{"title":"基于景观度量和聚类分析的勃兰登堡农业景观特征研究","authors":"Saskia Wolff, T. Lakes","doi":"10.1553/giscience2020_01_s89","DOIUrl":null,"url":null,"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.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Characterising Agricultural Landscapes using Landscape Metrics and Cluster Analysis in Brandenburg, Germany\",\"authors\":\"Saskia Wolff, T. Lakes\",\"doi\":\"10.1553/giscience2020_01_s89\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":29645,\"journal\":{\"name\":\"GI_Forum\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GI_Forum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1553/giscience2020_01_s89\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GI_Forum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1553/giscience2020_01_s89","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Characterising Agricultural Landscapes using Landscape Metrics and Cluster Analysis in Brandenburg, Germany
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.