Global Literature Review on the applications of Virtual Reality in Forestry

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Faculty of Science and Forestry

GLOBAL LITERATURE REVIEW ON THE APPLICATIONS OF VIRTUAL REALITY IN

FORESTRY

Mathilde Monique Marina Perez-Huet

MASTER’S THESIS

TRANSATLANTIC FORESTRY MASTER

JOENSUU 2020

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Abstract

Perez-Huet, Mathilde Monique Marina. 2020. Global Literature Review on the applications of Virtual Reality in Forestry. University of Eastern Finland, Faculty of Science and Forestry, School of Forest Sciences. Master’s thesis in Forest Science, 106 p.

The conceptualization of VR—and the course of its development—has been of recent

examination within the scientific literature despite the technology existing since the early 60s, research regarding the applications of VR (especially those with a focus on forestry) has been limited. General consensus on the future outcomes on VR is conflicting and theoretical due to the uncertainties regarding VR development; additionally, a general scoping investigation of the multiple applications of VR has only been completed by a few members of the scientific

community. This academic essay examines the current literature on the relation between virtual reality and forestry based on a collection of extant literature (N=141). The paper provides a literature review account on the evolution of virtual reality and its adaptation to meet the forestry industry’s needs. Results illustrate the coding process in which the literature data was analyzed and showcase the formulation of key analytical themes. A SWOT analysis was also conducted to supplement key analytical themes. These findings highlight the emergent themes that were most representative of the literature data as well as underlining themes that were less recognized. The SWOT analysis identified most prominent strengths, weaknesses, threats, and opportunities of the VR technology existing within the literature. Results and observations are discussed in the context of displaying the current understanding of the literature on the influence of VR and the future implications brought by these influences on the forestry industry.

Keywords: Virtual Reality, Forest Management, Restoration therapy, VR Education, Stakeholder Engagement, 3D Simulation

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Foreword

The author would like to sincerely thank Dr. Dominik Röser and Dr. Blas Mola-Yudego for the constant support and advice throughout the process of writing this academic essay, especially during these tough times brought by the COVID-19 pandemic. This essay would not have been possible without their time and never-ending patience. In addition, many thanks would like to be extended to both Dr. Svein Olav Krøgli and Dr. Kjersti Holt Hanssen. Previous unpublished work done by the researchers were utilized in completing the software complication list. Without their aid, the list would have not been done. Finally, the author would also like to extend

gratitude towards Dr. Adalberto Pérez de Léon for the valuable input given throughout the development of this thesis.

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List of Abbreviations

2D: Two-dimensional [space] (Okabe, Owada, Igarashi, 2005)

3D: Three-dimensional [space] (Ward and Johnson, 2007; White et al., 2018; Chou et al., 2010;

Xie et al., 2011; Boissonneault, Lamontagne, Thomas, 2016)

3DSMAX: Autodesk 3ds Max, formerly known as 3D Studio and 3D Studio Max 3DUI: 3D user interface (Huang et al., 2019; Huang, Lucash, Scheller, Klippel, 2019) 3DVIA: No abbreviations, brand of Dassault Systèmes

5G: 5th Generation (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019) AA: Advanced Analytics (Müller, Jaeger, Hanewinkel, 2019)

ADAR: Airborne Data Acquisition and Registration (Ward and Johnson, 2007) AI: Artificial Intelligence (Müller, Jaeger, Hanewinkel, 2019)

API: Application Programming Interface

AR: Augmented Reality (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019;

Hamon et al., 2011; Gupton. 2017)

ART: Attention Restoration Theory (Tabrizian, Baran, Smith, Meentemeyer, 2018) C#: C Sharp, programming language

C++: No abbreviations, a high-level, general-purpose programming language

CAD: Computer-aided Programs (Karjalainen and Tyrväinen, 2002; Lewis, Sheppard, and Sutherland, 2004)

CAVE: Cave Automatic Virtual Environment (Aghamirkarimi and Lemire, 2017) CAVE2: Cave Automatic Virtual Environment Two

CGI: Computer Generated Image (Yu, Lee, Luo, 2018)

CPS: Cyber-physical Systems (Müller, Jaeger, Hanewinkel, 2019) CPU: Central Processing Unit

CuVE: Cultural Virtual Environment (Meini, Di Felice, Petrella, 2018) DBH: Diameter at Breast Height (Müller, Jaeger, Hanewinkel, 2019)

DEM: Digital Elevation Model (Griffon et al., 2011; Li and Zhang, 2019; Xie et al., 2011;

Boissonneault, Lamontagne, Thomas, 2016)

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DirectX: No abbreviations, A collection of application programming interfaces for handling tasks related to multimedia, especially game programming and video, on Microsoft platforms DSS: Decision Support-system (Fabrika, Valent, Merganičová, 2019)

DTM: Digital Terrain Model (Lim and Honjo, 2003; Rossman, Schluse, Krahwinkler, 2007) FARSITE: Fire, Fuel, and Smoke Science Program

FIA: Forest Inventory Analysis

FORSI: Karjalainen and Tyrväinen, 2002 FOV: Field-of-View

GeoTIFF: Geographic Tagged-Image File Format (Wells, 2005)

GIS: Geographic Information System (Hanso and Drenkhan, 2013; Ward and Johnson, 2007;

Jorge et al., 2009; Aghamirkarimi and Lemire, 2017; Ball, Capanni, Watt, 2007) GNSS: Global Navigation Satellite System (Müller, Jaeger, Hanewinkel, 2019) GPS: Global Positioning System (Ward and Johnson, 2007)

GPU: Graphics Processing Unit (Kohek, Strnad, Zalik, Kolmanic, 2018) GUI: Graphic User Interface (Lim and Honjo, 2003)

GUI: Graphic User Interface (Soloman, 2018)

HMD: Head-mounted display (Mattila et al., 2020; Fabrika, Valent, Scheer, 2018; Yu, Lee, Luo, 2018; Bowman et al., 2003; Aghamirkarimi and Lemire, 2017; Delabrida et al., 2017;

Zimmerman 2016; Kim, Go, Choi, 2018; Zahabi and Razak, 2020)

HTC Vive: No abbreviations, a virtual reality headset developed by HTC and Valve HTML: HyperText Markup Language

HTML5: HyperText Markup Language Five HUD: Headsup-display (Bowman et al., 2003)

I 4.0: Industry 4.0 (Müller, Jaeger, Hanewinkel, 2019) IoS: Internet of Services (Müller, Jaeger, Hanewinkel, 2019)

IoT: Internet of Things (Müller, Jaeger, Hanewinkel, 2019; Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019)

IRVE: Virtual Environments (Bowman et al., 2003)

IVE: Immersive Virtual Environments (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019; Tabrizian, Baran, Smith, Meentemeyer, 2018;)

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IVR: Immersive Virtual Reality (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019)

JAVA: No abbreviations, general-purpose programming language LANDIS: No abbreviations, a landscape-scale forest ecosystem model LANDIS-II: No abbreviations, landscape-scale forest ecosystem model LED: Light-emitting Diodes (Kobayashi, Ueoka, Hirose, 2009)

LIDAR: Light Detection and Ranging (Ward and Johnson, 2007)

