8 <strong>Calibration</strong> <strong>and</strong> <strong>validation</strong> <strong>of</strong> <strong>the</strong> L<strong>and</strong> Use Scanner allocation algorithms
Summary The present report describes <strong>the</strong> calibration <strong>and</strong> <strong>validation</strong> <strong>of</strong> <strong>the</strong> spatial allocation performance <strong>of</strong> <strong>the</strong> renewed L<strong>and</strong> Use Scanner. The new version <strong>of</strong>fers a range <strong>of</strong> resolutions <strong>and</strong> different allocation algorithms at which simulation is possible. The focus will be on <strong>the</strong> most detailed resolution (100 metres) <strong>and</strong> <strong>the</strong> new allocation algorithm that <strong>use</strong>s a discrete specification <strong>of</strong> l<strong>and</strong> <strong>use</strong> per grid cell. This new approach describes only one type <strong>of</strong> l<strong>and</strong> <strong>use</strong> per cell, as opposed to <strong>the</strong> fractional (probability) description <strong>of</strong> all possible l<strong>and</strong>-<strong>use</strong> types in <strong>the</strong> original, continuous version <strong>of</strong> <strong>the</strong> model. The main objectives <strong>of</strong> <strong>the</strong> present analysis are: 1) to assess <strong>the</strong> potential <strong>of</strong> <strong>the</strong> new fine resolution in producing sensible l<strong>and</strong>-<strong>use</strong> patterns, <strong>and</strong> 2) to compare <strong>the</strong> performance <strong>of</strong> <strong>the</strong> two available algorithms. Fur<strong>the</strong>rmore, <strong>the</strong> most important location factors in <strong>the</strong> suitability map definition are pinpointed. For this analysis, a simplified model configuration is <strong>use</strong>d, that <strong>use</strong>s nine major types <strong>of</strong> l<strong>and</strong> <strong>use</strong>. Starting point for <strong>the</strong> calibration is <strong>the</strong> 1993 l<strong>and</strong> <strong>use</strong>. With multinomial logistic regression analysis, different sets <strong>of</strong> statistical relations are established, that describe <strong>the</strong> l<strong>and</strong>-<strong>use</strong> configuration in 1993. These relations are subsequently <strong>use</strong>d to simulate <strong>the</strong> l<strong>and</strong> <strong>use</strong> in 2000. A pixel-by-pixel comparison <strong>of</strong> <strong>the</strong> actual, observed l<strong>and</strong> <strong>use</strong> in 2000 to <strong>the</strong> simulated l<strong>and</strong> <strong>use</strong>, indicates <strong>the</strong> performance <strong>of</strong> <strong>the</strong> model. The initial calibration exercise, which <strong>use</strong>s <strong>the</strong> current (1993) l<strong>and</strong> <strong>use</strong> as an indication <strong>of</strong> l<strong>and</strong>-<strong>use</strong> suitability, proves that <strong>the</strong> model is able to exactly reproduce existing l<strong>and</strong>-<strong>use</strong> patterns. This shows that <strong>the</strong> allocation procedure is working correctly; for each l<strong>and</strong>-<strong>use</strong> type <strong>the</strong> proper amounts <strong>and</strong> locations are <strong>use</strong>d. In this respect, it is interesting to note that simulation starts with an empty map. The simulation reproduces current l<strong>and</strong> <strong>use</strong> by properly describing suitable locations, not through fixing l<strong>and</strong> <strong>use</strong>s at <strong>the</strong>ir present location, as o<strong>the</strong>r models do. This has <strong>the</strong> important advantage <strong>of</strong> making <strong>the</strong> model extremely flexible in producing simulations <strong>of</strong> future l<strong>and</strong> <strong>use</strong>. This characteristic makes <strong>the</strong> model very suited to simulate <strong>the</strong> l<strong>and</strong>-<strong>use</strong> patterns that may result from specified scenario conditions or policy objectives. The <strong>validation</strong> results relating to <strong>the</strong> statistically derived suitability maps show that <strong>the</strong> model performs relatively well in simulating agricultural l<strong>and</strong> <strong>use</strong> <strong>and</strong> nature. For <strong>the</strong> more urban categories (recreation, residential <strong>and</strong> commercial l<strong>and</strong> <strong>use</strong>) <strong>the</strong> model performs less well. This may partly be due to limitations <strong>of</strong> <strong>the</strong> available data sets <strong>and</strong> <strong>the</strong> applied statistical analysis. Inclusion <strong>of</strong> more detailed <strong>and</strong> more specific explanatory variables (related to, for example, spatial planning <strong>and</strong> accessibility) <strong>and</strong> a focus on <strong>the</strong> explanation <strong>of</strong> recent l<strong>and</strong><strong>use</strong> changes may help to improve <strong>the</strong> performance <strong>of</strong> <strong>the</strong> model in this respect. On a more fundamental level, however, it is clear that socioeconomic developments will always have a large degree <strong>of</strong> uncertainty. Not even <strong>the</strong> most rigorous calibration <strong>of</strong>fers any guarantee for producing <strong>the</strong> ‘right’ simulations <strong>of</strong> future l<strong>and</strong> <strong>use</strong>. To cope with this large degree <strong>of</strong> uncertainty, most socioeconomic outlooks on <strong>the</strong> future apply <strong>the</strong> scenario method. This implies that <strong>the</strong> model nei<strong>the</strong>r has to replicate past developments, nor has to produce <strong>the</strong> most probable l<strong>and</strong><strong>use</strong> pattern. It should, first <strong>and</strong> foremost, be able to produce possible spatial patterns that match <strong>the</strong> anticipated future conditions set out in scenarios or spatial policy objectives. And, as was discussed above, <strong>the</strong> model is indeed well-suited to do just that. Fur<strong>the</strong>rmore, this means that <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> model should not be interpreted as fixed predictions for particular locations, but ra<strong>the</strong>r as probable spatial patterns. The <strong>validation</strong>, fur<strong>the</strong>rmore, shows that <strong>the</strong> two allocation mechanisms, given equal starting points, provide very similar l<strong>and</strong>-<strong>use</strong> patterns. The new discrete allocation method proved to be very powerful in solving <strong>the</strong> very large optimisation problem at h<strong>and</strong>. The applied algorithm finds an exact solution with a desktop PC within several minutes, provided that a feasible solution exists. This calculation time is comparable to <strong>the</strong> original continuous model. This is an impressive result, as we do not know comparable complex optimisation models that are able to provide such fast results. The current calibration <strong>and</strong> <strong>validation</strong> study foc<strong>use</strong>s on <strong>the</strong> ability <strong>of</strong> <strong>the</strong> model to provide sensible spatial patterns <strong>and</strong> does not consider additional modelling aspects that influence <strong>the</strong> simulation results. These relate, first <strong>and</strong> foremost, to <strong>the</strong> amount <strong>of</strong> l<strong>and</strong>-<strong>use</strong> change that is <strong>use</strong>d in simulations <strong>and</strong>, more generally, to <strong>the</strong> complete modelling chain in which <strong>the</strong> L<strong>and</strong> Use Scanner is applied. The importance <strong>of</strong> <strong>the</strong>se issues is briefly discussed in <strong>the</strong> last section <strong>of</strong> this report. The model improvement project that <strong>the</strong> Ne<strong>the</strong>rl<strong>and</strong>s Environmental Assessment Agency started in 2008, however, pays specific attention to this <strong>and</strong> o<strong>the</strong>r more conceptual modelling issues. In general, we conclude that <strong>the</strong> model is able to produce meaningful l<strong>and</strong>-<strong>use</strong> patterns that match prescribed condi- Summary 9