the Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature (DATTUTDUT) model and the Triangle Method belong to the group of simpler contextual models, the Two-Source Energy Balance (TSEB) model incorporates a more physically based formulation of the surface energy balance. In addition to the comparison of UAS-based estimates of latent heat fluxes to EC observations, the effect of the spatial resolution of the model imagery input on the modelled results was analysed by running the models with imagery from the native resolution of the acquired images to resolutions that were aggregated up to 30 m.The results show that both contextual models are sensitive to the input image resolution and that the agreement with the EC observations improves with increasing image resolution. The TSEB model assumes that LST pixels represent a mixed signal of the soil and canopy components, thus an image resolution coarse enough to ensure this assumption should be chosen. However, with the exception of the native image resolution of 5 cm, we found no effect of image resolution on the spatially weighted mean TSEB estimates.For the studied grassland, the comparison of model estimates with EC observations indicates that all three models are able to reproduce observed energy fluxes with comparable accuracy with mean absolute errors of ET between 20 and 40 W m−2. The TSEB model showed larger deviations from the reference observations under cloudy conditions with rapid fluctuations of LST within the 30 min averaging period for EC. The two contextual models yielded similar results for most of the flights. The good performance of the DATTUTDUT model, which had the lowest input requirements of the three models, is especially promising in view of the application of UAS for routine near-real-time ET monitoring.

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments

Although sea turtles face significant pressure from human activities, some populations are recovering due to conservation programs, bans on the trade of turtle products, and reductions in bycatch. While these trends are encouraging, the status of many populations remains unknown and scientific monitoring is needed to inform conservation and management decisions. To address these gaps, this study presents methods for using unmanned aerial systems (UAS) to conduct population assessments. Using a fixed-wing UAS and a modified strip-transect method, we conducted aerial surveys along a three-kilometer track line at Ostional, Costa Rica during a mass-nesting event of olive ridley turtles (Lepidochelys olivacea). We visually assessed images collected during six transects for sea turtle presence, resulting in 682 certain detections. A cumulative total of 1091 certain and probable turtles were detected in the collected imagery. Using these data, we calculate estimates of sea turtle density (km−2) in nearshore waters. After adjusting for both availability and perception biases, we developed a low-end estimate of 1299 ± 458 and a high-end estimate of 2086 ± 803 turtles km−2. This pilot study illustrates how UAS can be used to conduct robust, safe, and cost-effective population assessments of sea turtle populations in coastal marine ecosystems.

Applications and Issues of Unmanned Aerial Systems in the Construction Industry

The adoption of innovative technologies in the construction industry is necessary for the industry development. Such technologies can help in reducing the time needed to accomplish tasks, increase work quality, improve safety standards, and lower expenses. Unmanned aerial systems (UAS) have various applications on construction sites. They provide a bird’s eye view for supervising construction site personnel as well as providing live feedback on actions taking place on-site. Given the high potential of UAS use in the construction industry and their recent wide usage, this study and literature review aims to summarize the current applications of UAS on construction sites. Furthermore, it will also identify the issues resulting from UAS use in the construction industry. The findings will enhance understanding of the implementation of UAS in the construction industry.

Analysis of Autonomous Unmanned Aerial Systems Based on Operational Scenarios Using Value Modelling

In recent years, the use of UAS (Unmanned Aerial Systems) has moved beyond the realm of military operations and has made its way into the hands of consumers and commercial industries. Although the applications of UAS in commercial industries are virtually endless, there are many issues regarding their operations that need to be considered before these valuable pieces of equipment are allowed for widespread civil use. Currently, UAS operations in the public domain are guided and controlled by the FAA Part 107 rules after overwhelming public pressure caused by the earlier 333 exemption. In order to approach such larger issues, this paper will exploit the use of value models, which will help to quantify how the different environmental and operational scenarios play a role in UAS operations based on the task being performed. The primary aim of this research is to use the attributes from key factors of the UAS such as the autonomy levels (AL) and technology readiness levels (TRL) along with their operating scenario factors, such as the environmental complexity and task complexity, based on the operating environment in which a UAS performs its task. To analyze the performance of autonomous UAS in different operational scenarios, the physical characteristics and class of a UAS may be linked to its AL and TRL. Using these parameters, the risks faced by the UAS in a particular mission are quantified and a value is assigned to the abstract entities involved. Although there are many critical questions with respect to good practices to be followed by UAS operators in order to obtain valuable data and information on the structures being scanned and monitored, there are many other challenges with regards to large scale operations of UAS such as the ethical, legal and societal implications that have to be addressed.

Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments

Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments

Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries.

