Landscape Modelling and Visualisation for Environmental Planning in Intensive Agricultural Areas Andrew LOVETT, Sylvia HERRMANN, Katy APPLETON and Thomas WINTER 1 Introduction Recent developments in computer technology and the availability of digital databases have made it much easier to generate landscape visualisations that can be used to support decision making on environmental issues (ERVIN & HASBROUCK, 2001; APPLETON ET AL., 2002). One application of such techniques has been to generate landscape scenes illustrating the impacts of particular policy scenarios for use in discussions with stakeholders regarding future management options (e.g. DOLMAN ET AL., 2001; LOVETT ET AL., 2002a; CHEN ET AL., 2002). Two common limitations of this approach, however, are that the translation of descriptive scenarios into visualisations is often somewhat subjective and there is a lack of other information on landscape impacts that can be presented to stakeholders alongside the visual images. This chapter presents the initial results of a collaborative British-German project that is seeking to tackle these issues by linking GIS, modelling and visualisation tools to assess agricultural policy scenarios in two regions characterised by intensive arable production. The research builds upon previous work by members of the project team (e.g. HERRMANN & OSINSKI, 1999; DABBERT ET AL., 1999; LOVETT ET AL., 2002b; APPLETON, 2003) and involves study areas in the Kraichgau region of Baden- Wuerttemberg, Germany and the River Wissey catchment in Norfolk, UK. In both areas, a GIS database is being assembled that includes a digital terrain model, details of field boundaries with crop information, and soil characteristics. A subsequent modelling stage focuses on estimating the implications of changes in farming practices in terms of both economic consequences and outcomes such as soil erosion or nitrate pollution levels. This work is being carried out with GIS-linked software tools, and the next element of the study involves importing the results into Visual Nature Studio (http://www.3dnature.com) to generate views of the landscape configurations associated with different outcomes. The final stage of the research will consist of discussions with farmers and other rural stakeholders in both regions to assess the contribution of such an integrated approach as part of more participatory approaches to environmental planning in agricultural areas. A landscape modelling approach developed for the Kraichgau region is described in the next section of this chapter. This is followed by a discussion of the work currently in progress to implement the model within part of the Wissey catchment. Particular attention is given to the construction of a GIS database, visualisation of the current landscape and estimation of the economic consequences of implementing runoff control measures. Further elements of the study are outlined in the final section of the chapter, along with an assessment of the merits of this approach to landscape modelling and planning.
2 A. Lovett, S. Herrmann, K. Appleton and T. Winter 2 The Kraichgau Landscape Model The Kraichgau extends over an area of approximately 45 km by 40 km in the north-western part of Baden-Wuerttemberg (see Fig. 1). As a result of a combination of relatively high average annual temperature (9 C), an average rainfall of 700 mm per year and extremely fertile soils (Loess), the area has had a long tradition of agricultural use. In much of the region, land consolidation and modern agricultural techniques have led to a reduction in the use of terracing and, despite the hilly topography, many areas are now characterised by large arable fields, with significant volumes of root crops and only a few remaining landscape elements such as hedges (see Fig. 2). Under these conditions, run-off, causing erosion and consequent flooding, has become an increasing problem. Fig. 1: Location of the Kraichgau within Baden-Wuerttemberg, Germany
Landscape Modeling and Visualisation in Intensive Agricultural Areas 3 Fig. 2: A typical Kraichgau landscape (view towards Massenbachhausen) A landscape modelling system has been developed for the Kraichgau region that incorporates both economic and ecological factors (see Fig. 3). The modules are accessed through a common user interface and utilise GIS software (ArcView and ArcInfo) for data storage, linking of modelling components and mapping of results. Fig. 3: The Kraichgau landscape modelling system
