Uncertainties in land use data
- 1Institute for Regional Development, University of Castilla La Mancha, Albacete, Spain
- 2Department of Geography, University of Calgary, Alberta, Canada
Abstract. This paper deals with the description and assessment of uncertainties in land use data derived from Remote Sensing observations, in the context of hydrological studies. Land use is a categorical regionalised variable reporting the main socio-economic role each location has, where the role is inferred from the pattern of occupation of land. The properties of this pattern that are relevant to hydrological processes have to be known with some accuracy in order to obtain reliable results; hence, uncertainty in land use data may lead to uncertainty in model predictions. There are two main uncertainties surrounding land use data, positional and categorical. The first one is briefly addressed and the second one is explored in more depth, including the factors that influence it. We (1) argue that the conventional method used to assess categorical uncertainty, the confusion matrix, is insufficient to propagate uncertainty through distributed hydrologic models; (2) report some alternative methods to tackle this and other insufficiencies; (3) stress the role of metadata as a more reliable means to assess the degree of distrust with which these data should be used; and (4) suggest some practical recommendations.