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Added a min_neighbours parameter to the LidarGroundPointFilter tool
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Added a min_neighbours parameter to the LidarGroundPointFilter tool
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@jblindsay
jblindsay committed Sep 18, 2018
1 parent a264800 commit 909f012
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Showing 4 changed files with 65 additions and 43 deletions.
2 changes: 1 addition & 1 deletion Cargo.lock
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3 changes: 0 additions & 3 deletions Cargo.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -9,9 +9,6 @@ readme = "README.md"
repository = "https://github.com/jblindsay/whitebox-geospatial-analysis-tools/whitebox_tools/"
license = "MIT"

# [profile.release]
# debug = true

[dependencies]
byteorder = "^1.1.0"
kdtree = "0.5.1"
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10 changes: 10 additions & 0 deletions readme.txt
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Expand Up @@ -57,6 +57,16 @@ for more details.
******************

Version 0.11.0 (XX-XX-2018)
- The following tools were added to the project:

- Added a minimum number of neighbours criteria in the neighbourhood search of the
LidarGroundPointFilter tool. In this way, if the fixed-radius search yields fewer
neighbours than this minimum neighbours threshold, a second kNN search is carried
out to identify the k nearest neighbours. This can be preferable for cases where
the point density varies significantly in the data set, e.g. in the case of
terrestrial LiDAR point clouds.



Version 0.10.0 (16-09-2018)
- The following tools were added to the project:
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93 changes: 54 additions & 39 deletions src/tools/lidar_analysis/lidar_ground_point_filter.rs
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Original file line number Diff line number Diff line change
@@ -1,8 +1,8 @@
/*
This tool is part of the WhiteboxTools geospatial analysis library.
Authors: Dr. John Lindsay
Created: June 2, 2017
Last Modified: 13/09/2018
Created: 02/06/2017
Last Modified: 18/09/2018
License: MIT
*/

Expand Down Expand Up @@ -63,6 +63,15 @@ impl LidarGroundPointFilter {
optional: false,
});

parameters.push(ToolParameter {
name: "Minimum Number of Neighbours".to_owned(),
flags: vec!["--min_neighbours".to_owned()],
description: "The minimum number of neighbouring points within search areas. If fewer points than this threshold are idenfied during the fixed-radius search, a subsequent kNN search is performed to identify the k number of neighbours.".to_owned(),
parameter_type: ParameterType::Integer,
default_value: Some("0".to_owned()),
optional: true,
});

parameters.push(ToolParameter {
name: "Inter-point Slope Threshold".to_owned(),
flags: vec!["--slope_threshold".to_owned()],
Expand Down Expand Up @@ -103,7 +112,7 @@ impl LidarGroundPointFilter {
if e.contains(".exe") {
short_exe += ".exe";
}
let usage = format!(">>.*{0} -r={1} -v --wd=\"*path*to*data*\" -i=\"input.las\" -o=\"output.las\" --radius=10.0", short_exe, name).replace("*", &sep);
let usage = format!(">>.*{0} -r={1} -v --wd=\"*path*to*data*\" -i=\"input.las\" -o=\"output.las\" --radius=10.0 --min_neighbours=10 --slope_threshold=30.0 --height_threshold=0.5 --classify", short_exe, name).replace("*", &sep);