4 A. Lovett, S. Herrmann, K. Appleton and T. Winter Several of the modules operate at the regional level (e.g. optimisation routines for agricultural land use), but the spatially explicit data within the GIS enables results to be transferred to the local level. This approach has allowed a number of different scenarios in terms of changes in agricultural returns, land uses and management practices to be evaluated in terms of their landscape impacts (e.g. DABBERT ET AL., 1999; HERRMANN, 2001; HERRMANN ET AL., 2003) 3 Implementing the Landscape Model in Norfolk, UK The UK research is focused on the upper catchment of the River Wissey in Norfolk. This locality is part of the region covered by the Norfolk Arable Land Management Initiative (NALMI), one of nine pilot projects funded by the UK Countryside Agency to work with local communities and demonstrate how farming systems can respond to the changing demands on agriculture in ways that will generate economic, environmental and social improvements (see http://www.countryside.gov.uk/farming/farming_04.htm). Fig. 4 shows the location of the catchment within the 13 parishes that constitute the NALMI region. Fig. 4: Location of the Wissey catchment, Norfolk, UK Agriculture in the region is similar to the Kraichgau in terms of the crops grown (e.g. cereals, sugar beet and various vegetables), but in other respects the area is less hilly and has larger farms with more prominent hedgerows subdividing the landscape. Fig. 5 shows
Landscape Modeling and Visualisation in Intensive Agricultural Areas 5 an aerial view looking north across the Wissey valley and provides a sense of the patchwork character of the landscape. Fig. 5: Aerial view across the Wissey valley In order to apply the Kraichgau modelling tools, it was first necessary to construct a GIS database for the upper Wissey catchment. Ordnance Survey (OS) Landline vector maps and Landform Profile elevation data (see http://www.ordnancesurvey.co.uk) were used as a basic framework, and other crop or management details were added through a combination of fieldwork in summer 2001 and information provided by local farmers. Fig. 6 illustrates the resulting land use information for the area highlighted in Fig. 5. The River Wissey flows west to east across the top half of the map and the village in the north east quadrant is Bradenham. Visualisations of the current landscape are being produced by importing the GIS data into Visual Nature Studio. This software renders still images from defined camera viewpoints and has particular strengths for the purposes of this research in terms of its ability to represent vegetation (either as textures or through combinations of bitmap images) and micro-scale variations in terrain. Another key capability is that for scenario modelling which allows different feature attributes stored in GIS data to be used to automatically vary the visual properties assigned to landscape elements (e.g. fields). Fig. 7 presents a
6 A. Lovett, S. Herrmann, K. Appleton and T. Winter representation of the current landscape looking south east across the Wissey valley (V1 in Fig. 6) and Fig. 8 shows a ground-level view looking down slope (V2 in Fig. 6). Fig. 6: Land use in part of the Wissey catchment near Bradenham, summer 2001 Land use information from the GIS database is currently being used to model the economic implications of adopting minimum tillage (mulch seeding) strategies and reducing field sizes on three farms. It is also planned to model the impacts of measures to reduce field runoff and soil erosion. The visualisation software will then be used to produce representations of the landscape changes associated with these options. As a result of this work, it should be feasible to provide farmers and other stakeholders with an integrated combination of modelling results and visualisations for a variety of scenarios, and hopefully improve the communication of information in ways that will ultimately benefit the environmental management of agricultural areas.
