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Visualizing Spatial Ecological Data (VSED01)

Oliver Hooker 
Visualizing Spatial Ecological Data (VSED01)

Bring your spatial ecological datasets to life in R. Learn to interpret and
present spatial and temporal patterns with clarity, accessibility, and
scientific rigour.
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Course Details & Format

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   *Next Session:* November 17?21, 2025 (Monday?Friday)
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   *Duration:* 5 days ? ~8?hours/day = *40?hours total*
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   *Schedule:* Live online sessions in Portugal local time (GMT+1); all
   sessions recorded and available immediately for on-demand access.
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   *Format:* Interactive remote classroom featuring lectures, practical R
   exercises, participant data discussions, and peer collaboration.

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What You?ll Learn

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   Visualise ecosystems using remote sensing data with RGB raster plotting
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   Measure spatial variability using both distance-based and
   abundance-based methods
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   Apply multivariate and temporal visualisations?including ridgeline
   plots?for dynamic ecological data
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   Manage dense datasets using scatterplots and hexagon binning
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   Create cartograms, bivariate maps, overlap metrics, and spatial density
   maps to analyse species distributions
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   Design accessible, colourblind-friendly scientific graphics using the
   tidyverse ecosystem

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Who It?s For

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   Ecologists and environmental scientists interpreting spatial patterns in
   ecosystems
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   Graduate researchers in ecology, geography, or related fields working
   with remote sensing or species distribution data
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   Conservation practitioners and policy analysts communicating complex
   spatial insights
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   Academic professionals designing teaching materials for ecological
   modelling or spatial analysis

*No prior experience with R or GitHub is required.* Guided instruction and
hands-on support ensure confident learning from the ground up
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Fees & Registration

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   *Early bird (first 10 places): ?430*
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   *Standard fee: ?480*

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Why Choose VSED01?

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   *In-depth & focused:* A comprehensive five-day exploration of spatial
   visualization in R
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   *Highly practical:* Real-world ecological examples using remote sensing,
   raster matrices, and spatial density mapping
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   *Inclusive & accessible:* Colour-safe graphics ensure clarity for all
   audiences
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   *Flexible learning:* Live instruction plus recordings, immediate
   follow-up support, and 30-day access to materials
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   *Bring your own data:* Tailor the learning to your research with
   dedicated data sessions and post-course email assistance

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*Elevate your spatial ecology skills?visualise with precision, clarity, and
accessibility using R.*

Questions or want to discuss whether this fits your work? Email
oliver at prstats.org