/*
* Copyright (C) 2011-2012 Dr. John Lindsay <jlindsay@uoguelph.ca>
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package plugins;
import java.util.Date;
import java.util.List;
import whitebox.geospatialfiles.WhiteboxRaster;
import whitebox.geospatialfiles.LASReader;
import whitebox.geospatialfiles.LASReader.PointRecord;
import whitebox.interfaces.WhiteboxPluginHost;
import whitebox.interfaces.WhiteboxPlugin;
import whitebox.structures.KdTree;
import java.io.*;
/**
* This tool can be used to interpolate a regular grid raster from a point cloud LiDAR dataset where each grid cell contains the point density within a user-specified radius.
*
* @author Dr. John Lindsay email: jlindsay@uoguelph.ca
*/
public class LiDAR_PointDensity implements WhiteboxPlugin {
private WhiteboxPluginHost myHost = null;
private String[] args;
/**
* Used to retrieve the plugin tool's name. This is a short, unique name
* containing no spaces.
*
* @return String containing plugin name.
*/
@Override
public String getName() {
return "LiDAR_PointDensity";
}
/**
* Used to retrieve the plugin tool's descriptive name. This can be a longer
* name (containing spaces) and is used in the interface to list the tool.
*
* @return String containing the plugin descriptive name.
*/
@Override
public String getDescriptiveName() {
return "Point Density (LiDAR)";
}
/**
* Used to retrieve a short description of what the plugin tool does.
*
* @return String containing the plugin's description.
*/
@Override
public String getToolDescription() {
return "Calculates the spatial pattern of point density fore a LiDAR data set.";
}
/**
* Used to identify which toolboxes this plugin tool should be listed in.
*
* @return Array of Strings.
*/
@Override
public String[] getToolbox() {
String[] ret = {"LidarTools"};
return ret;
}
/**
* Sets the WhiteboxPluginHost to which the plugin tool is tied. This is the
* class that the plugin will send all feedback messages, progress updates,
* and return objects.
*
* @param host The WhiteboxPluginHost that called the plugin tool.
*/
@Override
public void setPluginHost(WhiteboxPluginHost host) {
myHost = host;
}
/**
* Used to communicate feedback pop-up messages between a plugin tool and
* the main Whitebox user-interface.
*
* @param feedback String containing the text to display.
*/
private void showFeedback(String message) {
if (myHost != null) {
myHost.showFeedback(message);
} else {
System.out.println(message);
}
}
/**
* Used to communicate a return object from a plugin tool to the main
* Whitebox user-interface.
*
* @return Object, such as an output WhiteboxRaster.
*/
private void returnData(Object ret) {
if (myHost != null) {
myHost.returnData(ret);
}
}
private int previousProgress = 0;
private String previousProgressLabel = "";
/**
* Used to communicate a progress update between a plugin tool and the main
* Whitebox user interface.
*
* @param progressLabel A String to use for the progress label.
* @param progress Float containing the progress value (between 0 and 100).
*/
private void updateProgress(String progressLabel, int progress) {
if (myHost != null && ((progress != previousProgress)
|| (!progressLabel.equals(previousProgressLabel)))) {
myHost.updateProgress(progressLabel, progress);
}
previousProgress = progress;
previousProgressLabel = progressLabel;
}
/**
* Used to communicate a progress update between a plugin tool and the main
* Whitebox user interface.
*
* @param progress Float containing the progress value (between 0 and 100).
*/
private void updateProgress(int progress) {
if (myHost != null && progress != previousProgress) {
myHost.updateProgress(progress);
}
previousProgress = progress;
}
/**
* Sets the arguments (parameters) used by the plugin.
*
* @param args An array of string arguments.
*/
@Override
public void setArgs(String[] args) {
this.args = args.clone();
}
private boolean cancelOp = false;
/**
* Used to communicate a cancel operation from the Whitebox GUI.
*
* @param cancel Set to true if the plugin should be canceled.
*/
@Override
public void setCancelOp(boolean cancel) {
cancelOp = cancel;
}
private void cancelOperation() {
showFeedback("Operation cancelled.");
updateProgress("Progress: ", 0);
}
private boolean amIActive = false;
/**
* Used by the Whitebox GUI to tell if this plugin is still running.
