Ecosystem forecasting is supported by information visualization, e.g.
- Visualization of Data, Indicators, and Thresholds
- Collaborative Problem-Solving — Process Visualization & Management
- Navigation and Search — User Interface & Knowledge Management Frameworks
- Geospatial Visualization — Spatio-Temporal Representations
Visualization Of Data, Indicators, And Thresholds
Outstanding visualization is the key to understanding how components interact in a complex system. Tim Nyerges reviews the challenge of visualizing sustainability in his paper: “Linked Visualizations in Sustainability Modeling: An Approach Using Participatory GIS for Decision Support.”
Three visualizations representing sustainability issues:
1. Concept mapping. The diagram below, used by the USGS Decision Support Systems (DSS) team for Tahoe demonstrates how visualization can show complex relationships. The USGS DSS team has used concept maps to analyze a range of factors affecting the Tahoe Basin (Halsing, Hessenflow, and Wein 2004), associated with the Tahoe Constrained Optimization Model (TCOM) (Bernknopf et al. 2003).
Example of visual conceptual models developed for indicator analysis.
In the directed graph above, nodes represent:
The arrows show the direction of impact (A affects B). Such a graph is both a thinking tool (as it is produced and revised), a communication tool (to show links between data and indicators). It can become a user interface, with clickable nodes to navigate to relevant knowledge resources. It is quickly apparent that this ecosystem is so complex that no representation could capture all indicators or relationships. But such a concept map is a starting point.
- target category indicators,
- subordinate indicators affected by the primary indicators,
- control indicators, and
- threshold indicators.
2. Imagery in a Knowledge Framework. Overlaid on indicators of environmental quality are dynamics of interactive systems, visualized below. Rao created a visualization that counterposes consumptions (energy, water, food, materials) with impacts (on land use degradation, pollution, biodiversity, and climate change). Here again, no imagery could cover the full complexity of interacting systems, Rao's aim was to create a representation that could convey to the general public the interdependency of environmental indicators.
3. A Scenario-Builder. Tamara Munzer has explored ways to visualize and map large amounts of information. Matt Williams, under Munzer's supervision, is developing QuestVis, a tool for users to compare future environmental sustainability scenarios, given particular decisions. Since the space of all input and output factors is huge, and potential associations complex, exploration through the space of future scenarios is not easily understood. Williams’ mock-up shows input decisions (left) and corresponding results (grid at the bottom).
||QuestVis shows the complexity of some of the
interacting variables for sustainability
Collaborative problem-solving — Process management shifts from structuring knowledge to structuring process, from traditional critical path flow diagrams to bar charts, visual representations support process management.
||The triple loop (after Escher) diagrams how issues, actions addressing those issues, and impacts are co-related.
NAVIGATION AND SEARCH
Design of the user interface sits on the foundation of the Knowledge Management Framework (KMF). Studies of navigation and information representation offer a range of ideas for navigation schemas. Pacific National Laboratories research on ways to categorize documents shows the challenge of this task, e.g.
ThemeRiver™ visualization helps users identify time-related patterns, trends, and relationships across a large collection of documents. Themes in a collection are represented by a "river" that flows left to right through time. The river widens or narrows to depict changes in the collective strength of selected themes in the underlying documents. Individual themes are represented as colored "currents" flowing within the river. Theme currents narrow or widen to indicate changes in individual theme strength at any point in time.
Geospatial visualization of natural phenomena is complemented by information visualization to support ecosystem forecasting. Knowledge about the impact of human interventions on a complex ecosystem is a prerequisite for collaborative decision-making. It has been said that 80% of information contains locational content, even more for environmental information, which describes physical, biological, and social conditions as they vary with location. Mapped data is easier to interpret and a powerful medium for communication. Examples of geovisualization applied to environmental analysis:
- Aerial imagery is used as a context or backdrop to depict a region, as in the view of South Lake Tahoe. Urbanized lands are easily distinguished from undeveloped zones, adjacent to streams, floodplains, or other wetlands. A marina /residential development is clearly visible. This visualization enables environmental analysts to spot risks, e.g. of water pollution, flood hazards, or encroachment on wetland resources.
- Overlay of a road system on a SPOT image shows elements under review in context, enabling analysts to locate yet-to-be identified environmental resources, e.g. to study the impact of a transportation network on stream corridors.
- A map, assembled from a variety of servers (using OGC interoperable interfaces), overlays parks, protected areas, and ecologically sensitive zones, with jurisdictional boundaries, so it can be used to coordinate management of sensitive areas.
- Predictive tools guide decision makers managing development or impending threats, e.g. data visualized on invasive species. GIS helps determine which areas have a microclimate similar to an invasive species’ native habitat, signaling risk of future infestation.
- OGC has initiated development of decision support tools for compilation and integration of multiple datatypes, markup, and annotation, and vendor-neutral, interoperable interfaces, e.g. a mockup showing how such a tool would be used in a hypothetical road design scenario.
|1. Landsat image of the South Lake Tahoe region. Source: NASA
2. Local roads and highways superimposed on SPOT imagery. Source: BASIC 3. Parks, protected areas, and ecological zones of Canada, with government boundaries. Source: OGC. Data view produced by the National Forest Information System, Canadian Forest Service. 4. Forest invasion by exotic bark beetles. Green dots indicate collections of native beetles, yellow represents exotics, and red shows where exotics are not yet established. Source: OGC
User. Data view produced by the Canadian National Forest Information System. 5. Markups, annotations and multiple data types in a mocked-up decision support system for environmental planning.
FUTURE DIRECTIONS. Our pilot project on Tahoe Basin ecosystem forecasting and restoration planning is an ideal testbed to integrate Decision Support Systems that can later be replicated elsewhere. Because understanding the Tahoe Basin requires visualizing its complex system of variables as a whole, with all of its physical components dynamically linked and naturally constrained, an integrated decision support framework needs capacity for
- Linking models to simulate alternative impacts given indicator changes. Once calibrated, the urbanization model, together with other linked models addressing many indicators in the Basin, will be useful for Ecosystem Forecasting and for projecting “what if?” scenarios for the Tahoe Basin for given sets of variables and growth scenarios. Future capacity for scenario-building will allow planners to try out alternative hypotheses and associated decision sets to observe how scenarios play out in a simulated environment and explore outcomes, intentional or not.
- Animation of alternative urbanization scenarios. USGS is developing a geodynamic database to document land use changes in the Tahoe Basin since the Gold Rush. Data will then be used to construct an animation that shows the extent and pace of urbanization in the region. TRPA plans to implement a computer model of urbanization calibrated with historic data. Once calibrated, the model will be useful for Ecosystem Forecasting, projecting changes in the state of the Tahoe Basin for a given set of variables and growth scenarios.
- Multi-scale views: in and out zooming. Integrated planning requires capacity to see systems at all relevant scales. The challenge is to recognize the ranges-of-scale relevant for each planning/ management question through integration-modeling methods and advanced GIS spatial analysis and visualization techniques.
- Knowledge domain visualization. Beyond the organization of geo-spatial data and its links, knowledge domain visualizations give users a way to identify research areas, experts, institutions, grants, publications, journals, etc. in their area of interest. In addition, they can assist to identify interconnections, the import and export of research between fields, the dynamics (speed of growth, diversification) of scientific fields, scientific and social networks, and the impact of strategic and applied research funding programs etc.
- Process maps: status of collaborative problem-solving. Visualization of problem information is seldom adequately complemented by visualization of the problem-solving process. Information visualization goes beyond viewing static data to enable users to collaborate and to control and update the environment. It offers simple ways to navigate through information so the user can see where he and other users are on a map of their collaborative problem-solving process.