Introduction

The European Landscape Convention of 20 October 2000 defines landscape as “an area as perceived by man, the character of which is the result of the action and interaction of natural and/or human factors”. According to Leser and Löffler (2017), landscape is created in the mind (Fig. 1): it is a construct of what is seen, experienced, learned, and subject-specific models of the earth, biological, and human sciences. Social constructivist approaches to landscape research do not view “landscape” as “objectively” given (Edler et al. 2018).

Fig. 1
figure 1

“Landscape” is created in the mind! (Original Leser 2015; from: Leser and Löffler 2017, modified)

Landscape is “head-born landscape” but at the same time materially manifest. This dichotomy complicates both field research and the representations of the results. The latter include imagery and maps (both terrestrial and remote sensing), as well as analog and digital 3D or 4D models. Harvey (2018) pointed to the interest-driven manipulations of the visual, specifically of maps that represent supposed or actual “reality.” Digital media also alter perceptions of the environment (Barnikel et al. 2014), as do views of maps and aerial photographs.

“Landscape” is a construct of what is seen, experienced, learned, and subject-specific models—in other words, it is born in the mind. This makes it difficult to deal with—be it an object of theory or of research. Additional confusion is caused by the general casual use of language in the media and in public, but also in the various. The term “political landscape” is one example. It describes how politics is dealt with and how politics is placed in various contexts. This has nothing to do with the definition of landscape in geography or landscape ecology.

Users and practitioners deal pragmatically with the complex subject of landscape and with landscape ecological results. This often happens without reflection—both from a methodological (“theoretical”) and methodological (“craft”) point of view. This also applies to the presentation of results. While natural science landscape research is methodologically consolidated, social constructivist approaches to landscape research or the development of new representational techniques, for example, give rise to a plethora of previously unknown methodological practical and theoretical problems: “Often the technical tools created new barriers to access” (Kubicek 2010, p. 190). They appear both as potentials for development and as methodological pitfalls.

Landscape ecology defines landscape as a three-dimensional functional and process structure of all parameters from the fields of nature, society, and technology (Fig. 2) (Kühne 2021). The process structure arranges itself on the time axis. Representations (“illustrations”) can be verbal, pictorial, graphical, or mathematical-statistical. They are space–time functional models. They can appear as word models, pictures, maps sui generis, map-related, and computable representations.

Fig. 2
figure 2

The human–society–environment interaction structure as a space–time system (Modified after Leser and Schneider-Sliwa 1999; original: Leser 1998; from: Leser and Löffler 2017, modified)

The construction “landscape” is a complex structure of relations and effects between the individual human being, his society, and the environment. It is visibly expressed in the spatial pattern of the landscape and its elements. The structure of effects also includes the ecological and socio-economic processes, which are only visible to a limited extent or not visible at all. This structure of effects is looked upon a system.

The real world (“Real” Reality = RR or Objective Reality = OR Physical Reality = PR) is the reference level. Leser and Löffler (2017) provide the basis for this. With the terms Virtual Reality = VR and Augmented Reality = AR, the “head birth landscape” gets a new component both for field research and modeling of landscape ecology as well as for the visualization of “landscape”. It results in methodological and methodical consequences for researchers as well as for practitioners or users (these summarized here as “users”). In this context, this article offers some considerations.

In this article, the “landscape reality” is considered from the perspective of landscape ecology, which is the basis of this work (Leser and Löffler, 2017).

The term “Mixed Reality” (MR) is often imprecisely used. The authentic definition and accompanying figures in the original paper by Milgram et al. (1997, p. 281) make it clear: “[We] classify the relationships between AR and a larger class of technologies which we refer to as “Mixed Reality” (MR) and propose a taxonomy of factors which are important for categorizing various MR display systems.” The authors see AR in the context of a reality-virtuality continuum, “which ranges from completely real environments to completely virtual environments and encompasses a large class of displays which we refer to as “Mixed Reality” (MR).” (Milgram et al. 1997, p. 291). Figure 3 of this paper considers the MR approach without presenting it in extenso.

