The marginality index for agricultural land use, which was originally defined on a global scale, was used to evaluate agricultural land resources of Benin. For the assessment of the index, several biophysical factors limiting agricultural production under low capital input are analyzed using a fuzzy logic based algorithm. For Benin, we determined the marginality index (MI) successfully in a spatial resolution of 1km x 1km using influencing factors with a higher spatial resolution and an adapted fuzzy logic based algorithm. The results of the approach proved that the chosen indicators on a global scale are also useful indicators on a national scale. The necessary modifications were slight and mostly with the aim to increase the tangibility for national decision makers. On a national scale, data derived from remote sensing like MODIS or SRTM are interesting and embolden sources to derive input data. To support national decision makers, input data and algorithms were implemented within a computer-based Spatial Decision Support System (SDSS). With the developed SDSS 'AGROLAND' the user is able to visualize and analyze agricultural land resources based on the MI. Additionally, advanced model based raster analyses as well as the possibility of user interactions during runtime are implemented.