LA 341 Fall 1998

Land Suitability: Landscape Evaluation and Understanding -- Beyond Overlay Maps

Readings:
Orland, B., C. Ogleby, H. Campbell, and P. Yates, 1997, Multi-media approaches to visualization of ecosystem dynamics. Proceedings, ASPRS/ACSM/ RT’98 -Seattle, American Society for Photogrammetry and Remote Sensing, Washington, DC. vol 4, pp224-236. View on line.

Orland B., 1997, SmartForest-II: Forest Visual Modeling for Forest Pest Management and Planning. Final Report: USDA Forest Service, FPM-MAG, State and Private Forestry. View on line

The interactions between the vegetative and wildlife components of forest ecology are complex and frequently difficult to communicate.

In bird population models, for example, these interactions include the different responses of different life stages of the bird to habitat structure.
Each of these interactions might include processes that bear simple correlations to each other, exhibit more complex log or U-shape relationships, or include thresholds that determine where activity starts or stops.
Interactive game-like tools offer means for non-biologists to gain better understanding of such processes. Users can manipulate ecosystem parameters and have immediate feedback on the effects of their actions through the use of a graphical display.

Applying visualization to the study of landscape ecology

The introduction of computer-based visualization tools of different kinds has impacted two aspects of the practice of landscape ecology --

the improved understanding of the science underlying the interactions, and
the clearer communication of alternatives to affected publics.

What is missing is any bridging effort to bring and communicate the environmental knowledge and science of landscape ecology to the public decision-making arena.

A map may clearly indicate the extent of an environmental change but cannot indicate the dynamic interactions of ecosystem components nor communicate the experience of being in the landscape.

A hierarchy of graphic tools - I

The lowest order of visualization is the organizing of data into structured tables.

At this level the user can explore simple magnitude relationships but the full burden of integrating and evaluating the data is placed on the reader.

Colored maps as described above, or statistical displays of financial or scientific data use blocks of color to illustrate more complex relationships.

Although still low in the number of dimensions of data that can be exhibited simultaneously, careful choice of color and scales can greatly assist evaluation.

The use of three-dimensional display formats, with color, shade and scale can support the exploration of yet more complex relationships.

Animation of series of such images can be used to include issues of change over time.

Applying spatial references to the three prime dimensions of the graphic display expands the capability of the visualization to include the "walk-throughs" or "fly-overs" of computer graphic environments commonly used in environmental design and planning.

Photo-realistic renditions of future developments are becoming common.

While expensive to create these images can do much to convey the direct experience of an environment.
Unlike other media they enable qualitative as well as quantitative evaluations.

A hierarchy of graphic tools - II

The hierarchy does appear to address many of the sorts of issues that environmental evaluation might be expected to raise. There appear to be tools to support simple as well as complex issues, qualitative as well as quantitative appraisals.

However, while these tools facilitate the delivery of information about the outcomes of environmental processes they are limited in their ability to promote understanding of the many interactions that occur in the dynamics of ecosystem change.

A next highest level of visualization should enable the user to interact with the system under examination and be able to experiment. Interactive game-like visualizations enable the user to examine the effects of interactively changing environmental parameters. The intent is to deepen knowledge by experiencing the effects of non-linear, discontinuous and unevenly weighted interactions.

Objections to the use of visualization - I

While visualization and interactive game-playing appear to have significant benefits to ecosystem understanding and management, there are several significant objections.

1. Critics object that the use of computer-video simulations will result in decisions being made on strength of visual images alone.

However, an equally powerful argument is that the ONLY way we can ensure experts and public groups visualize the same future is to show them the same future.
Techniques enable non-visual ecosystem characteristics such as stress, vigor, pathogen risk and fire hazard to be shown in the same setting as the evident and sometimes misleading size and color of the vegetation.
The implied question of whether visualization should be contained in some way may already be moot when visual media are so widely used in settings such as advertising and political campaigning.

2. Computer visualization results in very concrete images which may lead viewers to believe they are "true."

More abstract media such as maps and graphs benefit from more looseness in interpretation. Imperfect matches between predicted futures and real outcomes can be more easily accommodated by this loose fit.
With a realistic image there is the danger that a given image takes on the role of a performance standard, or in issues of visual quality an aesthetic contract between agency and public interests.
Computer visualization may have to explicitly demonstrate its standards of accuracy and reliability in ways not currently demanded of more abstract media.
The net result, however, will be a benefit -- more "truth-in-advertising."

3. Computer visualizations are subject to incompleteness, inconsistent ìgrainî and plain bad information in the underlying data.

