Radeloff VC, Dubinin M, Coops NC, Allen AM, Brooks TM, Clayton MK, Costa GC, Graham CH, Helmers DP, Ives AR, Kolesov D, Pidgeon AM, Rapacciuolo G, Razenkova E, Suttidate N, Young BE, Zhu L, Hobi ML

Remotely sensed data can help to identify both suitable habitat for individual species, and environmental conditions that foster species richness, which is important when predicting how biodiversity will respond to global change. The question is how to summarize remotely sensed data so that they are most relevant for biodiversity analyses, and the Dynamic Habitat Indices are three metrics designed for this. The Dynamic Habitat Indices summarize three key measures of vegetative productivity: annual cumulative productivity, minimum productivity throughout the year, and seasonality, expressed as the annual coefficient of variation in productivity. The DHIs, which are closely related to well-established ecological hypotheses of biodiversity, can predict species richness well, and are promising for application in biodiversity science and conservation.

Remote Sensing of Environment 222: 204-214

Keywords: biodiversity, conservation, global, MODIS, phenology, productivity, remote sensing