Characterization of land use cover datasets from a global to an Andalusian level: an “obstacle course” for users


  • María Teresa Camacho Olmedo Universidad de Granada
  • Sabina Florina Nanu Departamento de Análisis Geográfico Regional y Geografía Física, Universidad de Granada
  • David García-Álvarez Departamento de Geografía, Universidad Complutense de Madrid



Advances in the field of Geographic Information Systems (GIS) and in Remote Sensing (RS) have led to the production of a significant number of Land Use and Land Cover (LUC) datasets. These datasets show great diversity in terms of the extents mapped, the scale and spatial resolution, or the temporal and thematic resolution, among others. In this paper, we review 33 general (non-thematic) LUC datasets covering different extents (from global to regional level), which are currently available or will be in the future for Andalusia (Spain). 17 are Global, 10 European, 3 cover Spain and 3 Andalusia. The aim is to analyze the spatial, temporal and thematic parameters of these datasets so as to enable users to choose the one that best suits their purposes. Spatial parameters include format, spatial resolution, cartographic scale, Minimum Mapping Unit (MMU) and Minimum Mapping Width (MMW); temporal parameters include temporal resolution or timeframe (single or time series), i.e. the length of time and the number of available dates. The thematic parameters include the number of classes and their nature, compatible legends and group of classes. This comparative analysis shows that within these 33 datasets, at least 217 different products/maps are on offer to users. This wide variety of maps is a major source of uncertainty and makes the path to find the best LUC dataset a real “obstacle course” for users.

Author Biography

María Teresa Camacho Olmedo, Universidad de Granada

Full professor. Department of Regional Geographic Analysis and Physical Geography.




How to Cite

Camacho Olmedo, M. T., Nanu, S. F., & García-Álvarez, D. (2022). Characterization of land use cover datasets from a global to an Andalusian level: an “obstacle course” for users. GeoFocus. International Review of Geographical Information Science and Technology, (30), 93–133.