LOD: Level-of-Detail (Schmalstieg and Gervautz, 1997;Wells, 2005; Bowman et al., 2003;

Jorge et al., 2009; Dong, Liu, Fan, Zheng, 2015; Zach, Mantler, Karner, 2002)

MAYA: No abbreviations, a 3D computer graphics application that runs on Windows, macOS and Linux

MONSU: No abbreviations, a calculation and planning software that was developed in Finland in order to be used within multiple-use forestry (Karjalainen and Tyrväinen, 2002)

Monte: No abbreviations, a forest growth model (González, Kolehmainen, Pukkala, 2007) MR: Mixed Reality (Gupton, 2017)

OpenGL: Open Graphics Library

QoE: Quality of Experience (Brunnström et al., n.d.) RAM: Random-access memory

RTIL-system: Real-time Interactive L-System (Hamon et al., 2011) SAR: Synthetic Aperture Radar (Ward and Johnson, 2007)

SDC: Stand Diagnostic Card (Fabrika, Valent, Scheer, 2018) SIBYLA: Simulator of Forest Biodynamics

SILVA: No abbreviations, a single tree forest growth simulator SLOAM: Semantic Lidar Odometry and Mapping

SQL: Structured Query Language SRT: Stress Recovery Theory

SVS: Stand Visualization System (Fabrika, Valent, Scheer, 2018) TABI: Thermal Airborne Broadband Imager (Ward and Johnson, 2007) UAV: Unmanned Aerial Vehicle

UI: User Interface (Delabrida et al., 2017)

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USD: US Dollars

VE: Virtual Environments (Bowman et al., 2003; Westerberg and Shiriaev, 2013; Uusitalo and Orland, 2001)

VEROSIM 3D GIS: Virtual Environments and Robotics Simulator 3D GIS VF: Virtual Forest

VQO: Visual Quality Objectives (Lewis, Sheppard, Sutherland, 2004)

VR: Virtual Reality (Mattila et al., 2020; Fabrika, Valent, Scheer, 2018; Liu, Cheng, Chen, 2019;

Aghamirkarimi and Lemire, 2017; Shodhan et al., 2018; Chen et al., 2020; Melemez, Di Gironimo, Esposito, Lanzotti, 2013; Cipresso, Giglioli, Raya, Riva, 2018; Hamon et al., 2011;

Huang et al., 2019; Zahabi and Razak, 2020; Gupton, 2017) VRI: Virtual Reality Images (Blasco et al., 2009)

VRML: Virtual Reality Modelling Language (Fabrika, Valent, Scheer, 2018; Bowman et al., 2003; Wang, Weinacher, Koch, 2008; Wang, Zhao, Song, 2008)

Web3d: Navigate Websites using 3D WebGL: Web Graphics Library

X3D: Extensible 3D (Bowman et al., 2003) XR: Extended Reality (Gupton, 2017)

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Glossary

1. 3-PG is a stand-level model of forest growth, without its study of physiological ecology process of one tree (Ma and Zhang, 2014)

2. Adaptive training is defined as the training in which the problem, the stimulus, or task is varied as a function of how well the trainee performs (Zahabi and Razak, 2020)

3. Adaptive variable is an adjustable feature that changes based on the trainee’s

performance (e.g., difficulty level of the simulation, feedback) (Zahabi and Razak, 2020) 4. Advanced analytics (AA) describes advanced statistical methodology, enabling data

analysis which was extremely time-consuming or impossible previously. Application examples of advanced analytics are predictive maintenance or short-term product demand forecasts (Müller, Jaeger, Hanewinkel, 2019)

5. Airborne data acquisition and registration (ADAR) is an airborne sensor that collects high spatial resolution data (1 m) (Ward and Johnson, 2007)

6. Artificial intelligence is the simulation of human intelligence processes (such as learning and reasoning) by computer systems (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019)

7. Attention restoration theory suggests that interaction with fascinating stimuli found in natural settings can restore cognitive resources that are subject to depletion, specifically direct attention (Tabrizian, Baran, Smith, Meentemeyer, 2018)

8. Augmented reality (AR) has a few definitions of its own. Below are some of the few that exists.

a. A system, which allows for real and virtual objects to exist within the same space, in which they can interact in real time (Milchev and Miltchev 2018)

b. Is where the real environment is enhanced with computer-generated, virtual objects, often for visualization purposes (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019)

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9. CAVE is a projection-based VR system that blends real and virtual objects in the same space so that a person has an unoccluded view of his/her own body as it interacts with the virtual objects. Users can navigate through the space either by physically walking around in the CAVE or using the wand as a control device to move greater distances (Neira et al., 1993)

10. Cloud technology also called cloud computing is the basis for digital integration platforms where data is stored, analyzed and made available for (collaborative) usage within and across organization borders. Cloud computing allows cheaper and more advanced processing of big data, often in form of so-called pay-per-use system (Müller, Jaeger, Hanewinkel, 2019)

11. DEM is a regular grid of terrain elevation values on which each point is interpolated from spot height measurement or contour data (Uusitalo and Orland, 2001)

12. E-Learning is a very broad term covering anything relating to the use of modern

technologies in education, whether implemented online, offline or a combination of both (Kirkenidis and Andreopoulou, 2015)

13. Environmental attitudes are to assist social groups and individuals in acquiring the value concerning about the environment and the promise to actively participate in

environmental improvement and protection (Liu, Cheng, Chen, 2019)

14. Environmental Education contains a lot of available definition. Below are some provided:

a. Environmental education as an education process aiming at the correlation

between people and the natural and artificial environment, including the problems related to human environment such as population, pollution, energy distribution and energy conservation, natural conservation, technology development,

transportation construction and urban and rural plans, allowing the citizens understanding the relationship between humans and environment through education (Liu, Cheng, Chen, 2019)

b. Environmental education as that educators concerned about the environment, including current or possible environmental problems in the education process and containing environmental competence in the related course and teaching activity into the education design to effectively pass down to the next generation

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to concern about the peripheral environment in daily life, protect the environment, do not damage the environment, actively participate in solving environmental problems and present environment problem-solving competency to cope with difficult environment problems (Liu, Cheng, Chen, 2019)

c. Environmental education as the lifelong learning process for people understanding the complicated natural world and the relevant issues d. Environmental education as the process of cognitive value and concept

clarification to develop, to understand and to appreciate skills and attitudes essential for the mutual relationship among humans, culture and the creature and physical environment (Liu, Cheng, Chen, 2019)

15. Environmental knowledge is to assist social groups and individuals in acquiring various experiences and basic understanding about the environment and the problems (Liu, Cheng, Chen, 2019)

16. Environmental literacy [ecology dictionary] referred to the knowledge of natural systems and ecological concepts, the understanding of environmental issues and the

environmental problem-solving with investigation, thinking and communication (Liu, Cheng, Chen, 2019)

17. Environmental literacy referred to individual knowledge and attitudes related to the environment and environmental issue, skills and motivation to solve environmental problems, and willingness to maintain the dynamic balance between life quality and environmental quality (Liu, Cheng, Chen, 2019)

18. Environmental skills are to provide social groups and individuals with skills to identify and solve environment problems (Liu, Cheng, Chen, 2019)

