G.W. Hazeu

A Dutch multi-date land use database: Identification of real and methodological changes

Abstract Land cover and land use are important information sources for environmental issues. One of the most important changes at the Earths surface concerns land cover and land use. Knowledge about the location and type of these changes is essential for environmental modeling and management. Remote sensing data in combination with additional spatial data are recognized as an important source of information to detect these land cover and land use changes. In this paper, we introduce the Dutch multi-date land use database (LGN). Today there are six versions of the LGN database (LGN1–LGN6) based on satellite imagery of respectively 1986, 1992/1994, 1995/1997, 1999/2000, 2003/2004 and 2007/2008. With the completion of LGN6 a time-series of land use databases covering 20 years became available. The different databases were produced according to different methodologies. The resulting inconsistencies for monitoring land use changes and possible solutions are the main themes of this paper. Emerging user requirements, increased data availability and technical improvements lead to methodological differences between the LGN5 and LGN6 Dutch land use database. Monitoring of land use changes by integrating independent spatial datasets results in a mixture of real and methodological changes. A methodology is applied to detect real land use changes for a limited number of land use monitoring classes. The detected real changes have a high probability (almost 95%) that they are real changes. Next to these real changes, differences exist between LGN5 and LGN6, i.e. so-called methodological land use changes, being the result of methodological adaptations over time.

Environmental and agricultural modeling: Integrated approaches for policy impact assessment

The Agri-Environmental Zonation (AEnZ) is a biophysical typology based on a recently available detailed database on organic carbon content of the topsoil of Europe, the Environmental Stratification (EnS) and an Agri-mask. The AEnZ is used within the integrated assessment framework of SEAMLESS. The basis for this typology is the Environmental Stratification of Europe (EnS) building mainly on climate and altitude characteristics. The 84 environmental strata were aggregated into 13 environmental zones (EnZs). The environmental zones were then combined with organic carbon topsoil data (OCTOP) to cover the wide range of agri-environmental diversity of Europe. The OCTOP content was selected as soil variable as it explained most of the variation in soils in Europe. The EnZs/OCTOP land units were combined with an Agri-mask representing major obstacles for farming resulting in the final AEnZ typology. The Agri-mask, which is based on CORINE Land Cover, soil, altitude and slope data, divides Europe into three zones with different agricultural potential (suited, unsuited and marginally suited). The AEnZ consists of 238 land types of which 82 classes are referred as suitable for agriculture (75.8% of EU27+). For the SEAMLESS framework two of the three dimensions of the Agri-Environmental Zonation have been used to build the spatial framework to link information on farming and biophysics. The spatial building block of SEAMLESS is thus the Seamzones, that is an overlay of the 13 environmental zones, the seven OCTOP classes and 270 administrative (NUTS2) regions. In total this results in 3,513 Seamzones that are used to structure the biophysical data as well as the data on farming across the EU27+.The Agri-Environmental Zonation (AEnZ) is a biophysical typology based on a recently available detailed database on organic carbon content of the topsoil of Europe, the Environmental Stratification (EnS) and an Agri-mask. The AEnZ is used within the integrated assessment framework of SEAMLESS. The basis for this typology is the Environmental Stratification of Europe (EnS) building mainly on climate and altitude characteristics. The 84 environmental strata were aggregated into 13 environmental zones (EnZs). The environmental zones were then combined with organic carbon topsoil data (OCTOP) to cover the wide range of agri-environmental diversity of Europe. The OCTOP content was selected as soil variable as it explained most of the variation in soils in Europe. The EnZs/OCTOP land units were combined with an Agri-mask representing major obstacles for farming resulting in the final AEnZ typology. The Agri-mask, which is based on CORINE Land Cover, soil, altitude and slope data, divides Europe into three zones with different agricultural potential (suited, unsuited and marginally suited). The AEnZ consists of 238 land types of which 82 classes are referred as suitable for agriculture (75.8% of EU27+).

A Biophysical Typology in Agri-environmental Modelling

The Agri-Environmental Zonation (AEnZ) is a biophysical typology based on a recently available detailed database on organic carbon content of the topsoil of Europe, the Environmental Stratification (EnS) and an Agri-mask. The AEnZ is used within the integrated assessment framework of SEAMLESS. The basis for this typology is the Environmental Stratification of Europe (EnS) building mainly on climate and altitude characteristics. The 84 environmental strata were aggregated into 13 environmental zones (EnZs). The environmental zones were then combined with organic carbon topsoil data (OCTOP) to cover the wide range of agri-environmental diversity of Europe. The OCTOP content was selected as soil variable as it explained most of the variation in soils in Europe. The EnZs/OCTOP land units were combined with an Agri-mask representing major obstacles for farming resulting in the final AEnZ typology. The Agri-mask, which is based on CORINE Land Cover, soil, altitude and slope data, divides Europe into three zones with different agricultural potential (suited, unsuited and marginally suited). The AEnZ consists of 238 land types of which 82 classes are referred as suitable for agriculture (75.8% of EU27+). For the SEAMLESS framework two of the three dimensions of the Agri-Environmental Zonation have been used to build the spatial framework to link information on farming and biophysics. The spatial building block of SEAMLESS is thus the Seamzones, that is an overlay of the 13 environmental zones, the seven OCTOP classes and 270 administrative (NUTS2) regions. In total this results in 3,513 Seamzones that are used to structure the biophysical data as well as the data on farming across the EU27+.The Agri-Environmental Zonation (AEnZ) is a biophysical typology based on a recently available detailed database on organic carbon content of the topsoil of Europe, the Environmental Stratification (EnS) and an Agri-mask. The AEnZ is used within the integrated assessment framework of SEAMLESS. The basis for this typology is the Environmental Stratification of Europe (EnS) building mainly on climate and altitude characteristics. The 84 environmental strata were aggregated into 13 environmental zones (EnZs). The environmental zones were then combined with organic carbon topsoil data (OCTOP) to cover the wide range of agri-environmental diversity of Europe. The OCTOP content was selected as soil variable as it explained most of the variation in soils in Europe. The EnZs/OCTOP land units were combined with an Agri-mask representing major obstacles for farming resulting in the final AEnZ typology. The Agri-mask, which is based on CORINE Land Cover, soil, altitude and slope data, divides Europe into three zones with different agricultural potential (suited, unsuited and marginally suited). The AEnZ consists of 238 land types of which 82 classes are referred as suitable for agriculture (75.8% of EU27+).

