Quick start

Install the package by typing:

julia

] 
add Rasters

then do

julia

using Rasters

Using Rasters to read GeoTiff or NetCDF files will output something similar to the following toy examples. This is possible because Rasters.jl extends DimensionalData.jl so that spatial data can be indexed using named dimensions like X, Y and Ti (time) and e.g. spatial coordinates.

julia

using Rasters, Dates

lon, lat = X(25:1:30), Y(25:1:30)
ti = Ti(DateTime(2001):Month(1):DateTime(2002))
ras = Raster(rand(lon, lat, ti)) # this generates random numbers with the dimensions given

╭──────────────────────────╮
│ 6×6×13 Raster{Float64,3} │
├──────────────────────────┴───────────────────────────────────────────── dims ┐
  ↓ X  Sampled{Int64} 25:1:30 ForwardOrdered Regular Points,
  → Y  Sampled{Int64} 25:1:30 ForwardOrdered Regular Points,
  ↗ Ti Sampled{DateTime} DateTime("2001-01-01T00:00:00"):Month(1):DateTime("2002-01-01T00:00:00") ForwardOrdered Regular Points
├────────────────────────────────────────────────────────────────────── raster ┤
  extent: Extent(X = (25, 30), Y = (25, 30), Ti = (DateTime("2001-01-01T00:00:00"), DateTime("2002-01-01T00:00:00")))

└──────────────────────────────────────────────────────────────────────────────┘
[:, :, 1]
  ↓ →  25         26         27          28           29          30
 25     0.765624   0.422345   0.955165    0.652584     0.678182    0.462025
 26     0.872759   0.923799   0.40098     0.837514     0.701663    0.636847
 27     0.842085   0.535627   0.0551546   0.114666     0.494154    0.596159
 28     0.770693   0.517485   0.175904    0.00756641   0.725256    0.445095
 29     0.163242   0.28253    0.835763    0.201491     0.0717478   0.925
 30     0.646135   0.252615   0.0390615   0.898083     0.0465577   0.196559

Getting the lookup array from dimensions

julia

lon = lookup(ras, X) # if X is longitude
lat = lookup(ras, Y) # if Y is latitude

Sampled{Int64} ForwardOrdered Regular Points
wrapping: 25:1:30

Select by index

Selecting a time slice by index is done via

julia

ras[Ti(1)]

╭───────────────────────╮
│ 6×6 Raster{Float64,2} │
├───────────────────────┴───────────────────────────── dims ┐
  ↓ X Sampled{Int64} 25:1:30 ForwardOrdered Regular Points,
  → Y Sampled{Int64} 25:1:30 ForwardOrdered Regular Points
├─────────────────────────────────────────────────── raster ┤
  extent: Extent(X = (25, 30), Y = (25, 30))

└───────────────────────────────────────────────────────────┘
  ↓ →  25         26         27          28           29          30
 25     0.765624   0.422345   0.955165    0.652584     0.678182    0.462025
 26     0.872759   0.923799   0.40098     0.837514     0.701663    0.636847
 27     0.842085   0.535627   0.0551546   0.114666     0.494154    0.596159
 28     0.770693   0.517485   0.175904    0.00756641   0.725256    0.445095
 29     0.163242   0.28253    0.835763    0.201491     0.0717478   0.925
 30     0.646135   0.252615   0.0390615   0.898083     0.0465577   0.196559

also

julia

ras[Ti=1]

╭───────────────────────╮
│ 6×6 Raster{Float64,2} │
├───────────────────────┴───────────────────────────── dims ┐
  ↓ X Sampled{Int64} 25:1:30 ForwardOrdered Regular Points,
  → Y Sampled{Int64} 25:1:30 ForwardOrdered Regular Points
├─────────────────────────────────────────────────── raster ┤
  extent: Extent(X = (25, 30), Y = (25, 30))

└───────────────────────────────────────────────────────────┘
  ↓ →  25         26         27          28           29          30
 25     0.765624   0.422345   0.955165    0.652584     0.678182    0.462025
 26     0.872759   0.923799   0.40098     0.837514     0.701663    0.636847
 27     0.842085   0.535627   0.0551546   0.114666     0.494154    0.596159
 28     0.770693   0.517485   0.175904    0.00756641   0.725256    0.445095
 29     0.163242   0.28253    0.835763    0.201491     0.0717478   0.925
 30     0.646135   0.252615   0.0390615   0.898083     0.0465577   0.196559

or and interval of indices using the syntax =a:b or (a:b)

julia

ras[Ti(1:10)]

