1 Spatial Modelling of the Terrestrial Environment - Georeferencial

264 Spatial Modelling of the Terrestrial Environment
components of many spatial modelling frameworks. Furthermore, from the eleven contributions,
three key research issues recur throughout the book as important components that
affect spatial modelling activities and require further research or technological advancement
for the modelling science to develop significantly. First, the development of improved
digital elevation models, second, the accurate representation of vegetation in models and
third, the need to better understand the impact of spatial resolution on model prediction.
We expand on each of these three issues in the next three sub-sections.
13.2.1 Digital Elevation Models (DEM): Improved Accuracy
and Error Characterization
The need for accurate DEMs in spatial modelling of terrestrial processes is particularly
important in the natural environmental sciences. In Bamber’s chapter, accurate topography
information is shown to be critical for ice sheet modelling and he argues that there is
not enough accurate data to enable us to answer some of the important science questions
relating to ice sheet dynamics and ultimately to global climate change. In this particular
example, elevation data are required to test and verify several types of ice sheet models so
it is important that accurate DEMs are available. With planned new satellite technologies
such as NASA’s ICESat or ESA’s Cryosat missions, the estimation accuracy of topographic
variables (elevation, slope, aspect, etc.) should be increased which, in turn, will improve our
ability to characterize the complex behaviour of ice sheets. At a smaller domain scale, Bates
et al. describe an application to estimate flood inundation using fine spatial resolution DEMs
from satellite and aircraft remote sensing data. These data are used to parameterize hydraulic
models of flood-water flow. In regions where these fine spatial resolution data exist, flood
inundation modelling should result in smaller estimation errors. By testing and validating the
models on well-defined river catchment flood plains, future Earth observation instruments,
with finer spatial resolution, will offer the potential to extend the flood inundation mapping
to more remote regions and at finer spatial scales than can currently be achieved. With
the release of NASA’s Shuttle Radar Topographic Mission data, which provides elevation
information of a large portion of the Earth’s surface in great detail and accuracy, there is a
good potential for increased accuracy of estimates from spatial models of land processes
that use DEMs.
In using DEMs for spatial modelling, it is also apparent that error propagation needs
to be carefully managed. The chapter by Lane et al. demonstrates how relatively small
elevation errors in a DEM that is used in a process erosion model can have a significant
impact on the prediction accuracy of the model. Thus, while increased accuracy of DEMs
are a general requirement by the terrestrial environmental science community, it is also
necessary to better account for the errors that can arise from the derivatives of DEMs when
used in process models.
13.2.2 Vegetation Cover: Improved Characterization
The characterization of vegetation is very important for many spatial models of terrestrial
processes. This is because vegetation often constitutes an important spatially and temporally
dynamic boundary layer in many terrestrial environments. For example, in their chapter on
soil erosion, Drake et al. note that vegetation is a stabilizing factor in the process of soil