19. FARSITE which is a fire behavior and growth simulator software (Jorge et al., 2009) 20. FORSI is a commercial landscape simulator that can be used on PC and is sued to fulfill

the needs of practical visualization in forestry organizations. Realism and flexibility are its advantages (Karjalainen, and Tyrväinen, 2002)

21. Gamification is the process of adding game design elements in non-game scenarios in order to improve engagement and motivation (Patil, Yao, Lok, 2019)

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22. GIS is a computer system that allows users to collect, manage, and analyze large amounts of data that can be linked to geographic locations (Ward and Johnson, 2007)

23. GPS is a satellite-based navigation system used to compute and track geographic positions (Ward and Johnson, 2007)

24. Hybrid models are several combined categories of models. They are mutually

complementary, i.e. their algorithms are mutually bound (Fabrika, Valent, Merganičová, 2019)

25. Imagination [VR context] which means that virtual reality can provide users with imagination space (Liu, Cheng, Chen, 2019)

26. Immersion [VR context], is defined as such below:

a. The extent to which the computer displays are capable of delivering an inclusive, extensive, surrounding, and vivid illusion of reality to the senses of a human participant (Zahabi and Razak, 2020)

b. When users no longer feel the external environment they are in, but integrate into the virtual world provided by the computer (Liu, Cheng, Chen, 2019)

27. Immersive virtual environments (IVE)—created through combination of hardware and software systems—refer to a distinct type of virtual reality where individuals are

“surrounded” by “synthetic” information meant to generate the illusion of real environments (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019) 28. Immersive VR is a computer-based environment where the perception of being physically

present in the non-physical world exists (Yusoff and Shafiril, 2019)

29. Industry 4.0 can be summarized as an integrated, adapted, optimized, service-oriented, and interoperable manufacturing process which is correlated with algorithms, big data and high technologies ((Müller, Jaeger, Hanewinkel, 2019)

30. Information-rich virtual environment (IRVE) is a realistic VE that is enhanced with the addition of related abstract information (Bowman et al., 2003)

31. Interaction [VR context] refers to the degree to which users can operate objects in the virtual environment and the natural degree to get feedback from the environment Users interact with characters and things in the virtual environment just as they do in the real environment (Liu, Cheng, Chen, 2019)

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32. Internet of Services can be understood as the opportunity of offering services as well as production technologies via the internet (Müller, Jaeger, Hanewinkel, 2019)

33. Internet of Things describes the “linkage of objects (things) with a virtual representation on the internet or a similar structure to the internet”. In this context objects are not only machines, but all devices and humans equipped with sensing, identification, processing, communication and network capabilities (Müller, Jaeger, Hanewinkel, 2019)

34. Landscape visualization can be considered a subset of the broader field of geographical visualization which is used to communicate existing conditions and alternative landscape scenarios, past and present, for both educative and consultative purposes (Pettit,

Raymond, Bryan, Lewis, 2011)

35. Light Detection and Ranging (LIDAR) is an airborne system that transmits pulses of laser light to the surfaces of the Earth and measures the time it takes for the light to be

reflected or scattered back to the instrument (Ward and Johnson, 2007)

36. L-system is a rewriting process based on formal grammar and is used to generate 3D, dynamic structures such as virtual plants and fractal graphics (Hamon et al., 2011) 37. Non-immersive VR is a computer-based environment that can simulate places in the real

or imagined worlds (Yusoff and Shafiril, 2019)

38. Presence or the sense of presence is defined as the degree to which participants feel that they are somewhere other than where they physically are when they experience the effects of a computer-generated simulation (Lee, Kim, Lee, 2004; Cipresso, Giglioli, Raya, Riva, 2018)

39. Remote sensing is another geospatial tool that refers to methods of gathering information about features without having sensors in direct contact with them. The sensors are typically mounted on satellites or airplanes and are used to identify features by the electromagnetic energy that is reflected or emitted from them. Remotely sensed images differ in spatial, temporal, and spectral resolutions (Ward and Johnson, 2007)

40. Restoration refers to recovery from both psychological and physiological stress, which can be caused by attentional fatigue (Mattila et al., 2020)

41. Serious games are games whose primary objective is not fun or entertainment but rather learning or practicing a skill (Yusoff and Shafiril, 2019)

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42. Simulator is a unification of the system environment and the system itself described by the model (Fabrika, Valent, Merganičová, 2019)

43. Smart Factory is the center and the final goal of I 4.0. This concept describes a factory in which CPS are the basis for decentralized, real-time communication and self-controlling production processes. The Smart Factory is intended to be more intelligent, flexible and dynamic as it consists of autonomous fractal systems which are linked via the IoTS.

Machines and equipment will have the ability to improve processes through self- optimization and autonomous decision making (Müller, Jaeger, Hanewinkel, 2019) 44. Smart urban forest is the collection of trees and associated vegetation within a city that

are designed, monitored, and managed using digital technologies, through which forest benefits are enhanced and self-organization, self-regulation, and automation can be achieved (Nitoslawski., Galle, Konijnendijk Van Den Bosch, Steenberg, 2019) 45. SRT is a psycho-evolutionary theory that considers non-threatening natural settings as

restorative environments, leading to a more positive emotional state and a decreased level of physiological arousal (Yu, Lee, Luo, 2018)

46. Subjective vitality is the positive feeling of aliveness and energy (Mattila et al., 2020) 47. Synthetic aperture radar (SAR) is another airborne system deployed aboard aircraft or

satellites that can be used to detect and locate features by sending out pulses of

electromagnetic waves and measuring the return times and directions of the waves. The spatial resolution of SAR data is limited by the width of the pulse, i.e., narrower pulses produce finer data (Ward and Johnson, 2007)

48. System parameters are constant values which control the model (Fabrika, Valent, Merganičová, 2019)

49. Thermal airborne broadband imager (TABI) is a relatively new airborne sensor with high spatial (25–1.5 m), spectral (288 bands), and thermal resolution (0.11). TABI has proved useful in urban areas for the mapping of heat island effects (Ward and Johnson, 2007) 50. Thinning trainer can be defined as a system composed of a mathematical model of a

forest, computer software and hardware used for training tree selection and simulation of immediate impact of thinning on forest condition (production, ecological and economic) (Fabrika, Valent, Scheer, 2018; Fabrika and Valent, 2018)

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51. Uncertainty is defined as the statistical variations, errors introduced and accumulated in data collection, processing, and visualization, and noisy or missing data (Huang et al., 2019)

52. Virtual environment (VE) is a synthetic, spatial (usually 3- dimensional) world seen from a first-person point of view. The view in a VE is under the real-time control of the user (Bowman et al., 2003)

53. Virtual experiment refers to using the networked virtual lab environment and the hardware equipment of virtual reality to make participants interact with the virtual physical objects to complete all kinds of scheduled experiment projects, and the experimental effect is the same as in the real world (Lei, Liu, Yang, 2012) 54. Virtual Forest (VF) is an image representing the summation of individual trees,

topography and soil conditions, available infrastructure and other information (Müller, Jaeger, Hanewinkel, 2019)

55. Virtual Forest is a joint effort of various partners who combine their know-how in the fields of automation/robotics, machine development and forestry to realize a

comprehensive framework in order to identify, visualize and optimize biological and technical processes in the forest (Germany) (Rossmann, Schluse, Schlette, 2010) 56. Virtual Forest is a projected launched earlier this month by Koen Hufkens, an ecologist

at Harvard University's Richardson Lab, which broadcasts a live feed of continuously refreshing, 360-degree still images (one every 15 minutes) from a spot deep in the middle of the Harvard Forest, a plot of land in Western Massachusetts that is owned by the university and open to researchers and the public (Unknown Author, n.d.)