Fig. 3
figure 3

Ecosystem and habitat—arranged between real landscape, landscape model, and artificial world (original reader 2019)

This article begins with an introduction to the terms used and provides information on the theoretical approach of how the view of landscape can be conceived in relation to virtuality. The article concludes with an overview of methodological and theoretical problems related to a virtual view of landscape.

Terms and Theoretical Foundation

The original idea of the term digitization is the change from analog data format to a digital one. Digital data can be stored and processed electronically. The term digitization is accompanied by the term digitality. According to various authors, it is based on “digital” and “reality/materiality”. Digitality must not be mixed up with the “technical” process of “digitization. The term “digitality” has broken away from the exclusively technical and expanded in the direction of living environments, i.e., toward the subject of cultural studies and the humanities. According to Stalder (2016), this involves the networking of technical-digital-virtual with organic-analog-real (life) worlds. According to Deck (2018), correlations and patterns can be found for them.

Accordingly, this approach does not only apply to the natural and technical sciences, but also to the cultural sciences and the humanities. In each case, explanations or justifications must be found for patterns and correlations. Since the very comprehensive term “digitality” goes beyond the purely technical, it correlates with the holistic approach of landscape ecology and geography, as descriptions of conditions according to the holistic landscape approach also require explanations. These must reach into the processes of the “impact structure landscape”. Methodologically, it is true that a holistic approach and a technical systems analysis approach need not be opposites (Harvey 1997). It is known (see also Deck 2018) that the disciplinary structures of the different approaches “blur.” For example, Mittelstrass (2007) looks upon science systematics as a dynamic structure rather than a rigid one (“transdisciplinarity”). One has to be aware of this openness not only in landscape research, but also in users of landscape ecological models, e.g., in their visualization. The technically oriented user of the landscape ecological approach has to keep in mind that a reference to “landscape” can prove to be both a possibility and a limitation.

Ecological Landscape Research and the Different Realities

There is nothing static about landscape. This is evidenced both by the entire history of the earth (incl. climate change) as well as by cultural landscape change. Landscape ecology primarily researches the current, real existing landscape. However, all sciences of landscape research construct subject-specific, thus diverse models according to subject-specific selected functional, spatial, and temporal aspects. A landscape ecosystem manifested in space can be modeled (i) for the present, (ii) for the past, and (iii) for the future. In the extreme case, future models can be exclusively VR. They are based on speculative to prognostic simulations, represented by different methods.

The current landscape with its development dynamics is a real object. As an "ecosystem landscape", it includes also non-visible material, energetic, social, and economic processes. Humans perceive landscape primarily as a complex objective or physical reality. Landscape can be modeled (i) verbally, (ii) pictorially, (iii) graphically, (iv) cartographically, or (v) mathematically–statistically. Some of these formats allow landscape to be perceived directly or indirectly by the eye, or to be depicted photographically.

This visible, tangible, and literally “graspable” reality only becomes virtual reality (VR) when it is digitally reconstructed: a computer-generated artificial world/landscape/environment is created. It only becomes perceptible, i.e., visible, with data glasses or comparable technical means. Special software also enables people to enter this virtual (artificial) environment/world. For example, he can look around in a virtual work environment to learn about production processes or work safety measures. The present paper excludes this way of using virtual environments. The focus is on imagery, map, map-related representations, and 3D, i.e., pictorial representations of physical reality.

The sui generis landscape ecosystem is discussed in Leser and Löffler (2017, p. 25 and p. 62) (see Fig. 2). Today, the definition of an ecosystem (in the broader sense) or a landscape ecosystem is considered to be open to all sides—for disciplines working in ecology as well as for users from the fields of technology, cartography, and informatics. To achieve discipline-specific goals, models are thinned out: they become “models of models.” Nevertheless, as a model should remain close to reality, it must retain its main features. Decreases in the value of a model result, for example, from oversimplifications of the number or type of components of the “ecosystem” effect structure. Therefore, the main principles of (1) general systems theory (with process models) and (2) ecosystem theory (with nature-human relationships) also apply to users of landscape ecological models.