*
* @return a boolean describing whether or not the plugin is actively being
* used.
*/
@Override
public boolean isActive() {
return amIActive;
}
/**
* Used to execute this plugin tool.
*/
@Override
public void run() {
/* The problem with this algorithm is that the implementation of the
* k-d tree used here only allows you to return the n-closest neighbours
* and does not allow you to search for points that are within a specified
* distance. This will introduce an inaccuracy in point density estimates.
*/
amIActive = true;
String inputFilesString = null;
String[] pointFiles;
String outputHeader = null;
int row, col;
int nrows, ncols;
double x, y;
double z = 0;
int a, i;
int progress = 0;
int numPoints = 0;
double maxDist = Double.POSITIVE_INFINITY;
double minX = Double.POSITIVE_INFINITY;
double maxX = Double.NEGATIVE_INFINITY;
double minY = Double.POSITIVE_INFINITY;
double maxY = Double.NEGATIVE_INFINITY;
double north, south, east, west;
double resolution = 1;
String str1 = null;
FileWriter fw = null;
BufferedWriter bw = null;
PrintWriter out = null;
List<KdTree.Entry<Double>> results;
double noData = -32768;
double northing, easting;
String returnNumberToInterpolate = "all points";
String suffix = "";
boolean excludeNeverClassified = false;
boolean excludeUnclassified = false;
boolean excludeBareGround = false;
boolean excludeLowVegetation = false;
boolean excludeMediumVegetation = false;
boolean excludeHighVegetation = false;
boolean excludeBuilding = false;
boolean excludeLowPoint = false;
boolean excludeModelKeyPoint = false;
boolean excludeWater = false;
// get the arguments
if (args.length <= 0) {
showFeedback("Plugin parameters have not been set.");
return;
}
inputFilesString = args[0];
suffix = args[1].trim();
returnNumberToInterpolate = args[2].toLowerCase();
resolution = Double.parseDouble(args[3]);
excludeNeverClassified = Boolean.parseBoolean(args[4]);
excludeUnclassified = Boolean.parseBoolean(args[5]);
excludeBareGround = Boolean.parseBoolean(args[6]);
excludeLowVegetation = Boolean.parseBoolean(args[7]);
excludeMediumVegetation = Boolean.parseBoolean(args[8]);
excludeHighVegetation = Boolean.parseBoolean(args[9]);
excludeBuilding = Boolean.parseBoolean(args[10]);
excludeLowPoint = Boolean.parseBoolean(args[11]);
excludeModelKeyPoint = Boolean.parseBoolean(args[12]);
excludeWater = Boolean.parseBoolean(args[13]);
// check to see that the inputHeader and outputHeader are not null.
if ((inputFilesString.length() <= 0)) {
showFeedback("One or more of the input parameters have not been set properly.");
return;
}
try {
boolean[] classValuesToExclude = new boolean[32]; // there can be up to 32 different classes in future versions
if (excludeNeverClassified) { classValuesToExclude[0] = true; }
if (excludeUnclassified) { classValuesToExclude[1] = true; }
if (excludeBareGround) { classValuesToExclude[2] = true; }
if (excludeLowVegetation) { classValuesToExclude[3] = true; }
if (excludeMediumVegetation) { classValuesToExclude[4] = true; }
if (excludeHighVegetation) { classValuesToExclude[5] = true; }
if (excludeBuilding) { classValuesToExclude[6] = true; }
if (excludeLowPoint) { classValuesToExclude[7] = true; }
if (excludeModelKeyPoint) { classValuesToExclude[8] = true; }
if (excludeWater) { classValuesToExclude[9] = true; }
pointFiles = inputFilesString.split(";");
int numPointFiles = pointFiles.length;
long numPointsInFile = 0;
maxDist = (resolution * 2) * (resolution * 2); // actually squared
PointRecord point;
double[] entry;
for (int j = 0; j < numPointFiles; j++) {
LASReader las = new LASReader(pointFiles[j]);
progress = (int)((j + 1) * 100d / numPointFiles);
updateProgress("Loop " + (j + 1) + " of " + numPointFiles + " Reading point data:", progress);
numPointsInFile = las.getNumPointRecords();
// first count how many valid points there are.
