uavRst: Unmanned Aerial Vehicle Remote Sensing Tools

Support the analysis of drone derived imagery and point clouds as a cheap and easy to use alternative/complement to light detection and ranging data. It provides functionality to analyze poor quality digital aerial images as taken by low budget ready to fly drones. This includes supported machine learning based classification functions, comprehensive texture analysis, segmentation algorithms as well as forest relevant analyzes of metrics and measures on the derived products.

Version: 0.5-0
Depends: R (≥ 3.1.0)
Imports: raster, foreach
LinkingTo: Rcpp
Suggests: knitr, stringr, sp, sf, htmlwidgets, htmltools, Rcpp, rgdal, rgeos, gdalUtils, tools, caret, zoo, data.table, parallel,, velox, link2GI, doParallel, CAST, glcm, crayon, ForestTools, itcSegment, pROC, methods, RSAGA, reshape2, rgrass7, randomForest, rLiDAR, rlas, lidR, rmarkdown, mapview
Published: 2018-11-19
Author: Florian Detsch [ctb], Hanna Meyer [aut], Thomas Nauss [ctb], Lars Opgenoorth [ctb], Chris Reudenbach [cre, aut], Environmental Informatics Marburg [ctb]
Maintainer: Chris Reudenbach <reudenbach at>
License: GPL (≥ 3) | file LICENSE
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
CRAN checks: uavRst results


Reference manual: uavRst.pdf
Package source: uavRst_0.5-0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: uavRst_0.5-0.tgz, r-oldrel: uavRst_0.5-0.tgz


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