Industrial land is under transition globally. Insights into this transition are important to plan a sustainable future. Since industrial land follows parcel shapes and the transition process requires multi-year data to observe the impacts of such changes, multi-year vector data should be used to analyse industrial land transition. This paper presents a framework to analyse path-dependent regional industrial land transition processes using vector data. A step by step instruction is presented. In the analysis, the changed percentages of land use in the surroundings of appeared or disappeared industrial land are visualized. The visualized surrounding land use compositions give planners an idea on what causes land use transitions, the most frequent transition forms and their impacts on the surroundings, purely from a land use point of view to reduce data collection efforts. The North Brabant region in the Netherlands is used as a case study. The region is split into urban and non-urban areas to show the generic applicability of this framework.@en

Abstract The current system of spatial planning in Poland does not provide an effective and efficient tool for controlling planning decisions at a level higher than local. The result is an unrealistic approach to adopting development policies. Nowadays there is strong competition among local governments to attract investors, which results in excessive designation of investment areas and, consequently, an imbalance between supply and demand on the real estate market. An extremely important factor from the point of view of local authorities is also the financial burden on government budgets related to the implementation of the provisions of previously adopted policies. An improper spatial development policy can therefore generate costs without delivering the expected results, due to the lack of demand for the offered resources. A step in the right direction in optimizing how the spatial policy process is shaped may include conducting analyses and forecasts to support the decision-making process. Such analyses are needed both in terms of the amount of areas designed for each type of land use as well as their spatial distribution. Our considerations are focused on the second aspect. Analysis of land use transformation potential can be used in spatial management by selecting areas most where land use is most likely to change. The paper presents the simplified mechanisms of such analyses which can be adopted by the use of cellular automata. The final potential of an area is affected by variables such as the neighborhood, accessibility and suitability. As a result of the integration of these variables, it is possible to determine land use transformation potential. These considerations relate to the MOLAND (Monitoring Land Use/Cover Dynamics) research project and works on the development of the Metronamica decision support system, conducted in Western Europe.@en