A new study conducted by Mao-Ning Tuanmu and Walter Jetz, members of the SBSC program at Yale, characterizes global fine-grain habitat heterogeneity for modeling biodiversity patterns. Fourteen metrics quantifying textural features of remote sensing imagery of vegetation greenness provide detailed information on different aspects of spatial habitat heterogeneity down to 1-km resolution. The metrics strongly exceed conventional heterogeneity variables in capturing fine-grain spatial variation in species richness across large extents. The NASA-funded study has been published in journal Global Ecology and Biogeography and the data layers of the new metrics at 1-, 5- and 25-km resolution are freely available at www.earthenv.org. These metrics and data layers provide a rigorous and comparable basis for understanding heterogeneity-diversity relationships, and offer a power tool for monitoring and understanding the responses of biodiversity to the changing environment. A recent Nature paper shows their even boarder applications in ecological, biogeographic and biodiversity conservation research.