BackgroundLow cost unmanned aerial systems (UAS) have great potential for rapid proximal measurements of plants in agriculture. In the context of plant breeding and genetics, current approaches for phenotyping a large number of breeding lines under field conditions require substantial investments in time, cost, and labor. For field-based high-throughput phenotyping (HTP), UAS platforms can provide high-resolution measurements for small plot research, while enabling the rapid assessment of tens-of-thousands of field plots. The objective of this study was to complete a baseline assessment of the utility of UAS in assessment field trials as commonly implemented in wheat breeding programs. We developed a semi-automated image-processing pipeline to extract plot level data from UAS imagery. The image dataset was processed using a photogrammetric pipeline based on image orientation and radiometric calibration to produce orthomosaic images. We also examined the relationships between vegetation indices (VIs) extracted from high spatial resolution multispectral imagery collected with two different UAS systems (eBee Ag carrying MultiSpec 4C camera, and IRIS+ quadcopter carrying modified NIR Canon S100) and ground truth spectral data from hand-held spectroradiometer.ResultsWe found good correlation between the VIs obtained from UAS platforms and ground-truth measurements and observed high broad-sense heritability for VIs. We determined radiometric calibration methods developed for satellite imagery significantly improved the precision of VIs from the UAS. We observed VIs extracted from calibrated images of Canon S100 had a significantly higher correlation to the spectroradiometer (r = 0.76) than VIs from the MultiSpec 4C camera (r = 0.64). Their correlation to spectroradiometer readings was as high as or higher than repeated measurements with the spectroradiometer per se.ConclusionThe approaches described here for UAS imaging and extraction of proximal sensing data enable collection of HTP measurements on the scale and with the precision needed for powerful selection tools in plant breeding. Low-cost UAS platforms have great potential for use as a selection tool in plant breeding programs. In the scope of tools development, the pipeline developed in this study can be effectively employed for other UAS and also other crops planted in breeding nurseries.

Atmosphere effects on sonar sensor model for UAS applications

The use of Unmanned Aerial System (UAS) applications is growing in both civilian and military fields. Fully autonomous UAS applications are useful to a variety of disciplines; for example, they can provide structural damage inspections in critical or dangerous areas (e.g. the L'Aquila earthquake in Italy, or Hurricane Ike in Galveston, Texas, USA). However, in some conditions, such as urban or low altitude operations, the Global Navigation Satellite System (GNSS) receiver antenna is prone to losing the line-of-sight from the satellite, making GNSS unable to deliver high quality positon information. This is quite dangerous for closed-loop control systems during the landing phase. In these cases, an ultrasonic sensor may be very useful for altitude control during the vehicle landing.

Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations

Abstract. Detailed information on the spatiotemporal snow depth distribution is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Today, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network like the one in Switzerland, with more than one measurement station per 10 km2 on average, is not able to capture the large spatial variability of snow depth present in alpine terrain.Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, in most countries such data acquisition is costly if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UASs), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Compared to manual measurements, such systems are relatively cost-effective and can be applied very flexibly to cover terrain not accessible from the ground. In this study, we map snow depth at two different locations: (a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and (b) an exposed location on a peak (2500 m a.s.l.) in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) of less than 0.07 to 0.15 m on meadows and rocks and a RMSE of less than 0.30 m on sections covered by bushes or tall grass, compared to manual probe measurements. This new measurement technology opens the door for efficient, flexible, repeatable and cost-effective snow depth monitoring over areas of several hectares for various applications, if the national and regional regulations permit the application of UASs.

What can unmanned aerial systems offer healthcare?

Healthcare requires well-choreographed interactions among providers, patients, medications, medical equipment, laboratories, and imaging services, tasks that would benefit greatly from a highly reliable and expeditious small-package delivery mechanism. Significant potential exists for the use of unmanned aerial systems (UAS) to serve this need, as well as related healthcare applications that have only recently begun to be realized. Medical care relies upon the movement of supplies and equipment, at times through harsh environments. While there will never be a replacement for care of patients by providers, UAS offer a unique opportunity to make healthcare more efficient and cost-effective. Non-governmental aid organizations were among the first to test the limits of UAS, employing them to transport supplies over rugged terrain in under-developed countries. More recently, flights carried medications, blood samples, and heart defibrillators, testing the boundaries of this new delivery resource in more controlled environments in the United States and abroad. While these tests represent a wide variety of applications that UAS may have, many other uses in the healthcare field remain to be explored. In this paper, we summarize potential applications of UAS in medicine.

Exploratory Study of Potential Applications of Unmanned Aerial Systems for Construction Management Tasks

Despite studies exploring potential applications of unmanned aerial systems (UASs), the particular use and value of visual assets (photographs or video) collected with UASs for construction management tasks is not well understood. This paper presents an exploratory case study to identify potential applications of visual assets obtained from UASs for construction management tasks. The case study involved the development of a visual assets database from UAS-based images and videos collected during UAS flights at jobsites in the United States and Brazil as well as semi-structured interviews with construction project personnel. The results revealed potential applications of UASs mainly for project progress monitoring, job site logistics, evaluating safety conditions, and quality inspections among other secondary management tasks. In addition, an analysis of costs related to the use of UASs was performed. The main contribution of this case study is a better understanding of the use of UASs for construction management tasks and their regulatory and cost implications.