Ecological landscape research implies landscape change. Geologically, and thus climatically, it is a natural change. Human activities in the Anthropocene (including Ehlers 2008) led to an anthropogenic global change of all parameters of planet Earth. As cultural landscape change, this is primarily the subject of landscape research (including Ewald and Klaus 2012). By representing it in images, maps, and models, many possibilities open, some of which have not yet been worked out. Current and future cartography has to start with these. As an imagined or constructed VR has the potential to visualize what does not yet exist (from a geographic perspective, e.g., for urban, spatial, and landscape planning), new technical procedures for map and imagery representations are consequently needed. However, these must be "readable" for practical use by non-informaticians in the subject sciences.

The “New Landscape Change” caused by climate change is also based on the theory of landscape ecology. Therefore, methodological filters are required for the development and application of new technical procedures:

  1. (1)

    The model of the complex landscape ecosystem with its real existing processes in the landscape is the basis.

  2. (2)

    Consideration is given to the dimensional levels of the systems (local, regional, zonal, and global). These are valid for all spatial–temporal ecological impact structures of the entire planet Earth.

Technical, administrative, or political demands on a project often create methodological pitfalls. Current ecological field research practices also tend to be simplistic for a variety of reasons: People neglect the field in the open field and instead obtain data in the chemophysical laboratory or from existing data offerings or on-screen map displays. Both imply a departure from the ecological reality of the environment and thus of humans: One is no longer at the “Objective Reality” (OR), i.e., the “Real Reality”. Or one reduces the number of process parameters and linkages in the model. Such process reductions distort reality. Behind all this is the methodological paradox that reality cannot be represented 1:1, so it must be modeled.

In this problem, landscape ecology and cartography meet at the level of (i) geographic dimensions and (ii) map scales. The selected object (e.g., landscape, process fabric, etc.) is resolved according to the problem and consequently contains more or less reservoirs, regulators, and processes of the ecological effect fabric. However, with respect to the dimensional level chosen for the object, they are then ascribed definitional character. This procedure corresponds, for example, to the selection process of map content elements when the scale is enlarged or reduced. Ultimately, this also applies to any kind of computer-generated visualization.

Virtual Reality

VR completely replaces the real existing objective physical world (OR). VR is not materially manifested but is simulated and can only be “experienced”. Cruz-Neira (1993): “VR refers to immersive, interactive, multi-sensory, viewer-centered, three-dimensional computer-generated environments and the combination of technologies required to build these environments.” (See also Dörner et al. 2014). VR must therefore be (i) convincingly conceived as an idea and (ii) technically constructed in a way that embeds the user and allows for interactions.

Geography, landscape ecology, and cartography have an identical professional understanding of “landscape”: they assume Objective Reality (OR), i.e., the real existing landscape. However, all three disciplines know about their natural or anthropogenic changes. This is proven by the terms “landscape change" or "cultural landscape change”, which are open in time.

VR is a computer-generated three-dimensional world/environment. It must be trustworthy. This depends upon the accuracy of rendering. From the perspective of geography, landscape ecology, and cartography, an artificial world is generated based on the real world. Different types of software create the computer-generated representation and simultaneous perception of an artificial world (e.g., people environment, landscape) by a "human". With the help of technology (e.g., a mobile device, data glasses, a 3D helmet), he can also act virtually in this virtuality. His behavior, be it demanded of him or be it spontaneous, is due to his real-life experiential background.

The digital VR appears all the more real to the user, the more it is aligned with his “head images" or real-life experiences or appears to be supposedly or actually identical with them. Knowledge Hayek et al. (2016, p. 100): “The level of immersion into the virtual environment depends on the illusion of reality to the senses of a participant”. This compatibility depends upon the sophistication of the software and the data fed into it. The greater the compatibility, the more plausible the sense of perception of this art world and for acting in it.

