Tutorials
Tutorial 1: Working with Domains
1.1 Understanding Domains
What domains represent
Types: Raster, Polygon, RasterStack
1.2 Creating Domains from Different Sources
1.3 Masking and Constraints
Tutorial 2: Simple Sampling Methods
2.1 Simple Random Sampling
2.2 Stratified Sampling
Tutorial 3: Spatially Balanced Sampling
3.1 Why Spatial Balance Matters
3.2 Generalized Random Tessellation Stratified (GRTS)
3.3 Pivotal Method
3.4 Spatially Correlated Poisson
3.5 Balanced Acceptance Sampling (BAS)
Tutorial 4: Environmentally Balanced Sampling
4.1 Spatial Stratification
- Using auxiliary variables to generate strata
4.2 Cube Method
Conceptual Overview
Flight and Landing Phrase
Tutorial 5: Inclusion Probabilities
5.1 Understanding Inclusion Probabilities
5.2 Creating Custom Inclusion Surfaces
5.3 Tilting and Transforming
Tutorial 6: Adaptive Sampling
6.1 Why adaptive sampling?
6.2 Active Learning
6.3 Adaptive Hotspot Sampling
Tutorial 7: Evaluating Sampling Designs
7.1 Spatial Balance Metrics
Moran's I
Voronoi Polygon Area Variance
7.2 Environmental Balance
Jensen Shannon
Mahalanobis Distance
7.3 Design-Based Properties
- Variance, bias, mse of mean under ground truth raster values
Tutorial 8: Foo Bar:
8.1 Climate Rarity
8.2 Climate Velocity
Tutorial 9: Advanced Topics:
8.1 Handling Practical Constraints
8.2 Handling Large Domains
8.3 Temporal Sampling
8.4 Performance Optimization