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Social and Behavioral Sciences Commons

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Physical Sciences and Mathematics

Journal of Spatial Information Science

Geographic information systems

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Full-Text Articles in Social and Behavioral Sciences

Evaluating Existing Manually Constructed Natural Landscape Classification With A Machine Learning-Based Approach, Rok Ciglic, Erik Strumbelj, Rok Cesnovar, Mauro Hrvatin, Drago Perko Jun 2019

Evaluating Existing Manually Constructed Natural Landscape Classification With A Machine Learning-Based Approach, Rok Ciglic, Erik Strumbelj, Rok Cesnovar, Mauro Hrvatin, Drago Perko

Journal of Spatial Information Science

Some landscape classifications officially determine financial obligations; thus, they must be objective and precise. We presume it is possible to quantitatively evaluate existing manually constructed classifications and correct them if necessary. One option for achieving this goal is a machine learning method. With (re)modeling of the landscape classification and an explanation of its structure, we can add quantitative proof to its original (qualitative) description. The main objectives of the paper are to evaluate the consistency of the existing manually constructed natural landscape classification with a machine learning-based approach and to test the newly developed general black-box explanation method in order …


The Influence Of Landscape Variation On Landform Categorization, Maia Williams, Werner Kuhn, Marco Painho Dec 2012

The Influence Of Landscape Variation On Landform Categorization, Maia Williams, Werner Kuhn, Marco Painho

Journal of Spatial Information Science

This paper compares the landform vocabularies of residents from two regions in Portugal. Participants described both their own and the other less familiar landscapes in response to video footage of the regions. The results indicate that participants used more detailed vocabularies to describe the known landscape compared to the less familiar study site with detail triggered by individual place recognition. A relationship between landform lexica content and landscape type was observed in the relative placement of detail within each vocabulary. The observed drivers of categorization were the salient features of the landscape (elevation and land cover) and utilitarian motivations (land …