The exactness of the reproduction depends on the quality of the software, i.e., on the differentiation of the digitally stored details: the user should be given a plausible illusion of a reality. However, there can be conflicts between the visual object perception perceived by the eye and an object of VR, which is present in a different (usually lower) resolution than the human eye allows. Perceptual disturbances occur as side effects, especially if the object or the perceiving person moves. For related ethical problems as well as dangers and risks for individuals and society, see Madary and Metzinger (2016).

Landscapes of distant (“alien”) habitats can be represented as virtual worlds, as well as planned structures and settlements that do not yet exist, unknown interiors of structures, altered cultural spaces, imagined cultural landscape change, landscape forms altered by imaginary processes (e.g., landslides, coastal erosion), geological and hydrological subsurface structures (e.g., sediments, groundwater) hidden by the Earth's surface, future climate-induced vegetation changes, and so on.

Examples of application for architecture were provided by A. Gruen (2008), for urban planning by Al-Kodmany (2002) or Coors et al. (2016) or for “participatory spatial planning” by Wissen et al. (2008), Wissen (2009), Stauskis (2014), Wissen Hayek et al. (2016). Increasingly, learning environments are being developed, e.g., for museum tours or specialized lessons. On e-learning, see Schwan and Buder (2006).

When working in VR, the methodological problems concerning landscape are like working in the real world (OR). For example, it is not sufficient to reconfigure database systems or to extend existing open interfaces to advance to the “object landscape”. From the perspective of landscape ecology and cartography, geographical dimensions (Neef 1967; Leser and Löffler 2017) must be considered above all, because they play a central methodological role for data resolution. For cartography, this results in the problem of the scales to be used for maps or map-like representations. The respective project goals determine the selection of what is considered virtual or real (i.e., non-virtual) for an issue. Overlaps in the weighting of the approaches (i) OR = ”reality” vs. (ii) VR = ”virtual reality” result from augmented reality (AR). The technical aspects excluded in this paper would be output and input devices for displaying virtual spaces and operating in virtual environments.

Augmented Reality

In VR, the user is more or less part of the artificial world, or respectively, he moves within it. In Augmented Reality (AR)—overview by Azuma (1997)—reality is preserved but supplemented by additions. The term AR emerged in the early 1990s (Milgram et al. 1994). It stands between real, objective, or physical reality (OR) and artificial reality (VR). According to Azuma (2017, p. 1), "Augmented Reality (AR) is an immersive experience that superimposes virtual 3D objects upon a user`s direct view of the surrounding real environment, generating the illusion that those virtual objects exist in that space. While Virtual Reality (VR) completely replaces the user’s view of the real world, AR supplements it.” The ER system is meant to be interactive and run to in real time.

With AR, the real world (OR) remains in the center of the user`s perception as an "image" or action space. For geography, landscape ecology, and cartography, the real world exists as a pictorial basis (photo, map, 3D models, film, video, etc.) in analog or digital form. It is extended to AR by targeted computer programs. In this process, computer-generated non-visible or non-existent (i.e., virtual) objects are superimposed on the exterior of a real landscape; at the same time, objects from the real world can also be suppressed or partially changed (Milgram et al. 1994; Gruen 2008).

Specifically, augmentation occurs through the superimposition or insertion of computer-generated objects (imagery, maps, people, motion sequences, etc.). Ecosystem sub-processes, such as material and energy flows, can also be brought in—either as static phenomena (numbers on process arrows) or dynamized (moving and defined shape-changing flow or process arrows). This makes interactive experimentation of ongoing processes possible for research and teaching. However, the application areas of landscape ecology, bioecology, hydrology, pedology, or geology expect a database based on measurements in the real field when working with AR.

AR is about additional information that expands the content of the existing imagery base (Dickmann et al. 2021). From the point of view of cartography, geography, and landscape ecology, it is basically a technical process with a didactic objective for school, all kinds of teaching, communication between authorities, planners, and the population, etc. Examples: Al-Kodmany (2002), Wissen et al. (2008), Manning et al. (2012), Reinwald, Schober, and Damyanovic (2013), Reinwald et al. (2014). More generally on AR use, see Billinghurst et al. (2014).