LidarGroundPointFilter {
name: name,
Expand Down Expand Up @@ -159,6 +168,7 @@ impl WhiteboxTool for LidarGroundPointFilter {
let mut input_file: String = "".to_string();
let mut output_file: String = "".to_string();
let mut search_radius: f64 = -1.0;
let mut min_points = 0usize;
let mut height_threshold: f64 = 1.0;
let mut slope_threshold: f64 = 15.0;
let ground_class_value = 2u8;
Expand All @@ -183,35 +193,41 @@ impl WhiteboxTool for LidarGroundPointFilter {
}
let flag_val = vec[0].to_lowercase().replace("--", "-");
if flag_val == "-i" || flag_val == "-input" {
if keyval {
input_file = vec[1].to_string();
input_file = if keyval {
vec[1].to_string()
} else {
input_file = args[i + 1].to_string();
}
args[i + 1].to_string()
};
} else if flag_val == "-o" || flag_val == "-output" {
if keyval {
output_file = vec[1].to_string();
output_file = if keyval {
vec[1].to_string()
} else {
output_file = args[i + 1].to_string();
}
args[i + 1].to_string()
};
} else if flag_val == "-radius" {
if keyval {
search_radius = vec[1].to_string().parse::<f64>().unwrap();
search_radius = if keyval {
vec[1].to_string().parse::<f64>().unwrap()
} else {
search_radius = args[i + 1].to_string().parse::<f64>().unwrap();
}
args[i + 1].to_string().parse::<f64>().unwrap()
};
} else if flag_val == "-height_threshold" {
if keyval {
height_threshold = vec[1].to_string().parse::<f64>().unwrap();
height_threshold = if keyval {
vec[1].to_string().parse::<f64>().unwrap()
} else {
height_threshold = args[i + 1].to_string().parse::<f64>().unwrap();
}
args[i + 1].to_string().parse::<f64>().unwrap()
};
} else if flag_val == "-slope_threshold" {
if keyval {
slope_threshold = vec[1].to_string().parse::<f64>().unwrap();
slope_threshold = if keyval {
vec[1].to_string().parse::<f64>().unwrap()
} else {
slope_threshold = args[i + 1].to_string().parse::<f64>().unwrap();
}
args[i + 1].to_string().parse::<f64>().unwrap()
};
} else if flag_val == "-min_neighbours" || flag_val == "-min_neighbors" {
min_points = if keyval {
vec[1].to_string().parse::<usize>().unwrap()
} else {
args[i + 1].to_string().parse::<usize>().unwrap()
};
} else if flag_val == "-classify" {
filter = false;
}
Expand Down Expand Up @@ -287,10 +303,14 @@ impl WhiteboxTool for LidarGroundPointFilter {
let mut index_n: usize;
let mut z_n: f64;
let mut min_z: f64;
let mut ret: Vec<(usize, f64)>;
for point_num in (0..n_points).filter(|point_num| point_num % num_procs == tid) {
let p: PointData = input.get_point_info(point_num);
if p.is_late_return() && !p.is_classified_noise() {
let ret = frs.search(p.x, p.y);
ret = frs.search(p.x, p.y);
if ret.len() < min_points {
ret = frs.knn_search(p.x, p.y, min_points);
}
min_z = f64::MAX;
for j in 0..ret.len() {
index_n = ret[j].0;
Expand Down Expand Up @@ -332,10 +352,14 @@ impl WhiteboxTool for LidarGroundPointFilter {
let mut index_n: usize;
let mut z_n: f64;
let mut max_z: f64;
let mut ret: Vec<(usize, f64)>;
for point_num in (0..n_points).filter(|point_num| point_num % num_procs == tid) {
let p: PointData = input.get_point_info(point_num);
if p.is_late_return() && !p.is_classified_noise() {
let ret = frs.search(p.x, p.y);
ret = frs.search(p.x, p.y);
if ret.len() < min_points {
ret = frs.knn_search(p.x, p.y, min_points);
}
max_z = f64::MIN;
for j in 0..ret.len() {
index_n = ret[j].0;
Expand Down Expand Up @@ -382,13 +406,17 @@ impl WhiteboxTool for LidarGroundPointFilter {
let mut max_slope: f64;
let mut slope: f64;
let mut dist: f64;
let mut ret: Vec<(usize, f64)>;
for point_num in (0..n_points).filter(|point_num| point_num % num_procs == tid) {
let p: PointData = input.get_point_info(point_num);
if residuals[point_num] < height_threshold
&& p.is_late_return()
&& !p.is_classified_noise()
{
let ret = frs.search(p.x, p.y);
ret = frs.search(p.x, p.y);
if ret.len() < min_points {
ret = frs.knn_search(p.x, p.y, min_points);
}
max_slope = f64::MIN;
for j in 0..ret.len() {
dist = ret[j].1;
Expand Down Expand Up @@ -429,19 +457,6 @@ impl WhiteboxTool for LidarGroundPointFilter {
let mut output = LasFile::initialize_using_file(&output_file, &input);
output.header.system_id = "EXTRACTION".to_string();

// for i in 0..n_points {
// if !is_off_terrain[i] {
// output.add_point_record(input.get_record(i));
// }
// if verbose {
// progress = (100.0_f64 * i as f64 / num_points) as i32;
// if progress != old_progress {
// println!("Saving data: {}%", progress);
// old_progress = progress;
// }
// }
// }

/////////////////////
// Output the data //
/////////////////////
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