Operational land cover and land use mapping in the Netherlands

This chapter deals with long-term Dutch national land cover and land use mapping activities. Land cover and land use are often difficult to separate 1:1. For practical reasons in this chapter only the term land cover will be used with the exception of direct translations of the names of database. Four main databases can be discerned: 1. Topographical database (Top10vector/Top10NL) 2. Land Use database “Bestand BodemGebruik (BBG)” 3. National Land Use database “Landelijk Grondgebruiksbestand Nederland (LGN)” 4. CORINE Land Cover database

High Nature Value farmland identification from satellite imagery, a comparison of two methodological approaches

While the identification of High Nature Value (HNV) farmland is possible using the different types of spatial information categories available at European scale, most data used is still too coarse and therefore only provides an approximate estimate of the presence of HNV farmland. This paper describes two promising methods using remote sensing – one for HNV farmland identification and one for change detection within HNV farmland. The performance of the two methods is demonstrated by detailed results for two case studies – the Netherlands for the HNV farmland identification, and Bulgaria for change detection within HNV farmland. An estimation of the presence of HNV farmland or of HNV farmland change can well be based on high-resolution satellite imagery, but the classification method must be adapted to regional characteristics such as field size and type of landscape. The temporal variability and bio-climatological characteristics across Europe do not allow for a simple European classification of HNV farmland. Also comparison between years is complicated because of the large impact of seasonal variation in the land cover expression and the complexity of the HNV farmland definitions. Although HNV farmland detection methods are promising, remote sensing alone does not yet provide the appropriate tools for adequate monitoring.

A biophysical typology for a spatially-explicit agri-environmental modelling framework

The Agri-Environmental Zonation (AEnZ) is a biophysical typology based on a recently available detailed database on organic carbon content of the topsoil of Europe, the Environmental Stratification (EnS) and an Agri-mask. The AEnZ is used within the integrated assessment framework of SEAMLESS. The basis for this typology is the Environmental Stratification of Europe (EnS) building mainly on climate and altitude characteristics. The 84 environmental strata were aggregated into 13 environmental zones (EnZs). The environmental zones were then combined with organic carbon topsoil data (OCTOP) to cover the wide range of agri-environmental diversity of Europe. The OCTOP content was selected as soil variable as it explained most of the variation in soils in Europe. The EnZs/OCTOP land units were combined with an Agri-mask representing major obstacles for farming resulting in the final AEnZ typology. The Agri-mask, which is based on CORINE Land Cover, soil, altitude and slope data, divides Europe into three zones with different agricultural potential (suited, unsuited and marginally suited). The AEnZ consists of 238 land types of which 82 classes are referred as suitable for agriculture (75.8% of EU27+). For the SEAMLESS framework two of the three dimensions of the Agri-Environmental Zonation have been used to build the spatial framework to link information on farming and biophysics. The spatial building block of SEAMLESS is thus the Seamzones, that is an overlay of the 13 environmental zones, the seven OCTOP classes and 270 administrative (NUTS2) regions. In total this results in 3,513 Seamzones that are used to structure the biophysical data as well as the data on farming across the EU27+.The Agri-Environmental Zonation (AEnZ) is a biophysical typology based on a recently available detailed database on organic carbon content of the topsoil of Europe, the Environmental Stratification (EnS) and an Agri-mask. The AEnZ is used within the integrated assessment framework of SEAMLESS. The basis for this typology is the Environmental Stratification of Europe (EnS) building mainly on climate and altitude characteristics. The 84 environmental strata were aggregated into 13 environmental zones (EnZs). The environmental zones were then combined with organic carbon topsoil data (OCTOP) to cover the wide range of agri-environmental diversity of Europe. The OCTOP content was selected as soil variable as it explained most of the variation in soils in Europe. The EnZs/OCTOP land units were combined with an Agri-mask representing major obstacles for farming resulting in the final AEnZ typology. The Agri-mask, which is based on CORINE Land Cover, soil, altitude and slope data, divides Europe into three zones with different agricultural potential (suited, unsuited and marginally suited). The AEnZ consists of 238 land types of which 82 classes are referred as suitable for agriculture (75.8% of EU27+).