The Methodology used
The methodology of the Project is based on comparative photointerpretation of satellite data for the years 1987-1990 (the one used for the creation of CLC database) and the year 1975.
The Project is organised in the following Workpackages:
WP1: Selection of the necessary data
The objective of this Workpackage is the selection of the necessary data for the Project, which includes the LANDSAT MSS satellite images (dated in 1975) and LANDSAT TM (1987-90) images that have been used for CORINE Land Cover Project, topographic maps, thematic maps, aerial photographs etc.
WP2: Pre-processing of satellite images
The objective of this Workpackage is the geometric correction of the LANDSAT MSS satellite images (dated in 1975) to the LANDSAT TM satellite images of CORINE Land Cover (image-to-image registration). The LANDSAT MSS images need to be processed in the best possible way, to obtain satellite images comparable with the CLC reference images. Thus, the LANDSAT MSS satellite images were resampled to 25 m resolution.
WP3: Processing of CORINE Land Cover data
This Workpackage includes the preperation of the vector CLC database for the comparative photointerpretation. A 10 km wide strip along the shoreline is clipped. After a preliminary study, it was observed that some sub-classes of specific interest for LACOAST could be easily distinguished, constituting a 4th level of the CORINE LC classes.
WP4: Comparative Photointerpretation between LANDSAT TM and MSS
It includes comparative photointerpretation of the LANDSAT MSS satellite images (dated in 1975) to the LANDSAT TM of CLC, for a 15 km zone and the down-dating of the vector database of CLC, in order to obtain the land use/land cover of the coastal zone for the year 1975. For this purpose, aerial photographs of 1:40,000 scale and topographical maps of 1:100,000 scale, are used.
WP5: Analysis of results
The analysis of the land cover changes leads to the definition of a number of indicators describing the evolution in the coastal area. Analysis of results is done using GIS handling other available existing geographical data, for stratification, overlay, statistics and mapping.