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pc2dem

Create digital elevation model (DEM) of point cloud data

Description

example

elevModel = pc2dem(ptCloudIn) creates and returns a digital elevation model (DEM) elevModel for the input point cloud. The output matrix contains generalized elevation information of the input point cloud. For more information, see Algorithms.

elevModel = pc2dem(ptCloudIn,gridResolution) additionally specifies the dimensions of the grid element.

[elevModel,xlimits,ylimits] = pc2dem(___) additionally returns the x- and y-limits of the DEM, using any combination of input arguments from previous syntaxes.

example

[___] = pc2dem(___,Name,Value) specifies options using one or more name-value arguments. For example, 'CornerFillMethod','min' specifies for the function to compute the generalized elevation values for the grid corners in the DEM as the minimum elevation in the default search radius of each grid corner.

Examples

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Create a lasFileReader object to read point cloud data stored in aerialLidarData.laz.

 fileName = fullfile(toolboxdir("lidar"),"lidardata","las", ...
            "aerialLidarData.laz");
lasReader = lasFileReader(fileName);

Read point cloud data from the file using the readPointCloud function.

ptCloud = readPointCloud(lasReader);

Visualize the point cloud data.

figure
pcshow(ptCloud.Location)
title("Point Cloud")

Figure contains an axes object. The axes object with title Point Cloud contains an object of type scatter.

Segment the ground points from the point cloud data.

groundPtsIdx = segmentGroundSMRF(ptCloud);

Extract the ground points.

ptCloudWithGround = select(ptCloud,groundPtsIdx);

Visualize the ground points.

figure
pcshow(ptCloudWithGround.Location)
title("Ground Points")

Figure contains an axes object. The axes object with title Ground Points contains an object of type scatter.

Create a digital terrain model (DTM) from the segmented ground points.

terrainModel = pc2dem(ptCloudWithGround);

Visualize the DTM.

figure
imagesc(terrainModel)
colormap(gray)
title("Digital Terrain Model")

Figure contains an axes object. The axes object with title Digital Terrain Model contains an object of type image.

Create a lasFileReader object to read aerial point cloud data from "aerialLidarData.laz".

fileName = fullfile(toolboxdir("lidar"),"lidardata","las", ...
          "aerialLidarData.laz");
lasReader = lasFileReader(fileName);

Read the point cloud data of the first return of the lidar sensor from the LAS file using the readPointCloud function.

ptCloud = readPointCloud(lasReader,"LaserReturns",1);

Create a digital surface model (DSM) of the point cloud with a grid element resolution of 1.1 meters.

gridRes = 1.1;
surfaceModel = pc2dem(ptCloud,gridRes,"CornerFillMethod","max");

Define the location of the illumination source.

azimuthAng = 135;
zenithAng = 45;

Compute the directional gradients of the DSM using the imgradientxy function.

[gx,gy] = imgradientxy(surfaceModel,"sobel");

Normalize the gradients using the grid element resolution.

gx = gx/(8*gridRes);
gy = gy/(8*gridRes);

Compute the slope and aspect of the DSM.

slopeAngle = atand(sqrt(gx.^2 + gy.^2));
aspectAngle = atan2d(gy,-gx);
aspectAngle(aspectAngle < 0) = aspectAngle(aspectAngle < 0) + 360;

Calculate the hillshade using the algorithm from Esri®. A hillshade is a 3-D grayscale representation of a surface, with the relative position of the illumination source taken into account when shading the image.

h = 255.0*((cosd(zenithAng).*cosd(slopeAngle)) ...
    + (sind(zenithAng).*sind(slopeAngle).*cosd(azimuthAng - aspectAngle)));
h(h < 0) = 0;

Visualize the hillshade of the DSM.

figure
imagesc(h)
colormap(gray)

Figure contains an axes object. The axes object contains an object of type image.

Input Arguments

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Input point cloud, specified as a pointCloud object.

Resolution of the grid element along the xy-axes, specified as a two-element vector of the form [x y], or as a scalar for square elements. Values for this argument must be positive real numbers.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Name-Value Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: 'CornerFillMethod','min' selects the type of method to compute the generalized elevation values for each grid corner in the DEM.

Method for grid corner the generalized elevation value calculation, specified as a character vector or a string scalar. The list of supported methods and how they must be specified is as follows:

  • 'min' — Minimum elevation of all the points in the search radius

  • 'max' — Maximum elevation of all the points in the search radius

  • 'mean' — Mean elevation of all the points in the search radius

  • 'idw' — Inverse distance weighted (IDW) mean elevation of all the points in the search radius

Data Types: char | string

Radius of search region around each grid corner, specified as a positive scalar.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Filter size for IDW interpolation to fill unfilled grid corners, specified as a positive odd integer.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Output Arguments

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Digital elevation model, returned as an M-by-N matrix of real values. The values of M and N are computed based on point cloud limits along the xy-axes and the gridResolution.

x-axis limits of the elevation model, returned as a two-element real-valued vector.

y-axis limits of the elevation model, returned as a two-element real-valued vector.

Algorithms

The function uses a local binning algorithm to create a digital elevation model (DEM) of the point cloud data. The algorithm assumes that the elevation of points is along the z-axis.

Local Binning Algorithm:

  • Divide the point cloud into a grid along the xy-dimensions (bird's eye view). Specify the grid dimensions using the gridResolution argument.

  • Utilize the elevation information of all points within a circular region around each grid corner to compute generalized grid values. You can specify the search radius and computation method using the 'SearchRadius' and 'CornerFillMethod' name-value arguments, respectively.

  • If there are no points within the circular region, the algorithm does not compute a value and those grid corners remain unfilled. The function represents them as NaN. The algorithm uses inverse distance weighted (IDW) interpolation to fill the unfilled grid corners. To specify the filter size for the IDW interpolation method, use the 'FilterSize' name-value argument.

Introduced in R2021b