This paper examines the problem of agricultural land abandonment through knowledge of driving factors. First, we reach out a review of the concept of abandonment in order to define the negative and positive aspects of this process in the landscape. Then we focus on a real case study in the Marina Baja region (SE Spain). Finally, we propose, from a theoretical perspective, the use of a methodology to define the most important variables for studying the abandonment processes in this region.First of all, we performed various analyses using Geographical Information Systems (GIS) to create a geodatabase which stores the main factors generally associated with abandonment. The variables considered can be grouped into three groups: environmental (such as climate, soils or relief), socio-economic (such as demographic, accessibility or technology) and those related to cultural practices in the crop (such as irrigation or rain-fed stone walls).Considering over a hundred variables we need to answer two questions: (1) which of the variables are really driving factors in the abandonment process of an agricultural plot? and (2) how important is each of them alone or in combination with others? The authors advocate the use of GIS for the feature creation or management and Data Mining techniques to perform the feature selection. Specifically, we propose the use of a concrete metric, aci (Attribute Correlation Index), to answer the questions raised above.
The environmental, cultural and socioeconomic causes and consequences of farmland abandonment are issues of increasing concern for researchers and policy makers. In previous studies, we proposed a new methodology for selecting the driving factors in farmland abandonment processes. Using Data Mining and GIS, it is possible to select those variables which are more significantly related to abandonment. The aim of this study is to investigate the application of the above mentioned methodology for finding relationships between relief and farmland abandonment in a Mediterranean region (SE Spain). We have taken into account up to 28 different variables in a single analysis, some of them commonly considered in land use change studies (slope, altitude, TWI, etc), but also other novel variables have been evaluated (sky view factor, terrain view factor, etc). The variable selection process provides results in line with the previous knowledge of the study area, describing some processes that are region specific (e.g. abandonment versus intensification of the agricultural activities). The European INSPIRE Directive (2007/2/EC) establishes that the digital elevation models for land surfaces should be available in all member countries, this means that the research described in this work can be extrapolated to any European country to determine whether these variables (slope, altitude, etc) are important in the process of abandonment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.