Oswald Marinoni

Implementation of the analytical hierarchy process with VBA in ArcGIS

Decisions on landuse have become progressively more difficult in the last decades. The main reasons for this development lie in the increasing population combined with an increasing demand for new land and resources and in the growing consciousness for sustainable land and resource use. The steady reduction of valuable land leads to an increase of conflicts in land use decision-making processes since more interests are being affected and therefore more stakeholders with different land use interests and different valuation criteria are being involved in the decision-making process. In the course of such a decision process all identified criteria are weighted according to their relative importance. But assigning weights to the relevant criteria quickly becomes a difficult task when a greater number of criteria are being considered, especially with regard to land use decisions where decision makers expect some kind of mapped result it is therefore useful to use procedures that not only help to derive criteria weights but also accelerate the visualisation and mapping of land use assessment results. Both aspects can easily be facilitated in a GIS. This paper focuses the development of an ArcGIS VBA macro which enables the user to derive criteria weights with the analytical hierarchy process and which allows a mapping of the land use assessment results by a weighted summation of GIS raster data sets. A dynamic link library for the calculation of the eigenvalues and eigenvectors of a square matrix is provided.

A stochastic spatial decision support system based on PROMETHEE

PROMETHEE is a well known multicriteria decision support method which gives insight into the preference structure of a whole set of alternatives. The retrieved preference information is used to give the partial or complete preorder of the available alternatives which makes PROMETHEE a well suited decision support tool if a ranking of available alternatives is desired. A relatively low degree of mathematical complexity makes PROMETHEE an attractive method for all non experts involved in a decision process. This paper discusses the integration of PROMETHEE in a GIS. It will be shown how the combination of a sophisticated decision support methodology with powerful spatial analysis and visualisation capabilities can be applied to evaluating decision alternatives that are made up of regular or irregular shaped zones of raster cells. Deterministic as well as stochastic PROMETHEE approaches are considered and general recommendations on the use of stochastic simulation methods are given. Moreover, a framework is presented which facilitates the application of the proposed approaches.

Improving geological models using a combined ordinary-indicator kriging approach

Abstract The generation of geological models always goes along with the geotechnical engineers wish to keep the models as accurate as possible. Consequently, a lot of research has been carried out in the last years to decrease geological model uncertainty. The focus was mainly put on the statistics of the mechanical parameters of soil and rock masses that go directly into the safety calculations. Besides the statistical features of the mechanical parameters, care must also be given to the statistics associated with the geometrical parameters of the geological layers. One way to statistically model the underground geometry is through the use of geostatistical interpolation techniques generally known as kriging. However, the most commonly used ordinary kriging techniques produce strongly smoothed model results that lead to an inaccurate regionalization of geological layers. Since geotechnical models are usually on a large scale, such inaccuracies cannot be tolerated. This paper shows how smoothing effects around zero value zones can be reduced significantly by the use of a combined ordinary–indicator kriging approach.

A discussion on the computational limitations of outranking methods for land‐use suitability assessment

The family of outranking methods includes a set of well‐known and popular decision‐aid methods. Heterogeneous variables of various scales can be introduced, and data transformations are not required. But it is also recognized that these methods are subject to computational limitations with respect to the number of decision alternatives. Dealing with large raster datasets and considering every raster cell a location alternative, these methods reach their computational limits quickly. This paper discusses these computational limits and presents an iterative approach which enables a modeller to easily and transparently apply outranking methods for land‐suitability assessment with practically no limit in the sizes of the raster datasets. An example using the PROMETHEE outranking approach is performed.

Comparison of Multicriteria Analysis Techniques for Environmental Decision Making on Industrial Location

European legislation calls for a well-planned sustainable development. As such, it has to in‐ clude a social, economic as well as an environmental dimension. According to Agenda 21 (http://www.un.org/esa/dsd/agenda21/), countries should undertake efforts to build up a comprehensive national inventory of their land resources in order to establish land informa‐ tion systems. The overall objective is to provide information for the improvement or the re‐ structuring of land-use decision processes including the consideration of socio-economic and environmental issues.