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GI_Forum 2020, Volume 8, Issue 1Journal for Geographic Information Science
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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GI_Forum 2020, Volume 8, Issue 1, pp. 89-98, 2020/06/25
Journal for Geographic Information Science
An increasing demand for agricultural products within the past years has led to increasing agricultural intensification. Various agricultural compositions and landscape configurations can have different impacts on the provision of ecosystem services. The EU follows the aim of supporting and developing sustainable food production systems. We use the plot-based data provided by the Integrated Administration and Control System (IACS) to identify different types of agricultural landscapes and their spatial distribution in Brandenburg, Germany. By calculating a set of landscape metrics to characterise agricultural land use, we were able to identify six types of agricultural landscapes by a Two-Step cluster analysis for a hexagonal grid. Thereby, the majority of Brandenburg is covered by agriculture characterised by high share of cropland but different degrees of fragmentation. By providing a framework using landscape metrics derived from IACS data, the approach of clustering to identify typologies is highly transferable to other regions within the EU and may provide an important asset for offering new units of analysis for a better tailored environmental and agricultural planning depending on the local to regional characteristics.
Keywords: agricultural land use pattern, agricultural intensification, landscape metrics, cluster analysis