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vignettes/hexsmoothR-complete-guide.Rmd

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@@ -27,6 +27,7 @@ hexsmoothR implements hexagonal grid-based spatial smoothing algorithms optimize
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## Hexagonal Grid Advantages
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Hexagonal grids offer several technical advantages for spatial analysis:
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- Six neighbors per cell vs. four in square grids
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- Eliminates diagonal artifacts and edge effects
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- Improved packing efficiency and uniform cell shapes
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## Coastal Data Demonstration
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Coastal vegetation data demonstrates hexagonal smoothing effectiveness:
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- Complex, irregular shorelines challenging traditional grid methods
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- Natural noise from water interference, cloud cover, and sensor issues
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- Underlying environmental patterns suitable for spatial enhancement
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## Workflow Overview
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The complete hexagonal smoothing workflow:
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1. Data preparation and validation
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2. Hexagonal grid creation with appropriate cell sizing
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3. Raster data extraction into hexagonal cells
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## Algorithm Implementation
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The hexagonal smoothing algorithm implements weighted neighbor averaging:
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- First-order neighbors: Directly adjacent hexagons
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- Second-order neighbors: Neighbors of first-order neighbors
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- Weighted averaging: Center cell and neighbors contribute according to specified weights
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### Coordinate Reference Systems (CRS)
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CRS selection affects hexagonal grid accuracy and cell sizing:
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- Projected CRS (UTM, State Plane): cell_size in meters
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- Geographic CRS (WGS84, NAD83): cell_size in degrees
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- Package handles CRS transformations automatically
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### Cell Size and CRS Dependencies
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Cell size units depend on coordinate reference system:
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- Projected CRS (UTM, State Plane): cell_size in meters
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- Geographic CRS (WGS84, NAD83): cell_size in degrees
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