Further appropriate aspects of AR use include representations of landscape changes due to natural landscape evolution (geological processes, various current geoprocesses) and anthropogenic interventions. These can refer to ongoing processes (e.g., expansion of large mining sites for raw materials) or also to plan landscape changes (also raw material mining, but also settlement development planning [new planning, inner development of places, and development of the outskirts of towns]). Here, cartography, photogrammetry, remote sensing, and architecture meet. Gruen (2008) showed this for numerous objects of quite different spatial dimensions and scales.

In landscape ecology research, AR applications are conceivable in which process flows (site control loop type) are introduced into 3D representations. This is possible statically (control loops in image, block image, map, or map-like representation), but also dynamized. For example, as a 3D landscape model on the time axis (like Fig. 2) with changing values of the input process variables. As a result, this leads to the methodological pitfall of the reduction of processes. It arises not only for the field landscape ecologist, but also for the visualization, i.e., for the “technicians” (geomaticians, cartographers). It must additionally be pointed out that when using AR, problems can also arise for technical reasons (e.g., displays, sensors, and interfaces of the system components). Because of the broad fields of application, countless individual technical and methodological problems occur that can only be identified in the specific projects.

Theoretical and Methodological Problems from the Perspective of Landscape Ecology and Cartography

Dynamics of landscapes means: (i) recording and representing past, (ii) present, and (iii) future developments—be they natural or anthropogenic. They are all the subject of landscape ecology and geography. The consolidation of the field of landscape ecology is evidenced by Steinhardt et al. (2005), Lang and Blaschke (2007), Wiens et al. (2007), Turner and Gardner (2015), Gerold (2016), Leser and Löffler (2017), among others. All of these textbooks also specifically point out numerous open questions in landscape ecological theory. An extreme example is emergence, which is not insignificant for landscape developments (Leser and Löffler 2017, p. 127). Representations of virtual reality, for example, cannot directly enter it, it because emergence is a gradual process and thus difficult to represent in terms of time and function. Its digital representation is currently still open.

Landscape, Map, and Virtual Reality

According to Fig. 1, landscape is a brainchild and thus per se Virtual Reality (VR). This virtual character is expressed in the numerous definitions of “landscape”, which range between the understandings of the professional sciences and those of practitioners to laypersons. Therefore, an “intermediate understanding of landscape” is assumed here without discussion.

In landscape ecology, models of various kinds allow to make the virtual character of the “head birth landscape” visible by means of imagery, number, graphic, map-like representation, or map. However, this is not yet the computer-generated artificial world, the “technical” VR (Fig. 3). The representation programs require extensive data collectives that have still to be defined: the bridge between the real existing process-defined ecosystem in the landscape and its virtual "image" has still to be built.

So far, geography, landscape ecology, and cartography are primarily concerned with making the “construct landscape”—i.e., the head birth—visible (Fig. 3). Visibility is a prerequisite for the use of landscape ecology research products—whether by cartography, neighboring sciences, media, teaching, or practitioners (planning, etc.). Visibility can be achieved in analog or digital form.

The real landscape is materially manifested and endowed with visible and non-visible features and functions. There are different modelings of this fact. They are components of the reality-virtuality continuum.

(0) Simplified image of the visible (unmodeled) real environment. The image symbolizes the model of the ecosystem in the landscape. It is studied as a space–time effect structure by geographic-landscape ecology research for its application in practice—(1) The “Objective Reality” (“Real Reality”) model of the ecosystem in the landscape. It represents the materially manifested visible real landscape. The model is to be used as a (1.1) map-like 3D model (e.g., block image) in landscape ecology research or 3D cartography, or as a (1.2) analog or digitally generated 2D map for cartographic applications of all kinds. (2) The Augmented Reality model. It is based on the Objective Reality model (or its reproductions) augmented. The model is to be used as (2.1) map-like 3D model of landscape ecological reality with visual and/or graphic and/or functional additional components or as (2.2) analog or digitally generated 2D map for cartographic applications of all kinds. (3) Virtual Reality—a technically conceived and digitally constructed artificial reality defined by purpose and goal. It may be based on the Objective Reality model. Other digitally generated "objects" can be implemented into the VR.

