Open pit mines left many regions worldwide inhospitable or uninhabitable. Many sites are left behind in a hazardous or contaminated state, show remnants of waste, or have other restrictions imposed upon them, e.g., for the protection of human or nature. Such information has to be permanently managed in order to reuse those areas in the future. In this work we present and evaluate an automated workflow for supporting the post-mining management of former lignite open pit mines in the eastern part of Germany, where prior to any planned land reuse, aforementioned information has to be acquired to ensure the safety and validity of such an endeavor. Usually, this information is found in expert reports, either in the form of paper documents, or in the best case as digitized unstructured text-all of them in German language. However, due to the size and complexity of these documents, any inquiry is tedious and time-consuming, thereby slowing down or even obstructing the reuse of related areas. Since no training data is available, we employ active learning in order to perform multi-label sentence classification for two categories of restrictions and seven categories of topics. The final system integrates optical character recognition (OCR), active-learningbased text classification, and geographic information system visualization in order to effectively extract, query, and visualize this information for any area of interest. Active learning and text classification results are twofold: Whereas the restriction categories were reasonably accurate (>0.85 F1), the seven topicoriented categories seemed to be complex even for human annotators and achieved mediocre evaluation scores (<0.70 F1).
The operation of open-cast lignite mines is a large intervention in nature, making the areas uninhabitable even after closing the mines without renaturation processes. Renaturation of these large areas requires a regional planning process which is tied to many conditions and restrictions, such as environmental protection laws. The related information is available only as unstructured text in a variety of documents. Associated temporal aspects and the geographical borders to these textual information have to be linked manually so far. This process is highly time-consuming, error-prone, and tedious. Therefore, the knowledge of experts is often used, but this does not necessarily include all the relevant information. In this paper, we present a system to support the experts in decision-making of urban planning, renaturation, and redevelopment projects. The system allows to plan new projects, while considering spatial and temporal restrictions extracted from text documents. With this, our presented system can also be used to verify compliance with certain legal regulations, such as nature conservation laws.
Experts face the task to decide where and how land reuse-transforming previously used areas into landscape and utility areas-can be performed. This decision is based on which area should be used, which restrictions exist, and which conditions have to be fulfilled for reusing this area. Information about the restrictions and the conditions is available as mostly textual, non-spatial data associated to areas overlapping the target areas. Due to the large amount of possible combinations of restrictions and conditions overlapping (partially) the target area, this decision process becomes quite tedious and cumbersome. Moreover, it proved to be useful to identify similar regions that have reached different stages of development within the data set which in turn allows determining common tasks for these regions. We support the experts in accomplishing these tasks by providing aggregated representations as well as multi-coordinated views together with category filters and selection mechanisms implemented in an interactive decision support system. Textual information is linked to these visualizations enabling the experts to justify their decisions. Evaluating our approach using a standard SUS questionnaire suggests, that especially the experts were very satisfied with the interactive decision support system. LAND REUSE of former open pit mines is an important topic, as these areas need to be renaturalized and should be made available again.Renaturalization becomes necessary after open pit mining activities due to soil contamination, remnants of waste, and unstable soil. The goal of
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