Anton Van Rompaey

Complexity and performance of urban expansion models

Abstract Urban expansion and spatial patterns of urban land have a large effect on many socioeconomic and environmental processes. A wide variety of modelling approaches has been introduced to predict and simulate future urban development. These models are often based on the interpretation of various determining factors that are used to create a probability map. The main objective of this paper is to evaluate the performance of different modelling approaches for simulating spatial patterns of urban expansion in Flanders and Brussels in the period 1988–2000. Hereto, a set of urban expansion models with increasing complexity was developed based on: (i) logistic regression equations taking various numbers of determining variables into account, (ii) CA transition rules and (iii) hybrid procedures, combining both approaches. The outcome of each model was validated in order to assess the predictive value of the three modelling approaches and of the different determining variables that were used in the logistic regression models. The results show that a hybrid model structure, integrating (static) determining factors (distance to the main roads, distance to the largest cities, employment potential, slope and zoning status of the land) and (dynamic) neighbourhood interactions produces the most accurate probability map. The study, however, points out that it is not useful to make a statement on the validity of a model based on only one goodness-of-fit measure. When the model results are validated at multiple resolutions, the logistic regression model, which incorporates only two explanatory variables, outperforms both the CA-based model and the hybrid model.

The effect of atmospheric and topographic correction methods on land cover classification accuracy

a b s t r a c t Mapping of vegetation in mountain areas based on remote sensing is obstructed by atmospheric and topo- graphic distortions. A variety of atmospheric and topographic correction methods has been proposed to minimize atmospheric and topographic effects and should in principle lead to a better land cover classi- fication. Only a limited number of atmospheric and topographic combinations has been tested and the effect on class accuracy and on different illumination conditions is not yet researched extensively. The purpose of this study was to evaluate the effect of coupled correction methods on land cover classifica- tion accuracy. Therefore, all combinations of three atmospheric (no atmospheric correction, dark object subtraction and correction based on transmittance functions) and five topographic corrections (no topo- graphic correction, band ratioing, cosine correction, pixel-based Minnaert and pixel-based C-correction) were applied on two acquisitions (2009 and 2010) of a Landsat image in the Romanian Carpathian moun- tains. The accuracies of the fifteen resulting land cover maps were evaluated statistically based on two validation sets: a random validation set and a validation subset containing pixels present in the dif- ference area between the uncorrected classification and one of the fourteen corrected classifications. New insights into the differences in classification accuracy were obtained. First, results showed that all corrected images resulted in higher overall classification accuracies than the uncorrected images. The highest accuracy for the full validation set was achieved after combination of an atmospheric correction based on transmittance functions and a pixel-based Minnaert topographic correction. Secondly, class accuracies of especially the coniferous and mixed forest classes were enhanced after correction. There was only a minor improvement for the other land cover classes (broadleaved forest, bare soil, grass and water). This was explained by the position of different land cover types in the landscape. Finally, coupled correction methods showed most efficient on weakly illuminated slopes. After correction, accuracies in the low illumination zone (cos ˇ ≤ 0.65) were improved more than in the moderate and high illumination zones. Considering all results, best overall classification results were achieved after combination of the transmittance function correction with pixel-based Minnaert or pixel-based C-topographic correction. Furthermore, results of this bi-temporal study indicated that the topographic component had a higher influence on classification accuracy than the atmospheric component and that it is worthwhile to invest in both atmospheric and topographic corrections in a multi-temporal study.

Soil erosion and sediment deposition in the Belgian loess belt during the Holocene: establishing a sediment budget for a small agricultural catchment

A method to establish a Holocene sediment budget for a 103 ha agricultural catchment representative for the Belgian loess belt is presented. Soil erosion and sediment deposition were determined based on 185 coring locations and a large excavation in the valley bottom. Results were integrated in a GIS and interpolation techniques applied to derive spatial patterns of erosion and sedimentation. Total soil erosion, sediment deposition and sediment export were calculated and the results show that volumes are highly dependent on the interpolation technique used. Sediment delivery ratios between 20% and 42% are derived and are consistent with data reported in previous studies. This clearly shows that the majority of the sediments produced during the Holocene have been stored near their source area and have not been delivered to the downstream rivers. The spatial distribution of soil erosion and sediment deposition within the catchment is strongly dependent on slope gradient and position within the catchment, which suggests that, since human impact began, topography has been the main factor determining long-term soil erosion and sedimentation.

