Geomorphometry.jl

BPI stands for Bathymetric Position Index (Lundblad et al., 2006), which is defined as the difference between a central pixel and the mean of the cells in an annulus around it.

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Geomorphometry.RIE Function

julia

RIE(dem::AbstractMatrix{<:Real})

RIE stands for Roughness Index Elevation, which quantifies the standard deviation of residual topography (Cavalli et al., 2008)

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Geomorphometry.SPI Method

julia

SPI(dem::AbstractMatrix; method=D8(), cellsize=cellsize(dem))

Computes the Stream Power Index (SPI) of a digital elevation model (DEM) dem with an optional method for flow direction and a cellsize.

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Geomorphometry.TPI Function

julia

TPI(dem::AbstractMatrix{<:Real})

TPI stands for Topographic Position Index, which is defined as the difference between a central pixel and the mean of its surrounding cells (see Wilson et al 2007, Marine Geodesy 30:3-35).

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Geomorphometry.TRI Method

julia

TRI(dem::AbstractMatrix{<:Real})

TRI stands for Terrain Ruggedness Index, which measures the difference between a central pixel and its surrounding cells. This algorithm uses the square root of the sum of the square of the difference between a central pixel and its surrounding cells. This is recommended for terrestrial use cases.

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Geomorphometry.TWI Method

julia

TWI(dem::AbstractMatrix; method=D8(), cellsize=cellsize(dem))

Computes the Topographic Wetness Index (TWI) of a digital elevation model (DEM) dem with an optional method for flow direction and a cellsize.

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Geomorphometry.aspect Method

julia

aspect(dem::Matrix{<:Real}, method=Horn())

Aspect is direction of slope.

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Geomorphometry.entropy Method

julia

entropy(dem::AbstractMatrix{<:Real}; step=0.5)

Entropy calculates the Shannon entropy of the surrounding cells of a central cell. step is the bin size for the histogram.

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Geomorphometry.filldepressions Function

julia

filldepressions(dem::AbstractMatrix, mask::Matrix{Bool})

Performs the Priority-Flood algorithm (Barnes et al., 2014) on the given digital elevation model (DEM) dem with an optional mask.

Arguments

dem::AbstractMatrix: A 2D array representing the digital elevation model (DEM).
mask::AbstractMatrix{Bool}: A 2D boolean array representing the mask. Cells with true values are considered in the computation, while cells with false values are ignored.

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Geomorphometry.flowaccumulation Function

julia

flowaccumulation(dem::AbstractMatrix, closed::Matrix{Bool}, method::FlowDirectionMethod)

Computes the flow accumulation of a digital elevation model (DEM) dem with an optional closed mask and a method for flow direction. Returns the flow accumulation and the flow direction (local drainage direction or ldd)

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Geomorphometry.hillshade Method

julia

hillshade(dem::Matrix{<:Real}; azimuth=315.0, zenith=45.0, cellsize=cellsize(dem))

hillshade is the simulated illumination of a surface based on its slope and aspect given a light source with azimuth and zenith angles in °, as defined in Burrough, P. A., and McDonell, R. A., (1998).

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Geomorphometry.multihillshade Method

julia

multihillshade(dem::AbstractMatrix{<:Real}; cellsize=cellsize(dem))

multihillshade is the simulated illumination of a surface based on its slope and aspect. Like hillshade, but now using multiple sources as defined in Mark, R.K. (1992), similar to GDALs -multidirectional.

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Geomorphometry.pitremoval Method

julia

pitremoval(dem::AbstractMatrix{<:Real})

Remove pits from a DEM Array if the center cell of a 3x3 patch is limit lower or than the surrounding cells.

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Geomorphometry.plan_curvature Method

julia

plan_curvature(dem::AbstractMatrix{<:Real}; cellsize = cellsize(dem), radius=1)

Calculate projected contour curvature (plan curvature) as defined by Minár et al., (2020).

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Geomorphometry.pmf Method

julia

B, flags = pmf(A; ωₘ, slope, dhₘ, dh₀, cellsize, adjust, erode)

Applies the progressive morphological filter by Zhang (2003) to A.

Output

B::Array{T,2} Maximum allowable values
flags::Array{Float64,2} A sized array with window sizes if filtered, zero if not filtered.

Afterwards, one can retrieve the resulting mask for A by A .<= B or flags .== 0..

Arguments

A::Array{T,2} Input Array
ωₘ::Real=20. Maximum window size [m]
slope::Real=0.01 Terrain slope [m/m]
dhₘ::Real=2.5 Maximum elevation threshold [m]
dh₀::Real=0.2 Initial elevation threshold [m]
cellsize::Real=1. Cellsize in [m]

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Geomorphometry.profile_curvature Method

julia

profile_curvature(dem::AbstractMatrix{<:Real}; cellsize = cellsize(dem), radius=1)

Calculate normal slope line curvature (profile curvature) as defined by Minár et al., (2020).

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Geomorphometry.pssm Method

julia

image = pssm(dem; exaggeration=2.3, resolution=1.0)

Perceptually Shaded Slope Map by Pingel, Clarke., (2014).

Output

image::Gray{T,2} Grayscale image

Arguments

A::Array{Real,2} Input Array
exaggeration::Real=2.3 Factor to exaggerate elevation
cellsize::Real=1.0 Size of cell to account for horizontal resolution if different from vertical resolution

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Geomorphometry.roughness Function

julia

roughness(dem::AbstractMatrix{<:Real})

Roughness is the largest inter-cell difference of a central pixel and its surrounding cell, as defined in Wilson et al (2007, Marine Geodesy 30:3-35).