57. Virtual Reality has many definitions. Below are a few examples.

a. A computer-generated environment, in which humans can interact with a sense of presence similar to that of real life (La Salandra, Frajberg, Fraternali, 2019) b. A dynamic 3D vision of multi-source information fusion as well as a system

simulation of physical behavior, generates an analog environment through computer, making users enter a virtual space through the help of sense-helmet, data gloves and other specialized equipment. Users can perceive and operate

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every object in the visual world to get an immersive experience through visual, tactile and auditory components (Shangguan, and Huang, 2014)

c. A situated world constructed with computer scientific technology, transforms entities in the real environment and digital data into observable and even

touchable 3D virtual scenes; matching with various human–computer interfaces, people become the direct participants in the virtual world, as in a real

environment…. virtual reality as the combination of computers and the peripherals, allowing users being in the 3D space generated in the computer model (Liu, Cheng, Chen, 2019)

d. A three-dimensional (3D) image or computer simulation in which an object from the real or imaginary world is modelled and displayed to a person in a virtual environment (Peedosaar, Poldveer, Kolla, Kanger, 2019)

e. Advanced technology combining a high degree of control with ecological validity that can simulate highly realistic environments (Yu, Lee, Luo, 2018)

f. Real-time interactive graphics with 3D models, combined with a display technology that gives the user the immersion in the model world and direct manipulation (Cipresso, Giglioli, Raya, Riva, 2018)

g. Refers to “immersive, interactive, multisensory, viewer-centered, three- dimensional, computer-generated environments and the combination of technologies required to build these environments” (Arns, Brisbin, Foldes, Holland, n.d.; Cipresso, Giglioli, Raya, Riva, 2018)

h. The illusion of participation in a synthetic environment rather than external observation of such an environment. VR relies on a 3D, stereoscopic head-tracker displays, hand/body tracking and binaural sound. VR is an immersive, multisensory experience (Cipresso, Giglioli, Raya, Riva, 2018)

58. Visualizations are pictures of objects, conditions, processes, or places that help the viewer understand and interpret the subject matter by revealing its appearance or visually

displaying certain significant characteristics (Lewis, Sheppard, and Sutherland, 2004) 59. VR Wildfire Prevention is a virtual reality game in which the player performs a series of

tasks regarding safe building and maintaining a campfire. The player has free reign to

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make mistakes, and is notified at the end of the game whether their actions presented some risk in starting a wildfire (Vega et al., 2017)

60. VRML has a few definitions in the literature. Below are some of them discussed in the research.

a. A programming language and library for 3-D computer graphics (Xie et al., 2011) b. A virtual reality modeling language which recommended by the international

organization ISU/IEC, except some modeling functions, it rules the

communicating norm of network and related interacting equipment, so it suitably be adopted to design the remote virtual experiment system in the

C/S(server/browser) mode of network, and it has other functions like independence of platform (Lei, Liu, Yang, 2012)

c. One of Web3d technologies, which are used to deliver interactive 3D objects and worlds across the Internet (Lim and Honjo, 2003)

61. WebVR is a programming interface that supports a variety of virtual reality devices via a web browser (Aghamirkarimi and Lemire, 2017)

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Declaration of Interest

The author declares that there is no conflict of interest during the entirety of the thesis work.

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Introduction

Virtual Reality (VR)—while coined in the 1980s (Shangguan, Huang, 2014)—has had many definition iterations in the scientific literature. While there is currently no official, agreed description, VR can be defined as a dynamic, 3D virtual computer-simulated environment in which users can interact with the 3D rendered objects; thus, immersing themselves in the realistic virtual space. The recreated environment tries to replicate reality as close as possible.

Access to the virtual world is done through the usage of specialized hardware equipment and is rendered through specific 3D visualization software. Users are able to retract information from the 3D models through visual and auditory simulations. VR technology was first conceptualized in the report “The Ultimate Display” written by Ivan Sutherland for IFIP in 1965 (Cipresso, Giglioli, Raya, Riva, 2018; Huang et al., 2019; Shangguan, Huang, 2014; White et al., 2018).

Ivan Sutherland described VR as “a window through which a user perceives the virtual world as if looked, felt, sounded real and in which the user could act realistically” (Cipresso, Giglioli, Raya, Riva, 2018). Earlier, Morton Heilig created the “Sensorama” which ultimately was the very first 3D immersive simulator (Cipresso, Giglioli, Raya, Riva, 2018). Ivan later improved upon the technology by adding sound, smell, and haptic feedback with the “Ultimate Display”.

In 1961, Philco (now owned by Phillips) developed the first HMD system capable of handling VR simulations (Cipresso, Giglioli, Raya, Riva, 2018). However, it wasn’t until the 1980s where the first commercial VR tools (software and hardware) appeared (Cipresso, Giglioli, Raya, Riva, 2018). The 1990s then saw an experimental phase of VR hardware like the Virtual Boy. An example of this was the creation of the CAVE Automatic Virtual Environment by the Electronic Visualization Laboratory of the University of Illinois. The CAVE is an immersive VR system composed by projectors fixed on three or more walls of a room that allows observes to view the exact virtual environment as the user (Cipresso, Giglioli, Raya, Riva, 2018). After 20th century, the technology—along with advanced software technologies—evolved to combine 3D

computing power and interactive technology to improve the rendering quality and transmission speed; thus, bringing about a new era of VR (Shangguan, Huang, 2014).

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As we enter the fourth industrial revolution (I 4.0), rapid technological processes in hardware and software systems increased the performance of data retention, processing and transmission, and digitization of services (Müller, Jaeger, Hanewinkel, 2019). Since 2016, a resurge in VR hardware development has provided further technological advancements in part due to this digital revolution (Kauppi, 2016). The revived interest in VR technology has allowed tech companies (Sony, Samsung, HTC, Google, and Facebook) to decrease costs and increase the quality of devices. This in turn allowed VR applications to diversify and be applied to various fields such as the military, gaming industry, industrial manufacturing, medical science,

education, aerospace training and of course, forestry operations (Cipresso, Giglioli, Raya, Riva, 2018; La Salandra, Frajberg, Fraternali, 2019; Shangguan, Huang, 2014; White et al., 2018). The availability of cheap tools for VR experimental and computational use has allowed the

technology to be applicable into any field (Cipresso, Giglioli, Raya, Riva, 2018). In recent years, VR research has focused on improving hardware and software performance to slowly close the gap between reality and the virtual world. Current efforts have been towards making better- quality VR devices that will blur that fine line. These new VR devices (e.g. Oculus Rift or Vive Pro Eye) have features such as large displays for more realistic simulations, high frame rates, low latency for more fluid rendering, and high-precision tracking to reliably identify the user’s movements (Cipresso, Giglioli, Raya, Riva, 2018; La Salandra, Frajberg, Fraternali, 2019). Due to the reduced cost and the growing quality of devices, VR applications have also reached the consumer market with VR platforms using either PCs or smartphones as computational units (Kauppi, 2016; La Salandra, Frajberg, Fraternali, 2019; Unknown Author, 2018; White et al., 2018).

