Characterising Agricultural Landscapes using Landscape Metrics and Cluster Analysis in Brandenburg, Germany

Abstract

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.

Assessment of Tuscany Landscape Structure According to the Regional Landscape Plan Partition

“…The methodology applied in this study was chosen due to the need for assessing and describing different landscape typologies that characterize the Tuscan territory. The use of a hexagonal grid has already been applied with success in other researches to correlate maps, spatial analysis and statistics [49] and proved to be particularly effective for the study of fine-scale Mediterranean landscape mosaics [45,[50][51][52]. The applied methodology resulted in being effective in assessing the landscape mosaic structure of different typologies of the landscape in Tuscany and also in creating a database that can represent a crucial baseline for a monitoring system based on fixed study areas that can be easily updated, similarly to what has already been conducted at the national level in Italy [53] and in other European countries [54,55].…”

Landscape Ecological Evaluation of Cultural Patterns for the Istanbul Urban Landscape

“…Landscape metrics offer a wide range of options to evaluate the landscape structure, from agricultural areas to mining/quarry sites, from wetlands to forests. The critical issue here is that the expert who makes the evaluation prefers the metric set that will best reveal the spatial arrangement of the landscape structure, depending on the subject investigated [20,67,[70][71][72][73][74][75][76][77][78][79][80].…”

“…We selected them among the "highly universal and consistent landscape structure components" defined by Cushman et al (2008) [42]. Previous research focusing on correlational relationships between metrics was also considered [21,47,65,77,90,91]. Topalo glu et al (2020) applied principal component analysis (PCA) to summarize the information of a data set containing classes described by several correlated metrics.…”