numPoints = 0;
for (a = 0; a < las.getNumPointRecords(); a++) {
point = las.getPointRecord(a);
if (returnNumberToInterpolate.equals("all points")) {
if (!point.isPointWithheld() &&
!(classValuesToExclude[point.getClassification()])) {
numPoints++;
}
} else if (returnNumberToInterpolate.equals("first return")) {
if (!point.isPointWithheld() &&
!(classValuesToExclude[point.getClassification()]) &&
point.getReturnNumber() == 1) {
numPoints++;
}
} else { // if (returnNumberToInterpolate.equals("last return")) {
if (!point.isPointWithheld() &&
!(classValuesToExclude[point.getClassification()]) &&
point.getReturnNumber() == point.getNumberOfReturns()) {
numPoints++;
}
}
}
// now read the valid points into the k-dimensional tree.
minX = Double.POSITIVE_INFINITY;
maxX = Double.NEGATIVE_INFINITY;
minY = Double.POSITIVE_INFINITY;
maxY = Double.NEGATIVE_INFINITY;
KdTree<Double> pointsTree = new KdTree.SqrEuclid<Double>(2, new Integer(numPoints));
// read the points in
if (returnNumberToInterpolate.equals("all points")) {
for (a = 0; a < numPointsInFile; a++) {
point = las.getPointRecord(a);
if (!point.isPointWithheld()
&& !(classValuesToExclude[point.getClassification()])) {
x = point.getX();
y = point.getY();
z = point.getZ();
entry = new double[]{y, x};
pointsTree.addPoint(entry, z);
if (x < minX) {
minX = x;
}
if (x > maxX) {
maxX = x;
}
if (y < minY) {
minY = y;
}
if (y > maxY) {
maxY = y;
}
}
progress = (int) (100d * (a + 1) / numPointsInFile);
if ((progress % 2) == 0) {
updateProgress("Reading point data:", progress);
}
}
} else if (returnNumberToInterpolate.equals("first return")) {
for (a = 0; a < numPointsInFile; a++) {
point = las.getPointRecord(a);
if (!point.isPointWithheld()
&& !(classValuesToExclude[point.getClassification()]) &&
point.getReturnNumber() == 1) {
x = point.getX();
y = point.getY();
z = point.getZ();
entry = new double[]{y, x};
pointsTree.addPoint(entry, z);
if (x < minX) {
minX = x;
}
if (x > maxX) {
maxX = x;
}
if (y < minY) {
minY = y;
}
if (y > maxY) {
maxY = y;
}
}
progress = (int) (100d * (a + 1) / numPointsInFile);
if ((progress % 2) == 0) {
updateProgress("Reading point data:", progress);
}
}
} else { // if (returnNumberToInterpolate.equals("last return")) {
for (a = 0; a < numPointsInFile; a++) {
point = las.getPointRecord(a);
if (!point.isPointWithheld()
&& !(classValuesToExclude[point.getClassification()]) &&
point.getReturnNumber() == point.getNumberOfReturns()) {
x = point.getX();
y = point.getY();
z = point.getZ();
entry = new double[]{y, x};
pointsTree.addPoint(entry, z);
if (x < minX) {
minX = x;
}
if (x > maxX) {
maxX = x;
}
if (y < minY) {
minY = y;
}
if (y > maxY) {
maxY = y;
}
}
progress = (int) (100d * (a + 1) / numPointsInFile);
if ((progress % 2) == 0) {
updateProgress("Reading point data:", progress);
}
}
}
outputHeader = pointFiles[j].replace(".las", suffix + ".dep");
// see if the output files already exist, and if so, delete them.
if ((new File(outputHeader)).exists()) {
(new File(outputHeader)).delete();
(new File(outputHeader.replace(".dep", ".tas"))).delete();
}
// What are north, south, east, and west and how many rows and
// columns should there be?
west = minX - 0.5 * resolution;
north = maxY + 0.5 * resolution;
nrows = (int)(Math.ceil((north - minY) / resolution));
ncols = (int)(Math.ceil((maxX - west) / resolution));
south = north - nrows * resolution;
east = west + ncols * resolution;
// create the whitebox header file.
