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Table of Contents

2025-03-27

Source: vignettes/articles/2.0-TableOfContents.Rmd
2.0-TableOfContents.Rmd

NatureCounts Spatial Data Tutorial in R

Authors

Dimitrios Markou, Danielle Ethier

Overview

The NatureCounts Spatial Data Tutorial in R is a data exploration resource for the greater Birds Canada community. It guides R users through downloading, processing, and visualizing spatial data, including NatureCounts surveys, conservation areas, and environmental layers.

Prerequisites

Before starting this tutorial, we recommend that users: - Familiarize themselves with the NatureCounts Intro R Tutorial. - Install the latest versions of R and RStudio.

Learning Objectives

This tutorial follows a structured format with seven focused chapters:

Chapter 1: Spatial Data Exploration

Learn how to distinguish between vector and raster data, apply geoprocessing functions, and use these functions to visualize NatureCounts data using a spatiotemporal map.

  • 1.1. Spatial Data Types
  • 1.2. Geoprocessing Functions
  • 1.3. Spatiotemporal Mapping

Chapter 2: Spatial Subsets

Learn how to download, process, and visualize spatial vector data from NatureCounts within conservation areas: Key Biodiversity Areas and Priority Places for Species at Risk. - 2.1. Key Biodiversity Areas - 2.2. Priority Places for Species at Risk

Chapter 3: Climate Data

Learn how to download, process, and visualize NatureCounts data with vector and raster climate data sources: Weathercan and WorldClim.

  • 3.1. Data Setup
  • 3.2. Weathercan (Vector) Data
  • 3.3. WorldClim (Raster) Data

Chapter 4: Elevation Data

Learn how to distinguish between types of elevation models, crop and mask LiDAR-derived Digital Terrain Models (DTMs), and extract elevation (raster) values at observation sites (vector points).

  • 4.1. Data Setup
  • 4.2. Elevation Models
  • 4.3. Spatial Extents (Crop & Mask)
  • 4.4. Map and Extract Digital Elevation Data
  • 4.5. LiDAR Data Resources
  • 4.6. Manual Data Download

Chapter 5: Land Cover Data

Learn how to crop and mask land cover data, assign land cover class labels, create point buffers, calculate landscape metrics like Percent Land Cover (PLAND) and Edge Density (ED) across point buffers, and perform a spatial join using land cover and NatureCounts data.

  • 5.1. Data Setup
  • 5.2. Spatial Extents (Crop & Mask)
  • 5.3. Class Labels
  • 5.4. Point Buffers
  • 5.5. Landscape Metrics
  • 5.6. Spatial Join

Chapter 6: Satellite Imagery

Learn how to plot true and false color composites of satellite imagery, calculate spectral indices like NDVI, and combine NatureCounts data with spectral values for analysis.

  • 6.1. Color Composite Images
  • 6.2. Calculate Spectral Indices
  • 6.3. Map and Extract Spectral Indices
  • 6.4. Copernicus Data Download

Chapter 7: Summary Tools

Learn how to summarize and visualize environmental data and biodiversity counts using various plotting techniques.

  • 7.1. Data Setup
  • 7.2. Diagnostic Plots
  • 7.3. Species Rank Plots
  • 7.4. Regression Plots
  • 7.5. Presence/Absence

Throughout the Spatial Data R Tutorial, we use diverse and real data to demonstrate some common conservation scenarios relevant to the greater Birds Canada community. This tutorial aims to enrich the learning of R users in academia, consulting, conservation, and beyond and assist them in meeting their project objectives. The most up-to-date version of this tutorial is available on the NatureCounts GitHub repository, with an adapted version and additional resources accessible in article format online.

Acknowledgements

Many people have contributed to the NatureCounts web interface and the R package, including, Denis Lepage, Steffi LaZerte, Paul Morrill and Catherine Jardine. The development of the NatureCounts web interface, R package, and accompanying online books were made possible by funding provided by Environment and Climate Change Canada and the generosity of donors to Birds Canada. We sincerely thank these contributors for their support and dedication to the project.