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Land cover maps constitute a necessary tool for development planning and management of the territory. Furthermore, land cover maps depicting the current reality are a must in countries where, due to political changes, rapid dynamic phenomena have taken place, resulting in a complete restructuring of the agricultural and other sectors, as in the case of Bulgaria.

The scale of such maps should be large enough to provide detailed information, however it should allow for regional assessment, statistics and subsequent planning. The 1:50 000 scale is the most suited for this exercise.

The FAO project TCP/BUL/8922 “Strengthening Capacity in Agricultural Development through Remote Sensing and GIS” has produced 14 land cover maps at 1:50 000 scale for selected test areas of the country, covering 5 600 sq km. These maps were prepared using Landsat satellite data, acquired in 1998 and 1999 as the main data source and thus represent the land cover existing at that time. The land cover classification was performed using the FAO Land Cover Classification System (LCCS).

To each mapped unit (polygon), soil type and erosion features were linked as attributes into the GIS system. This created a comprehensive database, which is unique in Bulgaria. The database provides very useful information for agriculture, forestry and urban development planning, for environment protection and for many other applications. The data collected in the database provide the possibility for different kinds of spatial analysis, which is necessary in land management.

For an area of particular interest, IKONOS very high resolution satellite data were used to produce an assessment of the state of vineyards, the updating of the linear features of a large scale topographical map and other applications.

The methodology and applications reported in this study have been tested and refined under operative conditions in the framework of the project’s activities.

Keywords: Bulgaria, GIS, land cover, LCCS, remote sensing

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* Environment and Energy Series
* Remote Sensing Centre Series
* Agrometeorology Working Papers
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