Recently, the forestry sector has taken a stab at VR technology and applying the 3D perspective in recreating forested landscapes. These reconstructed forests are known as “Virtual Forests” by the industry and have a variety of applications; from teaching tools to conducting forestry inventory (VR First, 2018). VR has the potential to improve the visualization of 3D spatial data such as structures of trees in a forest compared to 2D applications such as GIS on a

desktop/laptop environment (Boissonneault, Lamontagne, Thomas, 2018). The immersiveness of a VR interface allows users/operators to see the 3D scanning of the trees in a 1:1 scale with a

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real-world environment—including tactile and auditory components—, and therefore enables operators to perform the tasks (e.g. assessment) with their natural perceptual ability, similar to physically being on location (Bowman et al., 2003; Fabrika, Valent, Scheer, 2018; Liu, Chen, Cheng, 2019; Shangguan, Huang, 2014). Despite these promising features, there are still a few problems that are currently hindering the advancements of VR application in forestry. As an advanced piece of interface technology, VR technology requires a strong and comprehensive understanding of the specific tasks in which the interface is designed into (Lin, Chen, Tang, and Wang, 2009; Müller, Jaeger, and Hanewinkel, 2019; Shangguan, Huang, 2014; Ward and Johnson, 2007). Not many forestry companies have a division dedicated to VR yet and thus lack company-built or owned VR programs to construct 3D forests. Times where software was utilized to build 3D forests, they are not programmed to fit a forester’s objectives.

Additionally, due to the infancy of the modern VR, many challenges and unknowns hamper further introduction of VR as well as its development. Some of these challenges and unknowns include but are not limited to: Clarity of communications over 3D spatial data/visualizations (Barreteau, Le Page, Perez, 2017; Hanso, Drenkhan, 2013; Fujisaki et al., 2008; McGaughey, 1998), Technical barriers (Ichikawa, Takashima, Tang, Kitamura, 2018; Li, Zhang, 2019;

Müller, Jaeger, and Hanewinkel, 2019; Ward and Johnson, 2007; White et al., 2018), Data fragmentation (Aghamirkarimi and Lemire, 2017; Dong, Wei, Gu, Wei, 2014), Stakeholder input (Ball, Campanni, Watt, 2007; Boissonneault, Lamontagne, Thomas, 2018; Castella, 2009; Pettit, Raymond, Bryan, Lewis, 2011), Interoperability (Aghamirkarimi and Lemire, 2017; Müller, Jaeger, and Hanewinkel, 2019; Nitoslawski, Galle, Konijnendijk Van Den Bosch, Steenberg, 2019; Uusitalo, Orland, 2001), Optimization of data (Nitoslawski, Galle, Konijnendijk Van Den Bosch, Steenberg, 2019; Ward and Johnson, 2007), Methods of data collection (Aghamirkarimi and Lemire, 2017; Li, Zhang, Jaeger, Constant, 2010; Müller, Jaeger, and Hanewinkel, 2019;

Nitoslawski, Galle, Konijnendijk Van Den Bosch, Steenberg, 2019), Database connectivity (Aghamirkarimi and Lemire, 2017; Nitoslawski, Galle, Konijnendijk Van Den Bosch, Steenberg, 2019; Ward and Johnson, 2007), User-friendliness (Cipresso, Giglioli, Raya, Riva, 2018; White et al., 2018), Cost of VR technology (Hanso, Drenkhan, 2013; Nitoslawski, Galle, Konijnendijk Van Den Bosch, Steenberg, 2019; White et al., 2018), and more. In an increasingly digitized

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world, it is more important than ever for the forestry industry to quickly adapt and adjust to meet the new needs of the Industry 4.0 (I4.0) revolution (Milchev, Miltchev,2018; Müller, Jaeger, and Hanewinkel, 2019). VR provides the entry into this new era.

Despite continuing development and increasing focus/demand for virtual reality technology, the current literature on VR application in the forestry sector is quite sparse and fragmented.

Because of how little there is of the literature studying VR in forestry, some significant topics discussed usually in forestry such as ecosystem services, forest ecology, forest pathology, and others were absent. Additionally, due to the constraints of this research, this literature review does not cover all the extant literature. Of the existing literature that was surveyed, much has focused predominantly on the forest modeling and landscape visualization aspect of VR (Bao et al., 2011; Fan, Ren, Tang, 2009; Li, Deussen, Song, Willis, Hall, 2011; Reche, Martin, Drettakis, 2004; Qi, Qiu, Jia, 2011; Schroth et al., 2011; Wang, Weinacher, Koch, 2018). Modeling

specifically ranged from plant ecosystems (Deussen et al., 1998) to leaf organs (Hamon et al., 2011; Wang et al., 2013). It must be noted that the current literature provides a wide selection of models: all tailored to meet the needs of the experiment made during the research, hence the wide variety (Fabrika, Valent, Merganičová, 2019). They vary in their principles, algorithms, software designs, hardware usage, to 3D modeling.

Topics revolving around using VR for learning and education purposes were quite numerous within the examined literature. A number of studies have focused specifically on the training possibilities of VR (Aik and Tway, 2004; Brunnström et al., n.d.; Brunnström et al., n.d;

Delabria et al., 2017; Fabrika and Valent, 2015; Fabrika, Valent, Scheer, 2018; He, Wang, Chen, Leng, 2019; Lapointe and Robert, 2000; Nam and Park, 2015; Wells, 2006; Zahabi and Razak, 2020) while others examined the potential of virtual reality as a teaching tool and to improve the communication of science to the general public (Arns, Brisbin, Foldes, Holland, n.d.; Barreteau, Le Page, Perez, 2007; Fabrika, Valent, Merganičová, 2019; Hanso and Drenkham, 2013;

Kirkenidis and Andreopoulu, 2015; Lewis, Sheppard, Sutherland, 2004; Liu, Chen, Cheng, 2019;

Pettit, Raymond, Bryan, Lewis, 2011; Vega et al., 2017; Wagner and Campbell, 1994; Yusoff and Shafiril, 2019; Vretos et al., 2019). Some also examined the possibility of mutual

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stakeholder collaboration and coordination with VR (Barreteau, Le Page, Perez, 2007; Bots and Daalen, 2007; Castella, 2009; La Salandra, Frajberg, Fraternali, 2019; Stock and Bishop, 2006).

Certain individual topics were discussed in great detail, while others less. Studies examining virtual reality as a planning tool (from a forest management perspective) were found to be somewhat prolific among the literature (Fabrika, Valent, Merganičová, 2019; Ball, Capanni, Watt, 2007; Chou et al., 2010; Rossmann, Schluse, Schlette, 2010; Vanclay, Prabhu,

Muetzelfeldt, 2003). Quite a few found mental and physical restorative benefits through the introduction of a virtual forest via VR technology (Mattila et al., 2020; Moeller et al., 2018;

Patil, Yao, Lok, 2019; Tabrizian, Baran, Smith, Meentemeyer, 2018; White et al., 2018; Yu, Lee, Luo, 2018). A couple of authors focused on the opportunities that virtual reality could bring to the sector (Fabrika, Valent, Merganičová, 2019; Müller, Jaeger, Hanewinkel, 2019; Nitoslawski, Galle, Konijnendijk Van Den Bosch, Steenberg, 2019; Peedosaar, Poldveer, Kollo, Kangur, 2019; Uusitalo and Orland, 2001).

