Spatial Analysis and Data Science

Team lead: Dr Justin Moat

The Spatial Analysis and Data Science team researches and develops geospatial techniques on biodiversity for conservation and to improve people’s livelihoods.

Spatial distribution, resilience and conservation of plants

Below are some examples of our activities:

Identifying vulnerable and resilient species, both wild and domesticated, to global change by combining environmental and biological information with spatial analysis. Biological information can include: geographical occurrences, functional traits, genomics and phylogeny.
Identifying global conservation priorities by analysing our large-scale databases, including the World Checklist and the point data underpinning species extinction risk assessments to gain an understanding of historic and future distribution of plants.
Understanding the ecological and evolutionary processes driving plant and fungi distribution, for example, demography, functional traits, biotic interactions, dispersal and genetic diversity.

Geospatial techniques

Below are some examples of our activities:

Developing novel spatial algorithms for Kew’s critical work on extinction risk assessments, quantifying fragmentation and isolation, area of occupancy, dispersal and population metrics, to increase both numbers and quality of species assessments.
Developing techniques in species distribution modelling and climate change projections, especially for useful and economically valuable species.
Investigating and developing methods for working with remotely-sensed and Unmanned Aerial Vehicular (UAV aka drones) imagery, to classify plants, for species identification, plant health and abundance estimation.
Producing and developing tools to help with specimen georeferencing and capturing data in the field.
Providing training and services for staff and students, presenting our results and visualisation as multimedia outputs for the general public.