Landscape Modeling and Visualisation in Intensive Agricultural Areas 7 Fig. 7: VNS visualisation looking south east across the Wissey valley Fig. 8: VNS visualisation looking down slope towards the River Wissey 4 Conclusions This chapter has described initial work on a project to link GIS, modelling tools and visualisation techniques to provide an enhanced basis for environmental planning in intensive agricultural areas. To date, the research has focused more on the UK study area, but it is also intended to apply the visualisation techniques to GIS databases and modelling
8 A. Lovett, S. Herrmann, K. Appleton and T. Winter results that already exist for part of the Kraichgau. This will enable the effectiveness of the approach to be compared in two areas which share an emphasis on intensive agricultural production, but differ in their farm structure and environmental characteristics such as topography. The idea of linking modelling and visualisation tools is not itself novel (e.g. see BISHOP & KARADAGLIS, 1997), but operational examples of such decision support systems do not seem especially common. In many rural areas of Europe there now appears a particular need for such integrated tools due the difficulties of reconciling economic and environmental objectives within the context of substantial farm restructuring driven by changes in national and EU agricultural polices. More generally, it has been recognised that the increasing sophistication of visualisations only accentuates the need for transparency and defensibility in production processes (ORLAND ET AL., 2001; SHEPPARD, 2001). Closer integration of modelling and visualisation tools could well help to address this issue and so provide an important way forward for landscape planning. 5 Acknowledgements This research has been primarily funded by the British German Academic Research Collaboration Programme (ARC Project 1201). Additional support for Katy Appleton has been provided by a grant from the UK Economic and Social Research Council for a Programme on Environmental Decision Making based at the Centre for Social and Economic Research on the Global Environment (CSERGE) at the University of East Anglia. We would also like to thank Gilla Sünnenberg and Trudie Dockerty for their work on the NALMI land use database, Antonia-Jane Weston for taking aerial photographs of the Norfolk study area, and John Terry (NALMI Project Officer) for his help in many respects. All UK maps are derived from Ordnance Survey digital data, Crown copyright Ordnance Survey. The provision of these data is an EDINA Digimap/JISC supplied service. 6 References Appleton, K.J. (2003): GIS-Based Landscape Visualisation for Environmental Management. PhD Thesis, University of East Anglia, Norwich. Appleton, K.J., A.A. Lovett, G. Sünnenberg, & T.L. Dockerty (2002): Rural landscape visualisation from GIS databases: a comparison of approaches, options and problems. Computers, Environment and Urban Systems, 26: 141-162. Bishop, I.D., & C. Karadaglis (1997): Linking modelling and visualisation for natural resources management. Environment and Planning B: Planning and Design, 24: 345-358. Chen, X., I.D. Bishop & A.R. Abdul Hamid (2002): Community exploration of changing landscape values: the role of the virtual environment. In: Proceedings of DICTA2002 Digital Image Computing Techniques and Applications. Melbourne, pp. 273-278.
Landscape Modeling and Visualisation in Intensive Agricultural Areas 9 Dabbert, S., S. Herrmann, G. Kaule & M. Sommer (1999): Landschaftsmodellierung für die Umweltplanung. Springer, Berlin. Dolman, P., A.A. Lovett, T. O Riordan, & D. Cobb (2001): Designing whole landscapes. Landscape Research, 26: 305-335. Ervin, S.M., & H.H. Hasbrouck (2001): Landscape Modeling: Digital Techniques for Landscape Visualization. McGraw-Hill, New York. Herrman, S., & E. Osinski (1999): Planning sustainable land use in rural areas at different spatial levels using GIS and modelling tools. Landscape & Urban Planning, 46: 93-111. Herrmann, S. (2001): Entscheidungsunterstuetzung in der Landnutzungsplanung mittels GIS-gestuetzter Modellierung - Massstabsbezug, Realitaetsnaehe und Praxisrelevanz. Der Andere Verlag, Osnabrüuck. Herrmann, S., S. Dabbert & H-G. Schwartz-von Raumer (2003): Threshold values for nature protection areas as indicators for biodiversity a regional evaluation of economic and ecological consequences, to appear in Agriculture, Ecosystems and Environment. Lovett, A., R. Kennaway, G. Sünnenberg, D. Cobb, P. Dolman, T. O Riordan, & D. Arnold (2002a): Visualizing sustainable agricultural landscapes. In: P. Fisher and D. Unwin (eds) Virtual Reality in Geography. Taylor & Francis, London, pp.102-130. Lovett, A., G. Sünnenberg & T. Dockerty (2002b): Landscape Change in the NALMI Area: Construction of a GIS Database. Jackson Environment Institute Working Paper 15, University of East Anglia, Norwich. Orland, B., K. Budthimedhee & J. Uusitalo (2001): Considering virtual worlds as representations of landscape realities and as tools for landscape planning. Landscape and Urban Planning, 54: 139-148. Sheppard, S.R.J (2001): Guidance for crystal ball gazers: developing a code of ethics for landscape visualization. Landscape and Urban Planning, 54: 183-189. thesda, MA 20814, USA, in particular Chapter 5 (Molander, C.W.: Photogrammetry)