Upon reviewing the current literature, only a few, handful of studies discussed the need of 3D visualizations depicting the impact of climate change (Hanso and Drenkham, 2013; Huang, Lucash, Scheller, Klippel, 2019). Finally, some delved into the basics of VR; providing a better understanding of its concepts and technology (Aghamirkarimi and Lemire, 2017; Bowman et al., 2003; Cipresso, Giglioli, Raya, Riva, 2018; Huang et al., 2019; Nam et al., 2019; Neira et al., 1993; Shangguan and Huang 2014).

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Objectives

2. Research Rational

Due to its recent boom and ongoing development, the topic of VR in forestry has not been fully examined from multiple spectrums ranging from the forestry industry itself, environment, tourism, climate change predications, and ecosystem[s] monitoring. So far, what is understood and studied are the current applications made in tested environments (either at a university level or through a small number of private technology/forestry corporations). Thus, a lot of

speculation towards the application of VR technology leads to the following rhetoric: “VR is relatively young” and therefore, is not “fully developed” to accommodate to the demands by large forestry corporations and government agencies. In addition—due to the newly emerged market for VR—future predictions for the market’s development are based only on guesses rather than scientific data. While much of the papers discussing the topic of VR in forestry delve into these hypothetical futures of VR and how current challenges in forestry can be solved with VR, not all agree on the same outcome. So therefore, the research overarching goal will be to bridge all the known literature together to highlight the critical gaps, contradictions, ideas, and come to a consensus on the outlook of VR considering all the proposed solutions to each stated challenge—provided an unbiased direction. Then, with all the gathered data, a conclusion can be made.

While conducting the literature review, a grounded theory focus on virtual reality was also developed to showcase the many emerging areas of development in the technology within forestry such as restoration therapy, forest modeling, teleoperation, and education. However, reaching the objective will be met with certain obstacles. Because the technology being utilized in realizing virtual reality is at a relatively infant stage—the use of Virtual Reality is said to have exploded in 2016 despite existing as a concept since the 50s and technologically adapted in the 90s (Kauppi, 2016)—much of the research has yet to fully examine certain on-going

phenomenons associated with the VR technology industry. Furthermore, because development of

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VR hardware and software technology are usually kept as industry secrets to prevent competition from utilizing them, not much is known of VR outside of educational settings or possible

collaborations.

3. Research Objectives

In order to make a meaningful assessment of the VR impact on the forestry industry, every aspect of the forestry sector must be carefully observed and properly evaluated so that

challenges, problems, and proposed solutions can be appropriately identified and corrected; thus, closing the knowledge gap. The study was guided by the following steps:

1) Sorting the current literature through coding and interpreting the finalized codes into themes of interest

2) Create a modified SWOT analysis to highlight and simplify VR challenges, opportunities, and solutions for forestry

3) Summarizing the findings and conclude with prospects

4. Research Questions

Throughout the study, the following questions below were considered.

a. How is the forestry industry adapting VR technology into the field?

b. What are the challenges and limitations of the current research within the literature?

c. What are the current predictions (and factored unknowns) for the future of VR in forestry?

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Materials and Methods

5. Data sources/collection

Concerning the method of data collection, this specific study will be delving into literature review. Grant and Booth (2009) defined literature review as a method of reviewing published materials that provide examination of recent or current literature (Perez-Huet, 2019). A literature review can provide organized information within a subject area such as the systematic

identification, location, or previous analysis of multiple documents. The main focus of a literature review is to summarize and synthesize the arguments or ideas of others while also breaking down those arguments and/or ideas without adding new contributions to the body of research (The Writing Center, n.d.). Normally, the review can cover a wide range of topics at various levels—from completeness to comprehensiveness of a chosen subject—thus acting as an overview of the available material on said topic. For this particular study, a literature review method has been chosen for several reasons.

Firstly, the review has the ability to identify gaps within the literature and amalgamate them into a single piece of document for further research usage. By doing so can prevent duplication in future research work (Grant and Booth, 2009). Secondly, literature reviews can funnel all existing knowledge into one source and thus raising the case for more research on the subject matter (Shi, 2006). With the case of VR, because the current literature is so little, making the case for further research on this topic is vital to understand better its development within

forestry. Lastly, literature reviews can contribution to the identification of emergent or neglected topics concealed in the discussion within the literature (Paré and Kitsiou, 2017). Upon

identifying these special topics, perhaps new framework, theories, or research can develop; thus, improving and increasing the knowledge on the subject, especially regarding on-going dilemmas (Perez-Huet, 2019).

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Within the realm of literature review, different subgroups of literature reviews exist in terms of comprehensiveness, types of study included, and purpose (VCU Libraries Research Guide, 2019). While frequent inconsistencies or overlaps between the different review types exists;

there is currently no agreed set of discrete, coherent and mutually exclusive review types (Grant and Booth, 2009). Therefore, the literature review will contain a mixture of characteristic elements from scoping review and critical review with the focus mainly on scoping review.

Scoping review—which provides a preliminary assessment of the potential size and scope of the available research literature (Grant and Booth, 2009)—aims to classify the nature and extent of current research on the subject matter (Perez-Huet, 2019). Scoping reviews attempt to provide an initial indication of the potential size and nature of the extant literature on an emergent topic while also locating the gaps in knowledge (Paré and Kitsiou, 2017). In regard to VR, obtaining all available research evidence is crucial in understanding the developing nature of the

technology in concurrence with capturing the evolution of topics surrounding it. By doing so, new research can emerge parallel to the development of the industry; possibly increasing the chances of implementing the research faster on the field (Perez-Huet, 2019). Because of its comprehensive nature, scoping review include grey literature, thereby including more knowledge into the analysis of the subject matter (Paré and Kitsiou, 2017). This is especially important in monitoring on-going progresses in the technology as new knowledge or information can present itself faster and reliably in grey literature such as industry reports and working papers. Pre- conference workshop or symposium writeups provides the latest insight in VR technology such as the ForestTECH series or tech expos (e.g. E3, IoT Tech Expo, etc.).

In contrast, critical review aims to go beyond basic descriptions of the identified literatures and instead demonstrate the extensive research on the topic while also critically evaluating the

quality of the papers (Grant and Booth, 2009; Paré and Kitsiou, 2017). New interpretations of the existing data/content can arise from the critical analysis and thereby improving the evaluation of previous works (Perez-Huet, 2019). Paré and Kitsiou (2017) state that critical reviews also reveal strengths, weaknesses, contradictions, controversies, inconsistencies, and/or other important issues with respect to theories, hypotheses, research methods or results. Most of the work will be discussing the contradictions between authors regarding the direction of virtual reality and

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addressing the differences in approach of VR visualization. By highlighting these contradictions and different visualization approaches, the critical review can signal researchers to come to a consensus on the contradictions and discuss the various visualization models for VR. Out of these dialogues, further improvement on VR research can be done.