Data quality and model complexity for regional scale soil erosion prediction

Many spatially distributed environmental models have been developed for small spatial units (e.g. individual plots or fields). Their application at a regional scale (e.g. large drainage basins) was hitherto not very successful since most models are ‘scale-specific’. In most cases the lack of input data is a limiting factor for an appropriate model application at a regional scale. The use of simplified models on the other hand, can only be successful if they have the appropriate degree of complexity. This leads to the following paradox: on the one hand a model should be based on process knowledge so that it will react correctly to changes imposed by the modelling system. Including all available process knowledge, however, will lead to an overparametrisation. The error propagation involved in the poor data quality can then deteriorate dramatically the accuracy of the output results. For optimal model predictions at a regional scale the model complexity has to be in balance with the quality of the available input data. The error involved in a model application can be split in two parts: on the one hand the intrinsic model error because of an incomplete description of the processes and on the other hand the input error because of the use of low quality data. The total error is the sum of both parts. A simplification of the modelling structure will lead to an increase of the intrinsic model error and a decrease of the input error. If observed field values are available they can be used to determine which model structure gives the best results, given the available data. In many cases such validation data are not available. However, also in these cases, a model user should be able to select an optimal model structure. In this paper a technique is presented that allows the determination of the optimal degree of model complexity for an application at a regional scale if no observed field data are available. If the uncertainty of a model parameter exceeds a certain threshold, the model structure must be further simplified by replacement of this parameter by an aggregated value or a constant. The use of the technique is illustrated via the application of a soil erosion model.

The impacts of land use policy on the soil erosion risk : A case study in central Belgium

Set-aside programs of the European government have a double impact on the regional soil erosion risk in agricultural regions: (1) there is less area susceptible to soil erosion and (2) fields with a high erosion rate are preferably taken out of production resulting in a decrease of the average erosion risk. In order to quantify this double effect an inquiry among farmers in central Belgium was set up to find out which fields are preferably taken out of production. A statistical analysis pointed out that fields with a weak slope gradient, a loamy topsoil and good soil drainage have a low probability of being taken out of production. The results of the questionnaire were used to construct a transition probability map representing for each field the probability that it will be taken out of production. These transition probabilities were used to simulate the decrease in regional erosion risk for different scenarios. The outcome of these simulations suggests that there is a negative power relation between the set-aside percentage and the regional soil erosion risk.

Integrating science, policy and farmers to reduce soil loss and sediment delivery in Flanders, Belgium

Abstract This paper describes the evolution of soil erosion perception with policy makers and farmers in Flanders, and how these changes have resulted in the emergence of a soil conservation policy. Until the mid 1990s, soil erosion and its related problems received little attention in the environmental debate. This has changed through increased interest in environmental issues in general, as well as an increasing number of scientific reports on soil erosion and sediment delivery. New legislation that made the sediment problem a big financial issue in 1995, however, was the main reason for the recognition of soil erosion as an environmental problem with the policy makers. Despite the lack of monitoring soil erosion, a soil conservation policy emerged recently, which is clearly represented in the 2001 “soil erosion decree” by the Flemish government. This policy provides important opportunities for soil conservation as it incorporates both scientists and farmers. The involvement of farmers in demonstration projects is crucial with this respect as they have to be convinced about the usefulness and applicability of soil conservation measures. Farmers also participate in the development of a management plan. However, the success of the new policy could be undermined by its rapid development. There is still a lack of data underpinning the status of the erosion problem, and, the goals of the policy are not clearly defined. Furthermore, the administrative organisation is currently not favourable for an optimal co-operation with the farmers.

