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Visualizing Spatial Ecological Data (VSED01)

1 message · Oliver Hooker

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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