Changes in the methodology used in the production of the Spanish CORINE: Uncertainty analysis of the new maps

Highlights

• There are important differences between the new Spanish CORINE and previous editions.

• These differences are revealed using spatial metrics and a quantity/allocation agreement matrix.

• Photointerpretation seems to provide more consistent maps than map generalization.

• Expert intervention is decisive in achieving a good quality land use map.

• The biggest disagreements between the two CORINE are in the agricultural land classes.

Abstract

Since 2012 CORINE has been obtained in Spain from the generalization of a more detailed land cover map (SIOSE). This methodological change has meant the production of a new CORINE map, which is different from the existing ones. To analyze how different the new maps are from the previous ones, as well as the advantages and disadvantages of the new methodology, we carried out a comparison of the CORINE obtained from both methods (traditional and generalization) for the year 2006. The new CORINE is more detailed and it is more coherent with the rest of Spanish Land Use Land Cover (LULC) maps. However, problems have been encountered with regard to the meaning of its classes, the fragmentation of patches and the complexity of its perimeters.

Introduction

Land Use Land Cover (LULC) maps are extremely useful data, as evidenced by their widespread use in a large number of disciplines, such as Geography. These maps provide information on land occupation, seen as the biophysical cover observed on the Earth’s surface (Delgado Hernández, 2008). Their use is essential for the study and modeling of territorial dynamics.

There are different sources on land use and land cover for the Spanish territory. At global and continental levels maps are generated from supervised or unsupervised classification techniques. Some of the most significant at a spatial resolution of 1 km are GLC2000, UMD Land Cover Classification and DisCover. The first one was created for the year 2000, and the rest for the period 1992/93. At a finer resolution we can find MODISLC (500 m), drawn up yearly since 2000, and GlobCover (300 m), with reference date 2005.

For Europe, PELCOM was created from images of the year 1996, with a resolution of 1 km. At the national and regional level, CORINE (Coordination of information on the environment) and SIOSE (Land Cover and Land Use Information System of Spain) maps stand out, obtained from photointerpretation.

Comparative studies of different LULC maps at the global or continental level (Fritz and See, 2005; Giri et al., 2005; Hansen and Reed, 2000; Herold et al., 2008; McCallum et al., 2006; Tchuenté et al., 2011), some of which have used CORINE (Neumann et al., 2007), have evidenced differences and contradictions between the different sources. There are also many studies at the national and regional levels with similar conclusions (Bach et al., 2006; Chas-amil and Touza, 2015; Pérez-Hoyos and García-Haro, 2009; Ran et al., 2010; Waser and Schwarz, 2006).

In a similar vein, several studies suggest that the accuracy of these maps must be assessed. For CORINE, there are several analyses about the errors and confusions of its database (Caetano et al., 2006; Catalá Mateo et al., 2008; Diaz-Pacheco and Gutiérrez, 2013; Teixeira et al., 2016), although the uncertainties and limitations of these maps have not been totally specified.

Hence, there is a strong uncertainty linked to the way in which each map includes the information about land use and land cover. Understanding this uncertainty is essential for all research based in these maps, as in the case of LULC modeling (García-Álvarez in press; Hewitt et al., 2014, Camacho Olmedo et al., 2015). It is therefore necessary to assess the different ways used to produce CORINE in different countries and sometimes even within a single country.

Traditionally, CORINE has been generated from the photointerpretation of satellite imagery. However, in some countries (Germany, Austria, Finland, Ireland, Iceland, Norway, the United Kingdom, Sweden, Switzerland), especially since CLC06, the map is obtained from generalization techniques of national maps of greater detail (Hazeu et al., 2016). In other cases (Slovakia, Hungary, Poland, etc.), the CORINE map is used to obtain other maps of greater detail, at a 1:50.000 scale, with a minimum mapping unit (MMU) of 4 ha and a legend adapted to the geographical specifications of the country (Hazeu et al., 2016). They have even been used to obtain CORINE maps from before 1990 (Feranec et al., 2007a). In the case of Spain, CLC90 and CLC00 have a more detailed legend with 85 classes, with exceptions in the MMU (25 ha) for water surfaces and artificial areas (Catalá Mateo et al., 2008).

Therefore, there are different ways of producing CORINE, each of which can generate a different result. In Germany and Ireland, the methodological change in the production of CORINE (from photointerpretation to generalization) has led to the production of new maps, which show important inconsistencies with respect to the previous ones (Hovenbitzer et al., 2014, Lydon and Smith, 2014). In the Netherlands, this limitation has been one of the arguments for continuing to produce CORINE independently (Büttner, 2014; Hazeu et al., 2016).

The recent change in the methodology of production of CORINE in Spain (Hazeu et al., 2016) must go hand in hand with studies which show the degree of accuracy of the new CORINE map and its differences with the previous ones. Since the year 2012 CORINE has been obtained by generalizing SIOSE, as opposed to the digital photointerpretation technique used until the year 2006. For the same date CORINE was obtained using both methods (photointerpretation and generalization). This allows us to compare the CORINE obtained through both methods for the same time and place.

This paper aims to compare CORINE 2006 for Spain, obtained according to both the methods described above. With this we aim to answer the following questions: How has the change in production methods affected the information supplied by CORINE? Can the new CORINE be compared to the previous one? Is it more precise and reliable? How has the generalization from SIOSE to CORINE been performed and what degree of uncertainty is conveyed?

With these goals in mind, this paper is structured as follows: first, we begin by providing brief introduction to the CORINE and SIOSE databases, showing their features, differences and, in the former case, the recent change in its production methodology. We then describe the study area and the tools with which the analysis has been carried out. Finally, the results are presented and discussed in relation to the problems with the production of CORINE Spain and the rest of Europe.