more orga

docs/src/.vitepress/config.mts

@@ -19,6 +19,7 @@ const navTemp = {
     { text: 'Manual',
       items: [
         { text: 'Methods', link: '/manual/methods' },
+        { text: 'cellarea', link: '/manual/cellarea' },
         { text: 'Array Operations', link: '/manual/array_operations' },
         { text: 'Data Sources', link: '/manual/data_sources' },
         { text: 'Plots',
@@ -31,6 +32,8 @@ const navTemp = {
     },
     { text: 'Tutorials',
       items: [
+        { text: 'Spatial mean', link: '/tutorials/spatial_mean' },
+        { text: 'Reprojection and resampling', link: '/tutorials/resample_warp'},
         { text: 'Species Distribution Modelling', link: '/tutorials/gbif_wflow' },
       ]
     },
@@ -99,6 +102,7 @@ export default defineConfig({
       { text: 'Manual',
         items: [
           { text: 'Methods', link: '/manual/methods' },
+          { text: 'cellarea', link: '/manual/cellarea' },
           { text: 'Array Operations', link: '/manual/array_operations' },
           { text: 'Data Sources', link: '/manual/data_sources' },
           { text: 'Plots',
@@ -111,6 +115,8 @@ export default defineConfig({
       },
       { text: 'Tutorials',
         items: [
+          { text: 'Spatial mean', link: '/tutorials/spatial_mean' },
+          { text: 'Reprojection and resampling', link: '/tutorials/resample_warp'},
           { text: 'Species Distribution Modelling', link: '/tutorials/gbif_wflow' },
         ]
       },

docs/src/manual/cellarea.md

@@ -8,63 +8,59 @@ CollapsedDocStrings=true
 cellarea
 ```
 
-`cellarea` computes the area of each cell in a raster.  
-This is useful for a number of reasons - if you have a variable like 
+Computing the area of each cell in a raster is useful for a number of reasons - if you have a variable like 
 population per cell, or elevation ([spatially extensive variables](https://r-spatial.org/book/05-Attributes.html#sec-extensiveintensive)),
 you'll want to account for the fact that different cells have different areas.
 
-`cellarea` returns a Raster with the same x and y dimensions as the input, 
-where each value in the raster encodes the area of the cell (in meters by default).
-
-You can specify whether you want to compute the area in the plane of your projection 
-(`Planar()`), on a sphere of some radius (`Spherical(; radius=...)`).
-<!-- or on an ellipsoid 
-(`Geodetic()`), using the first argument.-->
-
 Let's construct a raster and see what this looks like!  We'll keep it in memory.
 
-The spherical <!-- and geodetic --> method relies on the [Proj.jl](https://github.com/JuliaGeo/Proj.jl) package to perform coordinate transformation, so that has to be loaded explicitly.
+The spherical method relies on the [Proj.jl](https://github.com/JuliaGeo/Proj.jl) package to perform coordinate transformation, so that has to be loaded explicitly.
 
-````@example cella
+````@example cellarea
 using Rasters, Proj
 ````
 
-To construct a raster, we'll need to specify the x and y dimensions.  These are called "lookups" in Rasters.jl.
+To construct a raster, we'll need to specify the `x` and `y` dimensions.  These are called `lookups` in `Rasters.jl.`
+
+````@example cellarea
 using Rasters.Lookups
+````
+
 We can now construct the x and y lookups.  Here we'll use a start-at-one, step-by-five grid.
 Note that we're specifying that the "sampling", i.e., what the coordinates actually mean, 
 is `Intervals(Start())`, meaning that the coordinates are the starting point of each interval.
 
 This is in contrast to `Points()` sampling, where each index in the raster represents the value at a sampling point;
 here, each index represents a grid cell, which is defined by the coordinate being at the start.
 
-````@example cella
+````@example cellarea
 x = X(1:5:30; sampling = Intervals(Start()), crs = EPSG(4326))
-y = Y(50:5:80; sampling = Intervals(Start()), crs = EPSG(4326))
+y = Y(50:5:80; sampling = Intervals(Start()), crs = EPSG(4326));
+nothing # hide
 ````
 
 I have chosen the y-range here specifically so we can show the difference between spherical and planar `cellarea`.
 
-````@example cella
+````@ansi cellarea
 ras = Raster(ones(x, y); crs = EPSG(4326))
 ````
 
 We can just call `cellarea` on this raster, which returns cell areas in meters, on Earth, assuming it's a sphere:
 
-````@example cella
+````@ansi cellarea
 cellarea(ras)
 ````
 
 and if we plot it, you can see the difference in cell area as we go from the equator to the poles:
 
-````@example cella
-using Makie, CairoMakie# , GeoMakie
-heatmap(ras; axis = (; aspect = DataAspect()))
+````@example cellarea
+using CairoMakie
+heatmap(cellarea(ras); axis = (; aspect = DataAspect()))
 ````
 
 We can also try this using the planar method, which simply computes the area of the rectangle using `area = x_side_length * y_side_length`:
 
-````@example cella
+````@ansi cellarea
 cellarea(Planar(), ras)
 ````
 

docs/src/manual/data_sources.md

@@ -43,10 +43,6 @@ They are always 3 dimensional, and have `Y`, `X` and [`Band`](@ref) dimensions.
 using Rasters
 ````
 
-````@docs
-smapseries
-````
-
 ## Writing file formats to disk
 
 Files can be written to disk with ArchGDAL.jl and NCDatasets.jl backends using