1 Spatial Modelling of the Terrestrial Environment - Georeferencial

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Modelling the Impact of Traffic Emissions on the Urban Environment 239 Reference case Policy case Low W N E High 1 2 3 4 5 S 0 20 40 60 km Figure 11.4 Index of emissions’ impact on settlement for the reference case (top) and the policy case (bottom) by the concentration. Resulting values were grouped into five classes ranging from low (class 1) to high (class 5). Whilst a very large number of possible indices might suggest themselves for this purpose, it was felt that a simple but robust measure was in keeping with the underlying emissions model which was designed for screening rather than detailed, accurate analysis. Figure 11.4 shows the index by ward for both the reference case and the policy case. In the reference case, high levels of exposure are evident along the A14 corridor to the
240 Spatial Modelling of theTerrestrial Environment west of Cambridge and in the vicinity of Huntingdon. Wards with low values along the corridor reflect relatively free-flowing stretches of the A14 with low-settlement density. The dormitory villages west of Cambridge also have fairly high levels, as do the immediate suburbs of the City in the West and East. The policy case reveals that the alternative policy package has achieved noticeable reductions in the A14 corridor, especially in the vicinity of Huntingdon and in suburban West Cambridge. Values also tend to drop in the city centre. Significantly, however, there is a very clear increase of exposure in the A10 corridor in the north of the county, especially in the vicinity of Ely. This is despite the low density, rural population pattern in this area and the wide expanses of open countryside. 11.6 Conclusion To date, remotely sensed data from satellites has seen remarkably little take-up by the planning community despite the fact that the complexities of data processing associated with its use have largely been removed and the costs of data purchase are now extremely low. Land use and transport models have become well established and their use as a basis for policy testing is proved. Emissions modelling exercises, however, are usually carried out by different sectors of the community with little reference to wide area environmental impacts of underlying policy. This research has demonstrated how GIS can provide a powerful basis for integrating these disparate areas of activity, thereby providing a powerful tool for modelling the environmental impacts of different planning policy packages. The Cambridgeshire case study has illustrated the power of the approach in the context of emissions impacts on settlement, but the same techniques could be used in a wide variety of planning and environmental assessment situations. The results of the case study raise a number of interesting questions. In reality, the policies tested are so extreme that it would be almost impossible to implement them within a single plan review period. Despite this, the models suggest that they only achieve a partial solution to the problems of traffic, congestion and emissions in the study area. This suggests that development has a high level of momentum, which makes effective implementation of policy change extremely difficult over relatively short time horizons. Furthermore, although the policies tested have strong sustainability credentials in terms of encouraging reductions in car usage in favour of public transport, the predicted outcomes are not so clearly sustainable. The index of emissions shows a shift of impact away from areas that are heavily populated to more rural areas where development is much less dense. Outcomes measured in terms of the impact on public health might well be very positive but different impact measures based on environmental quality would clearly show a substantial, net deterioration. Equally, it seems clear that from an ecological point of view, the same policy may prove sustainable in the context of one species and quite the opposite in the context of another. Perhaps the ultimate conclusion of this study is that integrated GIS that bring together complex models go far beyond offering approaches to environmental analysis. They can provide the basis for testing and learning about the likely outcomes of policy measures before they are implemented and before their undesirable effects become too difficult to reverse. Unless it can be clearly demonstrated that planning policies really do lead to
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Spatial Modelling of the Terrestria
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Copyright C○ 2004 John Wiley & So
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Contents List of Contributors Prefa
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Contributors Jonathan L. Bamber Sch
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List of Contributors xi George Perr
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xiv Preface in theory and applicati
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2 Spatial Modelling of the Terrestr
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Editorial: Spatial Modelling in Hyd
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Editorial: Spatial Modelling in Hyd
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2 Modelling Ice Sheet Dynamics with
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Modelling Ice Sheet Dynamics by Sat
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36 Spatial Modelling of the Terrest
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4 Using Coupled Land Surface and Mi
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Coupled Land Surface and Microwave
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100 Spatial Modelling of the Terres
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Editorial: Terrestrial Sediment and
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Editorial: Terrestrial Sediment and
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6 Remotely Sensed Topographic Data
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Remotely Sensed Topographic Data fo
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7 Modelling Wind Erosion and Dust E
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Modelling Wind Erosion and Dust Emi
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8 Near Real-Time Modelling of Regio
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Near Real-Time Modelling of Regiona
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High Low TSM Concentration Figure 8
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9 Estimation of Energy Emissions, F
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Fireline Intensity and Biomass Cons
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Page 194 and 195: Figure 9.4 The upper row shows EOS
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Page 248 and 249: PART IV CURRENT CHALLENGES AND FUTU
Page 272 and 273: 268 Index Bi-spectral InfraRed Dete
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1 Spatial Modelling of the Terrestrial Environment - Georeferencial

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