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Unmanned Aerial Vehicle R Tools

The uavR tools consist of two packages:

mission planning uavRmp (CRAN)
remote sensing toolbox uavRst (~~CRAN~~)

Unmanned Aerial Vehicle Remote Sensing Toolbox - uavRst

The uavRstanalysis toolbox package is far from being mature. You will need for most of the uavRst functions a bunch of third party software. The most comfortable way to fulfill these requirements is to install QGIS, GRASS- and SAGA-GIS. Following the excellent provided by the RQGIS team will give you a good first try to ensure a smooth working environment.

Most of the LiDAR related operations can be done by the great R package lidR. However for some of the basic point cloud related operations you will need to install the LAStool software. The LAStools toolset is available at the rapidlasso homepage. Please download it and unzip it as usual. For Windows systems it is by default expected that you put it at C:/LASTools, running Linux at ~/apps/LASTools.

Note: For running LAStools tools under Linux you first need to install wine.

In addition you need to install the link2GI package. In case of any problems drop an issue or try to use the actual github hosted version of the package.

Nevertheless all mentioned software packages have to be installed correctly on your the OS. Most of it tested under Windows and Linux and should run... The most easiest way to obtain a fairly good runtime enviroment is to setup Linux as a dual boot system or in a VB.

A full list of necessary libaries and binaries beyond R will hopefully (soon) be provided.

Wiki

You will find some tutorials and examples at the uavRst Wiki. Please feel free to participate.

Installation

The master branch is a github mirror for the CRAN version.

To install the actual development version from github you need to have installed the devtools package.

devtools::install_github("gisma/uavRst", ref = "develop")

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Version

Install

install.packages('uavRst')

Monthly Downloads

6

Version

0.5-4

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/gisma/uavRst/

Homepage

https://gisma.github.io/uavRst/

Maintainer

Chris Reudenbach

Last Published

December 30th, 2019

Functions in uavRst (0.5-4)

counts pixel values according to their classes

Calculates Gray scale morphological operations for a given kernel size.

converts GRASS raster to Geotiff

writes shapefiles from sf or sp* objects

applies a line to a raster and returns the position of the maximum value.

seeded region growing tree crown segmentation based on 'SAGA GIS'

OTB wrapper for Haralick's simple, advanced and higher order texture features.

writes raster* objects to the SAGA format

converts R raster* objects to SAGA raster

reads shapefiles as sf or sp objects

Calls the glcm package with useful settings

converts GRASS vector to shape file

Create a Digital Terrain Model from UAV generated point clouds by minimum altitude sampling (fix resolution of sampling gridsize)

Extracts training data from a raster stack using vector data as a mask.

returns the status of saga modules

Read a GPX file.

example raster data set for demonstration usage

Checks if running on a specified computer domain

converts OGR to GRASS vector

Create a Digital Terrain Model from UAV generated point clouds by minimum altitude sampling (multiple resolutions of sampling gridsize)

RGB Orthoimagefrom an arbitray MOF plot

Read, convert and write xyz DEM/DSM Data as typically provided by the Authorities to GeoTiff.

colorize the cat outputs

Calculates local statistics for a given kernel size

convenient function to establish all link2GI links

Calculates edges for a given kernel size.

converts SAGA raster to R raster object

Create a Digital Terrain Model from UAV generated point clouds by minimum altitude sampling

Calculate descriptive statistics of raster as segmented by polygons

create name vector corresponding to the training image stack create vector containing the names of the image stack claculated using calc_ext

'ForestTools' tree top detection

calculates most important DEM parameters

Find potential tree positions using a canopy height model

extract for all polygons the position of the maximum value of the applied raster(s).

DEM data set of Marburg-Biedenkopf

'rLiDAR' based tree detection of a LiDAR-derived Canopy Height Model (CHM)

calculate morphometric features of polygons.

tree top detection based on local maxima filters as provided by 'lidR'

classify images using raster predict

Split multiband image to single band SAGA files

divide a lidR las* or lascatalog object by given factors

Optional tree position raster map

Unmanned Aerial Vehicle Remote Sensing Tools - some cool tools to manipulate and analyze UAV derived RGB ortho imagery and point clouds.

Canopy height model raster map

Watershed segmentation based on 'rLiDAR'

Easy digitizing of vector features within your rstudio session (or any browser)

basic filtering of crown polygons using altitude, area and other optional thresholds

imagemagick based function to transform the RGB color space into another

Convenient function to preprocess synthetic raster bands from a given RGB image and/or DTM/DSM data.

Watershed segmentation based on 'ForestTools'

Decision tree segmentation method to grow individual tree crowns based on 'itcSegment'

Forward feature selection based on rf model