Below is a list of miscellaneous geospatial operations.


using GeoStats
using GeoStatsImages

๐’Ÿ = geostatsimage("Strebelle")

# 50/50 split perpendicular to (1.,1.)
S = split(๐’Ÿ, 0.5, (1.,1.))

plot(plot(S[1],ms=0.2), plot(S[2],ms=0.2))


Meshes.slice โ€” Function
slice(object, xmin:xmax, ymin:ymax, ...)

Slice the object using real coordinate ranges xmin:xmax, ymin:ymax, ...


This function is equivalent to view(object, Box(first.(ranges), last.(ranges)).

In Julia the range 0.5:10.0 is materialized as [0.5, ..., 9.5] so it won't necessarily include the right value. This behavior is different than the more intuitive behavior of view(object, Box((0.5,0.5), (10.0,10.0)).

# slice image
I = geostatsimage("Strebelle")
S = slice(I, 50.5:100.2, 41.7:81.3)

p1 = plot(plot(I), plot(S), link=:both)

# slide point set
P = sample(I, 100)
S = slice(P, 50.5:150.7, 175.2:250.3)

p2 = plot(plot(P), plot(S), link=:both, ms=3)

plot(p1, p2, layout=(2,1))


GeoStatsBase.uniquecoords โ€” Function
uniquecoords(data, agg=Dict())

Retain locations in data with unique coordinates.

Duplicates of a variable var are aggregated with aggregation function agg[var]. Default aggregation function is mean for continuous variables and first otherwise.

D = georef((z=[0, 1, 0],), [(0.,0.), (1.,0.), (0.,0.)])

U = uniquecoords(D)

Meshes.DataRows{DomainView{2, Float64, PointSet{2, Float64}, Vector{Int64}}, TypedTables.Table{NamedTuple{(:z,), Tuple{Int64}}, 1, NamedTuple{(:z,), Tuple{Vector{Int64}}}}}(2 View{3 PointSet{2,Float64}}, NamedTuple{(:z,), Tuple{Int64}}[(z = 1,), (z = 0,)])


GeoStatsBase.trend โ€” Function
trend(data, vars; degree=1)

Return the deterministic spatial trend for the variables vars in the spatial data. Approximate the trend with a polynomial of given degree.

# quadratic + noise
r = range(-1,stop=1,length=100)
ฮผ = [x^2 + y^2 for x in r, y in r]
ฯต = 0.1rand(100,100)
๐’Ÿ = georef((z=ฮผ+ฯต,))

โ„ณ = trend(๐’Ÿ, :z, degree=2)

plot(plot(๐’Ÿ), plot(โ„ณ))


GeoStatsBase.groupby โ€” Method
groupby(data, var)

Partition spatial data into groups of constant value for spatial variable var.


Missing values are grouped into a separate group.

๐’Ÿ = geostatsimage("Strebelle")

โ„ฑ = groupby(๐’Ÿ, :facies)

plot(plot(โ„ฑ[1],ms=0.2), plot(โ„ฑ[2],ms=0.2))