Referring to maps, Harvey (2018, partly adopted and modified) expressed: to transmit information, maps, like any image, use the human ability to visually perceive most of all information. Map users often use this information sight unseen, that is, without critical examination of the content. Maps are known to be an “objective” image of reality. But also, these images result from “head births”, ultimately from VR. We must keep in mind that truth and subjectivity are mixed in the map. A geovisual image is difficult to separate from individual perception of geographic facts. Therefore, Harvey recommends more intensive work on the mechanisms of geovisual communication. As maps are created in an interest-driven manner, the door is open to geovisual manipulation of perceptions, attitudes (i.e., opinions), and behaviors. Aspects of trust worthiness and usability are important with respect to map use (Schiewe and Schweer 2013).

Some Considerations Regarding the Problematic Nature for Map Users

Landscape is not only present in the mind, but also materially manifested and thus visible. As a result, landscape can be documented in imagery, maps, and map-related representations. This is also true for strongly transformed landscapes, e.g., by mining, waterway relocations or by climate change. It must now be asked whether the geomatician can only visualize what can be experienced in a realistic way or what is “imaginable”, i.e., conceivable. Likewise, one must ask whether the cartographer dealing with analog or digital maps is served by a purely mental construct. For him, clear methodological references to real existing landscapes must exist. Reason: The geomatician designs VR, and for this, he needs facts based on reality as a basis. It is only then that the technical process description for converting reality into a visualization can take place. However, a visualization depends on which “object landscape” is worked with in a cartographic project (or in a visualization procedure). The same problem also arises in AR, where the virtual occurs only as an addition to the reality represented cartographically and/or pictorially.

Cartography and landscape research belong together. The cartography practitioner, as a user of the landscape model, must deliver an analog or digital product to his "clients". Ultimately, any landscape is suitable for virtuality visualization if there is a regional or technical need for it. However, some principles must be considered:

  • The main components must be a landscape ecology concept based on the theories of landscape ecology (and geography). For this, Leser and Löffler (2017).

  • Landscape research principles applicable to visualization:

  • (1) The ecosystem approach and thus the model of the space-time functional structure of the landscape.

  • (2) The process structure of the landscape, which constitutes the (cultural) landscape change. These processes can be natural, technical (artificial), or anthropogenic in the broad sense (i.e., “non-natural”). Their consideration determines an authentic and plausible visualization of landscapes. However, project-related selection criteria must be defined for these—although applies,

  • (3) that according to the holistic approach of landscape research (simplified: “everything is landscape”), everything in the landscape is ecofunctionally relevant. Nevertheless, topic- or project-related focal points are to be set if required by presentation technique or statement objective:

  • (3.1) Adequate decision ladders are to be designed for this purpose. They aim at landscape change, i.e., at the processes in the landscape.

  • (3.2) The kind of processes in the landscape that should definitely be considered also depends on the defined project focus in a visualization.

  • (3.3) Emphasis can be put on natural, anthropogenic, or technical facts.

  • All results must be of such a nature that in the respective model of AR or VR, the ecosystem remains recognizable as a complex structure of effects of the landscape.

Final Remarks

Now, from the perspective of geography and landscape ecology, it can be asked whether new methodological or theoretical possibilities of experience arise for these two disciplines using the concept of virtual reality. Landscape ecology and geography are based, just as cartography, on the terrestrial and ecologically substantial existing landscape. It is always materially manifested and accounted for by physical, energetic, chemical, and biological processes. Currently available visualizations of landscapes in map, image, or AR are still sufficient for empirical landscape research. VR will only become a geographic-ecological-cartographic working tool when visualizations can fulfill positions (1) to (3). However, if one leaves the area of empirical landscape research, information-technological or landscape-ecological-theoretical development ideas could result from model speculations “in the cloud” for prognoses of future landscape states. From this point of view, at present, the clearly outlined methodological progress regarding VR for image, map, and model still results from the proven extension of OR in the direction of augmented reality (AR).