However, it must be noted that each type of literature review does have limitations and

weaknesses; thus, are subjected to bias. Scoping reviews are limited in their rigor as they do not have a process of quality assessment (Grant and Booth, 2009) while also being susceptible to bias. Critical reviews face similar limitations. While collecting the data, these must be kept in mind to avoid decreasing the validity of the work. Due to the literature review’s general search, only broad conclusions can be made of the literature and therefore difficult to generalize (Perez- Huet, 2019). Biases can be introduced through the failure to include significant sections of the literature or by not questioning the validity of statements made (S. Hagerman, personal

communication, October 17, 2018). Additionally, authors may only select certain pieces of literature that supports their world view; thus, lending more weight to a preferred school of thought (Grant and Booth, 2009). Potential validity threats will be addressed later in the paper.

Overall, literature review is still a valuable method of collecting data as it possesses some process for identifying key materials potential inclusion and providing critical assessments (Perez-Huet, 2019).

6. Conceptual framework

The majority of the selected literature will be mainly from scientific-based information, to provide an in-depth understanding of the research topic. The remaining non-research works will help shed additional information that may have been absent or not well-explained in the

scientific body of VR work. The information made available from the scientific literature focuses on different types of propositions on the topic such as the environment, politics of knowledge, public perception, science-policies, and local community development with a global emphasis.

By having a large range of literature sources, different perspectives on virtual reality can be integrated into the analysis and making it more comprehensive (Perez-Huet, 2019).

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When constructing the research design, a pragmatic worldview will be utilized throughout the analysis of the literature. Creswell (2014, Chapter 1) defines pragmatism as a worldview arises out of actions, situation, and consequences rather than antecedent conditions. Specifically, pragmatism is a problem-centered, real-world oriented worldview. With VR, there is a concern with how it can properly solve the problems that currently plague the forestry industry such as operations efficiency, market adaptability, technical advancements, etc. By incorporating a pragmatic worldview to the issue will offer a meaningful approach to investigate these

aforementioned problems while also providing a better understanding of what is actually going on in the background (Creswell, 2014, Chapter 1). At times, communication of the science isn’t so clear and direct. Challenges that VR currently faces—either on a technological barrier or field implementation constraint—can be further explored and highlighted with a pragmatic worldview as well.

7. Study Area Description 7.1. Study boundary

While VR was first conceptualized in the U.S. by Ivan Sutherland, the concept—and by extension, technology—has been expanded upon and further advanced outside of the U.S.

(Cipresso, Giglioli, Raya, Riva, 2018). VR currently is being researched all over the world.

Cipresso, Giglioli, Raya, and Riva (2018) discovered that a majority of VR research occurred globally with majority of papers came from US, China, England and Germany. They also found that Japan, Canada, Italy, France, Spain, South Korea, and the Netherlands took prominent positions as well (Cipresso, Giglioli, Raya, Riva, 2018). However, it must be noted that the authors only delved into virtual reality as a whole subject matter rather than narrowing their search to a specific sector like forestry. Vretos et al. (2019) showcased the large investments from governments of different countries across the globe into virtual reality technology with the USA, France and China investing the most. Because of how widespread VR has developed and how no one country has specialized in VR (yet), no geographical boundary will be applied to this research. However, because of this large site boundary, access to some of the literature will be

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denied, either due to a language barrier or prohibition of entry to the database. Unfortunately, these papers will have to be discarded. The criteria in which these were discarded will be discussed in detail further into the paper.

7.2. Study time frame selection

Despite VR existing since the 50s as a concept (White et al., 2018), it wasn’t until Ivan Sutherland described VR as “a window through which a user perceives the virtual world as if looked, felt, sounded real and in which the user could act realistically through a VR prototype” in 1965 (Cipresso, Giglioli, Raya, Riva, 2018; Huang et al., 2019). The very first commercially available devices began to appear in the 80’s and continued until the 90s (Cipresso, Giglioli, Raya, Riva, 2018; Lim and Honjo, 2002; Yu, Lee, Luo, 2018). For example, in 1992, the Electronic Visualization Laboratory of the University of Illinois created the CAVE Automatic Virtual Environment which was an immersive VR system composed of multiple projectors mounted unto three or more walls of a room (Cipresso, Giglioli, Raya, Riva, 2018). Yet, the use of virtual reality really exploded in 2016 and has since then continued to rapidly develop to the present—and hopefully beyond (Kauppi, 2016). Given this timeline, a time frame for the literature selection would be from 1990 to present. Sources from before 1990 would either contain obsolete or discontinued technology as well as concepts that have not been updated. The most relevant information is necessary when dealing with a rapidly developing piece of

technology to allow the data to be as representative to the reality as much as possible. At the time of writing the research, it is worth noting that not all of the most recent literature is contained within this literature review. Perhaps a future addition will be made by new research to offset this issue.

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8. Methodology 8.1. Approach

Within a pragmatic worldview lens, the research will be conducted with a grounded theory approach. The purpose of utilizing grounded theory to study the VR technological development for the forestry industry in a global context is to provide emergent ideas and track the future direction of the technology; thus, providing an explanation (or theory) of the evolution of virtual reality. The intent of grounded theory is to generate or design a general, abstract theory of an on- going phenomenon, action, or interaction that is shared in the views of the studied individuals (Charmaz, 2006, Chapter 1; Creswell, 2013, Chapter 4). Usually occurs when a theory is not available or incomplete to explain. The studied phenomenon or action must occur over time;

overgoing through various, distinct steps or phases. In this case, VR has been through multiple phases, evolving over several stages of conceptualization and developments. Additionally, the proper usage and field implementation possibilities have not yet been agreed upon by the scientific community as a whole thereby allowing to showcase all of the emergent research and consolidate them into a single explanation; thus, explaining the current phenomenon despite what experts disagree on. The raw, “grounded” data is at the core of the studied process and determines the analysis process (Creswell, 2013, Chapter 4). The studied individuals—which in this case are the scientists conducting the experiments or VR specialists witnessing the progress or implementation of VR—all have experiences in the phenomenon and the creation of the theory may help explain the progress or provide a framework for further research on the topic (Creswell, 2013, Chapter 4).

In order to develop this theory, data from a large number of participants must be extracted. This process involves using multiple stages of data collection, refinement, and interrelationships of categories of information (Charmaz, 2006, Chapter 1; Creswell, 2013, Chapter 4). The process provides a systematic, analytical approach to develop the theory. Before conducting the analysis, coding is an integral part of the development of grounded theory especially when extracting the raw data and forming thematic categories. The coding process can be found in the next section.

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Finally, the theory is articulated towards the conclusion as a visual narrative for the predictions of virtual reality’s future in forestry. Other questions answered during the analysis are how the phenomena of virtual reality arose and what strategies can be introduced to impede the current issues of virtual reality. Challenges to keep in mind while conducting grounded theory are the preconceived ideas or notions built before conducting the research (to prevent the incorporation of research bias and tampering of the data) and predicting when the theory is adequately

capturing the occurring process (Creswell, 2013, Chapter 4). These challenges will be further delved into.