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Geomorphometry.rugosity Method

julia

rugosity(dem::AbstractMatrix{<:Real})

Compute the rugosity of a DEM, which is the ratio between the surface area divided by the planimetric area.

Jenness 2019 https://onlinelibrary.wiley.com/doi/abs/10.2193/0091-7648(2004)032[0829%3ACLSAFD]2.0.CO%3B2

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Geomorphometry.skb Method

julia

mask = skb(A; mean=mean(A))

Applies skewness balancing by Bartels e.a (2006) to A. Improved the performance by applying a binary search to find the threshold value.

Output

mask::BitMatrix Mask of allowed values

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Geomorphometry.skbr Method

julia

mask = skbr(A; iterations=10)

Applies recursive skewness balancing by Bartels e.a (2010) to A. Applies skb iterations times to the object (non-terrain) mask, as to include more (sloped) terrain.

Output

mask::BitMatrix Mask of allowed values

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Geomorphometry.slope Method

julia

slope(dem::Matrix{<:Real}; cellsize=cellsize(dem), method=Horn(), exaggeration=1.0)

Slope is the rate of change between a cell and its neighbors.

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Geomorphometry.smf Method

julia

B = smf(A; ω, slope, dhₘ, dh₀, cellsize)

Applies the simple morphological filter by Pingel et al. (2013) to A.

Output

B::Array{Float64,2} A filtered version of A

Arguments

A::Array{T,2} Input Array
ω::Float64=18. Maximum window size [m]
slope::Float64=0.01 Terrain slope [m/m]
cellsize::Float64=1. Cellsize in [m]

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Geomorphometry.spread Method

julia

spread(points::Matrix{<:Real}, initial::Matrix{<:Real}, friction::Real; distance=Euclidean(), res=1.0)
spread(points::Matrix{<:Real}, initial::Real, friction::Real; distance=Euclidean(), res=1.0)

Optimized (and more accurate) function based on the same friction everywhere.

When the friction is the same everywhere, there's no need for searching the shortest cost path, as one can just take a direct line to the input points.

The calculated cost is more accurate, as there's no 'zigzag' from cell center to cell center.

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Geomorphometry.spread Method

julia

spread(::Eastman, points::Matrix{<:Real}, initial::Matrix{<:Real}, friction::Matrix{<:Real}; res=1, limit=Inf, iterations=3)

Pushbroom method for friction costs as discussed by Eastman (1989). This method should scale better (linearly) than the Tomlin (1983) method, but can require more iterations than set by default (3) in the case of maze-like, uncrossable obstacles.

Output

Array{Float64,2} Total friction distance

Arguments

points::Matrix{<:Real} Input Array
initial::Matrix{<:Real} Factor to exaggerate elevation
friction::Matrix{<:Real} Resolution of cell size
res=1 Resolution or cell size
limit=Inf Initial fill value

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Geomorphometry.spread Method

julia

spread(points::Matrix{<:Real}, initial::Matrix{<:Real}, friction::Matrix{<:Real}; cellsize=(1,1), limit=Inf, method=Tomlin())

Total friction distance spread from points from initial with friction. By default uses Tomlin, see SpreadMethod for other algorithms.

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Geomorphometry.spread Method

julia

spread(::Tomlin, points::Matrix{<:Real}, initial::Matrix{<:Real}, friction::Matrix{<:Real}; res=1, limit=Inf, method=Tomlin())

Total friction distance spread from points as by Tomlin (1983). This is also the method implemented by PCRaster.

Output

Array{Float64,2} Total friction distance

Arguments

points::Matrix{<:Real} Input Array
initial::Matrix{<:Real} Initial values of the result
friction::Matrix{<:Real} Resolution of cell size
res=1 Resolution or cell size
limit=Inf Initial fill value

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Geomorphometry.tangential_curvature Method

julia

tangential_curvature(dem::AbstractMatrix{<:Real}; cellsize = cellsize(dem), radius=1)

Calculate normal contour curvature (tangential curvature) as defined by Minár et al., (2020).

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Reference - Internal functions

Geomorphometry.MaximumDownwardGradient Type

Maximum Downward Gradient

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Geomorphometry.SpreadMethod Type

Spread algorithms.

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Geomorphometry.cellsize Method

julia

cellsize(dem)

Return an Tuple with the x and y length of each cell of the dem. Set them negatively to flip the image.

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Geomorphometry.entropy! Method

julia

entropy!(dem::AbstractMatrix{<:Real})

Entropy calculates the Shannon entropy of the surrounding cells of a central cell.

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Geomorphometry.opening! Method

Apply the opening operation to A with window size ω.

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Geomorphometry.opening_circ! Method

Apply the opening operation to A with window size ω.

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Geomorphometry.prominence Method

julia

prominence(dem::AbstractMatrix{<:Real})

Prominence calculates the number of cells that are lower or equal than the central cell. Thus, 8 is a local maximum (peak), while 0 is a local minimum (pit).

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Geomorphometry.round_odd Method

julia

round_odd(x)

Rounds x to the nearest odd number.

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Index ​

Reference - Exported functions ​

Reference - Internal functions ​

Index

Reference - Exported functions

Reference - Internal functions