The power of generalized entropy for biodiversity assessment by remote sensing: An open source approach

Abstract

The assessment of species diversity in relatively large areas has always been a challenging task for ecologists, mainly because of the intrinsic difficulty to judge the completeness of species lists and to undertake sufficient and appropriate sampling. Since the variability of remotely sensed signal is expected to be related to landscape diversity, it could be used as a good proxy of diversity at species level. It has been demonstrated that the relation between species and landscape diversity measured from remotely sensed data or land use maps varies with scale. While traditional metrics supply point descriptions of diversity, generalized entropy’s framework offers a continuum of possible diversity measures, which differ in their sensitivity to rare and abundant reflectance values. In this paper, we aim at: (i) discussing the ecological background beyond the importance of measuring diversity based on generalized entropy and (ii) providing a test on an Open Source tool with its source code for calculating it. We expect that the subject of this paper will stimulate discussions on the opportunities offered by Free and Open Source Software to calculate landscape diversity indices.