8.2. Sampling

Upon considering the sampling of this research, both purposeful and theoretical sampling where debated. In purposeful sampling, researchers pick the participant sampling criteria prior to

conducting research whereas in grounded theory, theoretical sampling occurs throughout the data collection process (Maxwell, 2013, Chapter 5; Creswell, 2013, Chapter 4). Initial collection began with identifying cases, individuals, or situations that deliberately provide information relevant to the research questions. By deliberately selecting cases, individuals, or situations representative of the norm, there is more confidence that the conclusions adequately represent the average members of the population rather than a sample of the same size that captures random or accidental variation (Maxwell 2013, Chapter 5; Creswell 2013, Chapter 3). However, as the process continued, the selection of the material shifted towards emergent topics and narrowing the search to specifically focus on them. Ultimately, while the research commenced with some purposeful sampling, theoretical sampling was the main sampling method in obtaining the literature material.

Thus, when reviewing the available literature on VR in forestry, a sample frame was created to include a bounded—but still comprehensive—search. Diversity of literature papers (from various topics) was a top priority in the search and was integrated in the criteria (Perez-Huet, 2019).

These topics included any socio-economic or environmental related global topics associated with VR regarding the forestry industry such as biodiversity monitoring, forest operations, local

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community development, wildfire management, etc. were included in the search. In addition to the sample frame, an inclusion and exclusion criteria was applied to limit the amount of research papers into the source pool. Inclusion and exclusion criteria must be set in place to aid

researchers eliminate studies that do not correspond with the research questions and subject matter (Paré and Kitsiou, 2017). By minimizing the amount of papers, the quality of the material can increase while also allowing the literature review to be more manageable and well-organized (Shi, 2006). In this case, to refine the search of research material, the following inclusion filters were applied: 1) Language (English or French), 2) Interest of subject matter (Forestry, Forests, Forest Management, Simulation, Virtual Reality), 3) Availability (Online peer-reviewed

journals), and 4) Years (1990-2020). The excluded papers were not available off-line or through blocked database entry, or non-English or French documents. An initial attempt to translate some research in Chinese was made (had shown up in the search as their abstract was available in English but not the rest of the paper); however due to a lack of time and an official translator, these papers were later discarded (N=13). One Estonian and one Finnish paper were also discarded due to the same reasons. Four papers were discarded due to lack of entry of database.

Refer to Appendices A and B for citations of these papers. The literature search was conducted in 2019 and continued until completion in 2020. A sample frame of N<200 (N=141) was selected, with 20 papers discarded due to language or access barrier.

The main source used to search for much of the literature was through UEF Primo. UEF Primo was chosen as the main search library due its accessibility as a student. Other search engines included Google Scholar and UBC library also for their accessibility and user-friendliness application. Google Scholar also provided more recent and diverse topical research material that had not yet been published or licensed through UBC library or UEF Primo. Both UBC Library and UEF Primo was also utilized to search material inaccessible through Google Scholar.

Research papers that were unfortunately inaccessible due to licensing or lack of direct weblink were backtracked through entering the search directly into databases such as ESCOBUS, Elsevier, Scopus, ResearchGate, CNCI, SpringerLink, IEEE, and Web of Science.

Supplementary data was also collected directly from conducting a search in specific journals such as AMC SIGGRAPH, VRCAI, VRST, IEEE Virtual Reality. Specifics of the searches can

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be found in Appendices C. Another database considered was the North Carolina State University library, but permission to access was denied due to the COVID19 pandemic and therefore was unable to be utilized.

When searching for potential literature on the databases, both keywords and subject headings were considered. Keywords included concepts in everyday language whereas subject headings only represented one term for a concept (VCU Libraries Research Guides, 2019). Subject headings and keywords both advantages and disadvantages. Keywords can capture alternative spellings while subject headings help find relevant articles. For example, by typing simply “VR forestry” led to variable retention research rather than virtual reality. Moreover, the term “3D”

and “visualization” has a certain association (to some degree) with virtual reality and therefore were included as keywords during the search. Examples of keywords and subject headings include “Virtual Reality forestry”, “3D visualization”, “Virtual Simulation [in forestry]”,

“landscape visualization”, “3D”, etc. As there exists different variation in virtual reality terminology usage—not yet a consensus within the scientific community on the official terminology—alternate synonyms for VR such as virtual forest or virtual landscape were also utilized as keywords in the databases/journals. While keywords provided a good insight into the paper’s discussion, a quick review of the abstracts allowed more screening of unwanted papers as some had relation to VR only through keywords. Despite inputting the correct keywords, sometimes papers that were vaguely related or had no relation at all to virtual reality such as Augmented Reality (AR), LIDAR, or tree map visualizations appeared. Either these were

discarded or kept aside for additional analysis. Duplicates were removed from the literature pool.

Literature identified via cross referencing from other peer-reviewed publications or articles recommended by experts for detailed information were also included in the systematic search.

Throughout the document collection, a memo was created alongside. Memos help understand the topic while helping the researcher write down ideas about the evolving theory (Maxwell, 2013, Chapter 6; Creswell, 2014, Chapter 1, Charmaz, 2006, Chapter 1). Further information on the process of the data search can be found in Appendices C.

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The types of documents were also of importance when conducting the literature review.

Documents provide a source of understanding and making sense of social and organization practices or as readings of people’s social events (Coffey, 2014). All documents are created for a particular purpose; according to social convention to serve a function of sorts (Coffey, 2014; S.

Hagerman, personal communication, October 17, 2018). By analyzing particular documents, they can help better understand the context construct and display affairs that would normally not be available to the general public or easily accessible to those outside the industry (Coffey, 2014). The majority of documents consisted of primary, unsolicited sources with a few tertiary incorporated. The few supplemental tertiary material came from online blogs or conference reports. All the documents were extant texts. When proceeding with the selection of tertiary documents, the criteria will mostly focus on three main points: 1) the relevance of the

information, 2) document author, and 3) document relevance to the search criteria. Through the examination of such documents, a clearer understanding of the advancements of VR, but also showcase the expectations and future projections of forestry industry officials on the technology.

Documents that were considered within the sample frame selection included academic (journal) papers, conference articles, symposium abstracts, symposium/conference reviews, industry reports, research reports, and online blog posts. Documents of the academic nature were mostly chosen to avoid a biased reporting while also maintaining the scientific background needed to properly assess the phenomenon. Grey literature was included as scoping the literature was to be comprehensive as possible (Paré and Kitsiou, 2017). General comments made on the reports or blog posts were not included due to their general, opinionated positions.

Once all the literature was scanned through and picked, interpreting the data was the next approach. To narrow the large amounts of data present in the literature, coding was conducted.

Coding is the process of breaking down data and rearranging them into categories that facilitate comparison between things in the same category which will then aid in the development of theoretical concepts (Maxwell, 2013, Chapter 5). With grounded theory, coding starts early in the data collection process and continues until the analytical interpretation is fully developed (S.

Hagerman, personal communication, October 17, 2018 and October 31, 2018; Charmaz, 2006,

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Chapter 1). The process of coding and resulting thematic categories are discussed in further detail in the results portion of the paper.

Global Literature Review on the applications of Virtual Reality in Forestry

Faculty of Science and Forestry