To achieve a complete visual image it is frequently necessary to fabricate or manipulate missing or inappropriate data, and hence open the process to criticism of bias.
This situation must continue to exist but the creation of demonstrable links to underlying data and metadata describing the reliability of the visualization is a priority.
Users acknowledge that the demands of our litigious society require the ability to accurately and reliably describe the information on which we base out decisions.

An example interactive visualization

SmartForest demonstrated the concept of integrating multiple ecosystem sub-models in a single visualization environment where users could "play" the responses of forest structure to, say, insect herbivory, and the responses of insect populations to changes in forest structure.

SmartForest is underlain by interacting ecosystem models so that as one component changes, all the others flex in response. The fundamental core of SmartForest is a tree list describing the large woody component of the forest. Other sub-models take input from the forest development core and react.

The Goshawk model developed in the Imaging Systems Laboratory was based on published work by Fischer (1986), Hayward et al., (1990), Kenward and Widen (1989), and Reynolds et al. (1991). The initial model was developed using the STELLA visual modeling package (High Performance Systems, 1990).

The Powerful Owl -- I

The Powerful Owl (Ninox strenua) is a large (26" (65cm)) bird inhabiting high altitude forest and preying on a variety of arboreal creatures. It is susceptible to changes in habitat composition such as: Nest Stand Size (hectares per nest), Overstory average tree diameter (DBH), Trees per hectare, Basal Area, Height of dominant trees (mtrs.), Canopy closure (% ground coverage), Understory Canopy (% ground coverage), and Snags (# standing dead trees per hectare.)

To accommodate the constraints of the edutainment context of the museum a subset of forest characteristics was chosen for manipulation -- Trees/hectare, Tree diameter, Canopy cover.

Macromedia Director 5 was used to develop the visual interface providing an introduction to the Owl and habitat modeling, controls for the model, and interactive displays.

The Powerful Owl -- II

The variables that go into the model can be changed by moving sliders in the Director interface.
The original population model is a dynamic set of equations relating changes in numerous forest characteristics to changes in the resident bird population.
Adjusting the values of the three forest variables causes the model to run and return a set of population values which are used by the Director program to create the population map and graph.
While running a habitat "map" is constantly updated with distributions of fledgling, young, and reproducing adults to represent the dynamics of the population until at the end of five annual cycles the population graph is plotted to show the accumulated values.

Discussion

In both Goshawk and the Owl examples users can interact with the system under examination and experiment with changing the input variables.

It is possible for users, especially in the latter example, to rapidly experiment with many combinations and begin to find thresholds and other interactions that characterize these complex ecosystem dynamics.

The population ìmapî shows the population of owls at each one-month time step in a five year cycle and gives the user a strong impression of how the population changes as the new brood of eggs hatches and matures into the adult population.

The graph accumulates these one-month snapshots over time. Attempting to produce a flat population by adjusting the input parameters gives users a valuable lesson in how different forest components might contribute to a productive and stable ecosystem.

The interactive game-like visualization is not intended to predict and communicate the actual changes in wildlife population but to engage users in understanding how the ecosystem is working.

Technical details

Original model format: Safia Aggarwal and Brian Orland, Imaging Systems Laboratory, University of Illinois
Modeling computer: Apple Macintosh Quadra 950, 40MB RAM, 1GB disk storage.
Development software: Stella-II, High Performance Systems; SME, International Institute for Ecological Economics
Exhibit conception: Brian Orland and Cliff Ogleby, Department of Geomatics, University of Melbourne.
Exhibit computer: Pentium 166 with Diamond Stealth graphics, 32MB RAM, 1.2GB disk storage.
Exhibit development: Macromedia Director 5, Visual C++. Data storage for this exhibit, 170 MB.
Display programming: Hugh Campbell and Paul Yates, Department of Geomatics, University of Melbourne

Readings for next Monday:

Freyfogle, E.T., 1993. Justice and the Earth. New York: The Free Press. Chapters 1 and 6. 1-17; 113-132.

Goulet, Denis, 1990. Development Ethics and Ecological Wisdom, Chapter 2 in: J. Ronald Engel and Joan Gibb Engel (eds.) Ethics of Environment and Development. Tucson: University of Arizona. 36-49.

Sterling, Stephen R., 1990. Towards an Ecological World View, Chapter 5 in: J. Ronald Engel and Joan Gibb Engel (eds.) Ethics of Environment and Development. Tucson: University of Arizona. 77-86.

Modified: 22 August 1998, Brian Orland

EAST ST LOUIS ACTION RESEARCH PROJECT