fw = new FileWriter(outputHeader, false);
bw = new BufferedWriter(fw);
out = new PrintWriter(bw, true);
str1 = "Min:\t" + Double.toString(Integer.MAX_VALUE);
out.println(str1);
str1 = "Max:\t" + Double.toString(Integer.MIN_VALUE);
out.println(str1);
str1 = "North:\t" + Double.toString(north);
out.println(str1);
str1 = "South:\t" + Double.toString(south);
out.println(str1);
str1 = "East:\t" + Double.toString(east);
out.println(str1);
str1 = "West:\t" + Double.toString(west);
out.println(str1);
str1 = "Cols:\t" + Integer.toString(ncols);
out.println(str1);
str1 = "Rows:\t" + Integer.toString(nrows);
out.println(str1);
str1 = "Data Type:\t" + "float";
out.println(str1);
str1 = "Z Units:\t" + "not specified";
out.println(str1);
str1 = "XY Units:\t" + "not specified";
out.println(str1);
str1 = "Projection:\t" + "not specified";
out.println(str1);
str1 = "Data Scale:\tcontinuous";
out.println(str1);
str1 = "Preferred Palette:\t" + "spectrum.pal";
out.println(str1);
str1 = "NoData:\t" + noData;
out.println(str1);
if (java.nio.ByteOrder.nativeOrder() == java.nio.ByteOrder.LITTLE_ENDIAN) {
str1 = "Byte Order:\t" + "LITTLE_ENDIAN";
} else {
str1 = "Byte Order:\t" + "BIG_ENDIAN";
}
out.println(str1);
out.close();
// Create the whitebox raster object.
WhiteboxRaster image = new WhiteboxRaster(outputHeader, "rw");
int numPointsToUse = 10;
int numPointsInArea = 0;
boolean flag = false;
int maxIteration = 20;
int k = 0;
double halfResolution = resolution / 2;
double area = Math.PI * maxDist; // maxDist is already the squared radius
for (row = 0; row < nrows; row++) {
for (col = 0; col < ncols; col++) {
easting = (col * resolution) + (west + halfResolution);
northing = (north - halfResolution) - (row * resolution);
entry = new double[]{northing, easting};
// keep increasing the numPointsToUse, until you have a point
// that is at a greater distance than maxDist.
numPointsToUse = 10;
flag = false;
k = 0;
do {
k++;
results = pointsTree.nearestNeighbor(entry, numPointsToUse, true);
for (i = 0; i < results.size(); i++) {
if (results.get(i).distance > maxDist) {
flag = true;
}
}
if (!flag) {
numPointsToUse = numPointsToUse * 2;
}
} while (!flag && k < maxIteration);
// how many points are within the radius?
numPointsInArea = 0;
for (i = 0; i < results.size(); i++) {
if (results.get(i).distance <= maxDist) {
numPointsInArea++;
}
}
image.setValue(row, col, numPointsInArea / area);
}
if (cancelOp) {
cancelOperation();
return;
}
progress = (int) (100f * row / (nrows - 1));
updateProgress("Calculating point density:", progress);
}
image.addMetadataEntry("Created by the "
+ getDescriptiveName() + " tool.");
image.addMetadataEntry("Created on " + new Date());
image.close();
}
returnData(pointFiles[0].replace(".las", suffix + ".dep"));
} catch (OutOfMemoryError oe) {
myHost.showFeedback("An out-of-memory error has occurred during operation.");
} catch (Exception e) {
myHost.showFeedback("An error has occurred during operation. See log file for details.");
myHost.logException("Error in " + getDescriptiveName(), e);
} finally {
updateProgress("Progress: ", 0);
// tells the main application that this process is completed.
amIActive = false;
myHost.pluginComplete();
}
}
// // this is only used for debugging the tool
// public static void main(String[] args) {
// LiDAR_PointDensity nn = new LiDAR_PointDensity();
// args = new String[17];
// args[0] = "/Users/johnlindsay/Documents/Data/u_5565073175.las";
// //args[0] = "/Users/johnlindsay/Documents/Data/u_5565073250.las";
// args[1] = " last return intensity";
// args[2] = "intensity";
// args[3] = "last return";
// args[4] = "4";
// args[5] = "1";
// nn.setArgs(args);
// nn.run();
//
// }
}