Reconstruction of late-Holocene slope and dry valley sediment dynamics in a Belgian loess environment

To unravel the evolution of a dry valley in the Belgian loess area soils and sediments along a slope catena were studied in detail. A 67 m long trench was opened from the upper slope to the centre of the valley bottom. The exposed soils and sediments showed evidence of severe soil erosion and other human disturbances that significantly changed the valley topography. The early-Holocene slope gradient was up to 25%, whereas now it is less than 10%. In the thalweg, a remnant of the early-Holocene soil was found underneath colluvial deposits, which were more than 3 m thick. A chronology for the valley evolution was established based on AMS 14C dating of charcoal fragments and optical dating of colluvial sediments. The first sediment deposition occurred in the early Iron Age, with an average sedimentation rate of approximately 3.4 ± 1.3 t/ha per yr. This increased to c. 5.4 ± 2.2 t/ha per yr during the Roman Period and further to 18.0 ± 2.2 t/ha per yr in the Middle Ages. Although sediment accumulation in the valley was substantial, soil-erosion processes were mainly low-magnitude and signs of gullying are absent in the thalweg until the last few centuries.

A strategy for controlling error of distributed environmental models by aggregation

In this paper a strategy for controlling error when calculating model parameter values from low-resolution low-accuracy data (LRLA-data) is presented. The basic principle of the proposed strategy is that the error in the model output can be reduced by output aggregation. By comparing the output from LRLA input data and high-resolution, high-accuracy input data (HRHA-data) at various aggregation levels, the error due to a decrease in accuracy and resolution of the input data can be assessed. An aggregation level can then be chosen so that an output is generated with the desired level of error and sufficient spatial detail. The method may also be used to evaluate the information loss when simplified models are used. The calculation of the topographic factors in an erosion model is taken here as an example application.

Performance of atmospheric and topographic correction methods on Landsat imagery in mountain areas

An effective removal of atmospheric and topographic effects on remote-sensing imagery is an essential preprocessing step for mapping land cover accurately in mountain areas. Various techniques that remove these effects have been proposed and consist of specific combinations of an atmospheric and a topographic correction (TC) method. However, it is possible to generate a wide range of new combined correction methods by applying alternative combinations of atmospheric and TC methods. At present, a systematic overview of the statistical performance and data input requirement of preprocessing techniques is missing. In order to assess the individual and combined impacts of atmospheric and TC methods, 15 permutations of two atmospheric and/or four TC methods were evaluated statistically and compared to the uncorrected imagery. Furthermore, results of the integrated ATCOR3 method were included. This evaluation was performed in a study area in the Romanian Carpathian mountains. Results showed that the combination of a transmittance-based atmospheric correction (AC), which corrects the effects of Rayleigh scattering and water-vapour absorption, and a pixel-based C or Minnaert TC, which account for diffuse sky irradiance, reduced the image distortions most efficiently. Overall results indicated that TC had a larger impact than AC and there was a trade-off between the statistical performance of preprocessing techniques and their data requirement. However, the normalized difference vegetation index analysis indicated that atmospheric methods resulted in a larger impact on the spectral information in bands 3 and 4.

Predicting land cover changes and their impact on the sediment influx in the Lake Balaton catchment

The land cover pattern in the Lake Balaton catchment (Hungary) has been changing since decollectivization in the 1990s. These land cover changes significantly impact the landscape connectivity, controlling the influx of sediments into the lake. A comparison of high resolution land cover maps from 1981, 2000 and 2005 showed a significant extensification of the agriculture with land cover conversions from arable land and vineyards to grassland and forest. For each land unit transition probabilities were assessed using logistic regression techniques to evaluate to which extent land cover changes are controlled by physical or socio-economic parameters. A stochastic land cover allocation algorithm was applied to generate future land cover patterns. The landscape connectivity for each of the simulated land cover patterns was assessed by means of a distributed routing algorithm. The simulations suggest that further land abandonment in the upslope parts of the catchment will cause a non-linear reduction of average soil erosion rates. The changes, however, have a relatively low impact on the sediment volume entering the lake because of the land unit’s poor connectivity with permanent river channels. The major contributors to the lakes sediment load are the vineyards near the lakeshore. They are likely to be maintained because of their touristic value. A significant reduction of the total sediment input in the lake can be expected only if soil conservation measures in the vineyards near the shorelines are undertaken.