Design tool for offgrid hydrogen refuelling systems for aerospace applications

To develop an environmentally acceptable refuelling solution for fuel cell-powered unmanned aerial systems (UASs) to operate in remote areas, hydrogen fuel must be produced on-site from renewable energy sources. This paper describes a Matlab-based simulation tool specifically developed to pre-design offgrid hydrogen refuelling systems for UAS applications. The refuelling system comprises a high concentrated PV array (CPV), an electrolyser, a hydrogen buffer tank and a diaphragm hydrogen compressor. Small composite tanks are also included for fast refuelling of the UAV platforms at any time during the year. The novel approach of selecting a CPV power source is justified on the basis of minimizing the system footprint (versus flat plat or low concentration PV), aiming for a containerized remotely deployable UAS offgrid refuelling solution.To validate the simulation tool a number of simulations were performed using experimental data from a prototype offgrid hydrogen refuelling station for UAVs developed by Boeing Research & Technology Europe. Solar irradiation data for a selected location and daily UAS hydrogen demands of between 2.8 and 15.8Nm3 were employed as the primary inputs, in order to calculate a recommended system sizing solution and assess the expected operation of the refuelling system across a given year. The specific energy consumption of the refuelling system obtained from the simulations is between 5.6 and 8.9kWhe per kg of hydrogen delivered to the UAVs, being lower for larger daily hydrogen demands. Increasing the CPV area and electrolyser size in order to supply higher daily hydrogen demands (e.g., above 10Nm3 H2 per day) improves the system operability. However this can imply excessive system size and costs, jeopardizing the techno-economic feasibility of a remotely deployable off-grid refuelling solution.

Testing marine conservation applications of unmanned aerial systems (UAS) in a remote marine protected area

In 2014, the United States National Oceanic and Atmospheric Administration (NOAA) utilized unique partnerships with the National Aeronautics and Space Administration (NASA), and the US Coast Guard for the first comparative testing of two unmanned aircraft systems (UAS): the Ikhana (an MQ-9 Predator B) and a Puma All-Environment (Puma AE). A multidisciplinary team of scientists developed missions to explore the application of the two platforms to maritime surveillance and marine resource monitoring and assessment. Testing was conducted in the Papahānaumokuākea Marine National Monument, a marine protected area in the Northwest Hawaiian Islands. Nearly 30 h of footage were collected by the test platforms, containing imagery of marine mammals, sea turtles, seabirds, marine debris, and coastal habitat. Both platforms proved capable of collecting usable data, although imagery collected using the Puma was determined to be more useful for resource monitoring purposes. Lessons learned included the need for increased camera resolution, co-location of mission scientists and UAS operators, the influence of weather on the quality of imagery collected, post-processing resource demands, and the need for pre-planning of mission targets and approach to maximize efficiency.

Assessing use of and reaction to unmanned aerial systems in gray and harbor seals during breeding and molt in the UK

Wildlife biology applications of unmanned aerial systems (UAS) are extensive. Survey, identification, and measurement using UAS equipped with appropriate sensors can now be added to the suite of techniques available for monitoring animals – here we detail our experiences in using UAS to obtain detailed information from groups of seals, which can be difficult to observe from land. Trial flights to survey gray and harbor seals using a range of different platforms and imaging systems have been carried out with varying success at a number of sites in Scotland over the last two years. The best performing UAS system was determined by site, field situation, and the data required. Our systems routinely allow relative abundance, species, age–class, and individual identity to be obtained from images currently, with measures of body size also obtainable but open to refinement. However, the impacts of UAS on target species can also be variable and should be monitored closely. We found variable responses to UAS flights, possibly related to the animals’ experience of previous disturbance.

Unmanned Aerial Systems in Occupational Hygiene-Learning from Allied Disciplines.

Unmanned Aerial System (UAS) technologies are rapidly developing, lowering cost, and technology barriers for their use in numerous applications. This review and commentary summarizes relevant literature in allied fields and evaluates potential application and utility of UAS technology in the discipline of occupational hygiene. Disciplines closely related to occupational hygiene are moving to investigate potential uses--and in some cases--already employing this technology for research or commercial purposes. The literature was reviewed to formulate a cross-sectional picture of how UAS technology is being used in these closely allied disciplines which could inform or guide potential use in occupational hygiene. Discussed are UAS applications in environmental monitoring, emergency response, epidemiology, safety, and process optimization. A rapidly developing state of the art indicates that there is potential utility for this technology in occupational hygiene. Benefits may include cost savings, time savings, and averting hazardous environments via remote sensing. The occupational hygiene community can look to allied fields to garner lessons and possible applications to their own practice.