INPROGRESS-mbes-point-cloud-tools-help

Overview

The point cloud files produced from multi-beam SONAR (MBES) and Light Detection and Ranging (LiDAR) surveys can produce large .txt based files in the magnitude of megabytes to gigabytes. Files of this size can be difficult for popular GIS software to handle and often pose problems for GIS users. The aim of this project is to develop a humble Python based GUI that houses a set of tools aimed at the basic processing of these point clouds.


**All text file outputs (with the exception output from the uncertainty stats tool) are comma delimited. 

Below is a list of tools that help is provided for:

Create Uncertainty Text File

Overview:

When surveying with MBES and other surveying methods which provide fine sampling resolutions the potential to survey the same point twice occurs. Using a precise point matching algorithm this tool finds all exact matches within the point cloud and creates a text file which has many uses in this toolkit and is the basis for developing a Fuzzy Inference System in order to create a spatially variable uncertainty model.

Inputs: 
1.point cloud file
2.  field separator of point cloud file

Output: 
1. text file that has found all of the occurences where a location was surveyed twice. This serves as an estimation of uncertainty. The output can be used in other tools to create a shapefile or to create a histogram of the uncertainty as well as calculate basic statistics of uncertainty.

When clicking this button a series of interfaces will pop-up. First the user must select a point cloud file, after choosing a file and clicking okay they will be prompted with another window to enter in the field separator for their file. The default separator is a space but the user can choose another if it is different for their file type.

Create Uncertainty Shapefile

Overview:

Shapefiles are a widely used data type in GIS operations. However current poplar GIS does not provide tools to automate the process of creating a shapefile directly from a text file. This tool automates the process and in doing so saves the user needless work.

Inputs: 
1.  Text file created from Create Uncertainty Text file tool

Outputs: 
1. Shapefile of the uncertainty estimate, this can be used in other standard GIS software.


Calculate Uncertainty Stats

Overview:

To better understand the uncertainty that exists within a users point cloud this tool provides basic summary statistics in text file to be used as well as a pop-up window for quick analysis.

Inputs: 
1.  Text file created from Create Uncertainty Text file tool

Outputs:
1. Text file of basic summary statistics of uncertainty in points being surveyed twice from point cloud file.

Create Histogram \ Boxplot of Uncertainty


Overview:

To better understand the uncertainty that exists within a users point cloud this tool provides basic a quick and easy way to visually inspect the distribution of uncertainty within the point cloud. Upon creating both the histogram and the boxplot the user has the option to save the figures.

Inputs: 
1.  Text file created from Create Uncertainty Text file tool

Outuputs:
1. A histogram of the distribution of uncertainty values conatained within the uncertainty text file. Through the pop-up window displaying the figure the user has the option to save the figure.
2. A boxplot of the distribution of uncertainty values conatained within the uncertainty text file. Through the pop-up window displaying the figure the user has the option to save the figure.


Determine Sampling Resolution

Overview:

Understanding the sampling resolution within a point cloud can helps to determine the level of details that can be discerned from the data. This is useful in later steps of analysis such as determining a raster resolution for a project. This tool provides a text file containing all possible beam footprints within a point cloud based on the parameters of the reach and surveying equipment. The output text file is formatted for ease of use in other statistical software packages.  Additionally a pop-up window provides an initial idea of the sampling resolution achieved.

Inputs: 
1. Min, max water depth of the river reach
2. Min, max beam angle of surveying equipment 
3. Beam width of surveying equipment
4. Min, max slopes of surface observed in reach
**Only choose one min and one max for 1, 2, and 4

Output:
1. Text file representing all possible sampling resolutions within reach. This can be read into other programs for further statistical analysis
2. Boxplot of range of sampling resolutions observed within reach.
3. Dialogue box summarizing the min, max, and mean sampling resolutions based on user input


Point Cloud Decimation

Overview:

Point decimation is a powerful tool available to those surveying with equipment able to provide fine resolution/high density. By decimating point clouds statistical power is gained to calculate locally detrended standard deviation amoung other statistical derivatives. This tool allows the user to decimate to any number of resolutions ranging from 1 all the way to 100 feet. Additionally the text and shapefiles produced can be used as inputs to an information sensitivity loss analysis to accurately determine the appropriate cell resolution of analysis for a project. 

Inputs:
1. Point Cloud file
2. Any number of levels to decimate the point cloud to that are provided by in multiple choice list

Outputs:
1. Text file calculating a wide variety of statistics based on points within defined decimation interval. Can be read into other GIS software.
2. Text file  representing minimum value within each decimated interval. Can be read into other GIS software.
3. Text file frepresenting maximum value within each decimated interval. Can be read into other GIS software.
4. Text file containing all decimated intervals that did not meet the minimum requirements to calculate statistics for. Can be read into other GIS software.


Interpolation Analysis 

In development.

Create Shapefile from Decimated Derivatives

Overview:

This tool is used to create shapefiles from the derivatives of point cloud decimation. Popular GIS does not have this task automated which creates needless work for GIS analysts. This tool seeks to solve this problem along with iteratively creating fields in the shapfile for all fields within the input text file.

Inputs:
1. Any of the output files from decimating a point cloud file.

Outputs:
1. A shapefile of whatever decimated derivative the user chose. The information in these shapefiles has highly useful statistical calculations that can be used on their own or to create raster derivatives from.

Create Slope Raster

In development.

Create Surface Roughness Raster

In development.


Develope Fuzzy Inference System Groups


In development.
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