╭──────────────────────────╮
│ 6×6×10 Raster{Float64,3} │
├──────────────────────────┴───────────────────────────────────────────── dims ┐
  ↓ X  Sampled{Int64} 25:1:30 ForwardOrdered Regular Points,
  → Y  Sampled{Int64} 25:1:30 ForwardOrdered Regular Points,
  ↗ Ti Sampled{DateTime} DateTime("2001-01-01T00:00:00"):Month(1):DateTime("2001-10-01T00:00:00") ForwardOrdered Regular Points
├────────────────────────────────────────────────────────────────────── raster ┤
  extent: Extent(X = (25, 30), Y = (25, 30), Ti = (DateTime("2001-01-01T00:00:00"), DateTime("2001-10-01T00:00:00")))

└──────────────────────────────────────────────────────────────────────────────┘
[:, :, 1]
  ↓ →  25         26         27          28           29          30
 25     0.765624   0.422345   0.955165    0.652584     0.678182    0.462025
 26     0.872759   0.923799   0.40098     0.837514     0.701663    0.636847
 27     0.842085   0.535627   0.0551546   0.114666     0.494154    0.596159
 28     0.770693   0.517485   0.175904    0.00756641   0.725256    0.445095
 29     0.163242   0.28253    0.835763    0.201491     0.0717478   0.925
 30     0.646135   0.252615   0.0390615   0.898083     0.0465577   0.196559

Select by value

julia

ras[Ti=At(DateTime(2001))]

╭───────────────────────╮
│ 6×6 Raster{Float64,2} │
├───────────────────────┴───────────────────────────── dims ┐
  ↓ X Sampled{Int64} 25:1:30 ForwardOrdered Regular Points,
  → Y Sampled{Int64} 25:1:30 ForwardOrdered Regular Points
├─────────────────────────────────────────────────── raster ┤
  extent: Extent(X = (25, 30), Y = (25, 30))

└───────────────────────────────────────────────────────────┘
  ↓ →  25         26         27          28           29          30
 25     0.765624   0.422345   0.955165    0.652584     0.678182    0.462025
 26     0.872759   0.923799   0.40098     0.837514     0.701663    0.636847
 27     0.842085   0.535627   0.0551546   0.114666     0.494154    0.596159
 28     0.770693   0.517485   0.175904    0.00756641   0.725256    0.445095
 29     0.163242   0.28253    0.835763    0.201491     0.0717478   0.925
 30     0.646135   0.252615   0.0390615   0.898083     0.0465577   0.196559

More options are available, like Near, Contains and Where.

Dimensions

Rasters uses X, Y, and Z dimensions from DimensionalData to represent spatial directions like longitude, latitude and the vertical dimension, and subset data with them. Ti is used for time, and Band represent bands. Other dimensions can have arbitrary names, but will be treated generically. See DimensionalData for more details on how they work.

Lookup Arrays

These specify properties of the index associated with e.g. the X and Y dimension. Rasters.jl defines additional lookup arrays: Projected to handle dimensions with projections, and Mapped where the projection is mapped to another projection like EPSG(4326). Mapped is largely designed to handle NetCDF dimensions, especially with Explicit spans.

Subsetting an object

Regular getindex (e.g. A[1:100, :]) and view work on all objects just as with an Array. view is always lazy, and reads from disk are deferred until getindex is used. DimensionalData.jl Dimensions and Selectors are the other way to subset an object, making use of the objects index to find values at e.g. certain X/Y coordinates. The available selectors are listed here:

Selectors	Description
`At(x)`	get the index exactly matching the passed in value(s).
`Near(x)`	get the closest index to the passed in value(s).
`Where(f::Function)`	filter the array axis by a function of the dimension index values.
`a..b`/`Between(a, b)`	get all indices between two values, excluding the high value.
`Contains(x)`	get indices where the value x falls within an interval.

Info

Use the .. selector to take a view of madagascar:

julia

using Rasters, RasterDataSources
const RS = Rasters
using CairoMakie
CairoMakie.activate!()

A = Raster(WorldClim{BioClim}, 5)
madagascar = view(A, X(43.25 .. 50.48), Y(-25.61 .. -12.04))
# Note the space between .. -12
Makie.plot(madagascar)

Quick start ​

Install the package by typing: ​

Getting the lookup array from dimensions ​

Select by index ​

Select by value ​

Subsetting an object ​

Quick start

Install the package by typing:

Getting the lookup array from dimensions

Select by index

Select by value

Subsetting an object