Package: waveformlidar
Type: Package
Title: Waveform LiDAR Data Processing and Analysis
Version: 1.2.0
Date: 2020-07-25
Authors@R: person("Tan", "Zhou", email = "tankchow12@gmail.com",
                  role = c("aut", "cre"))
Depends: R (>= 4.0.0)
Maintainer: Tan Zhou <tankchow12@gmail.com>
Imports: data.table, caTools, minpack.lm, flux, raster, rgdal, sp,
        rgeos, sqldf, splitstackshape, reshape2
Suggests: knitr, rPeaks
Additional_repositories: https://tankwin08.github.io/drat
Description: A wealth of Full Waveform (FW) Light Detection and Ranging (LiDAR) data are available to 
	the public from different sources, which is poised to boost the extensive 
	application of FW LiDAR data. However, we lack a handy and open source tool 
	that can be used by ecological and remote sensing communities for processing and analyzing FW LiDAR 
	data. To this end, we introduce 'waveformlidar', an R package dedicated to 
	FW LiDAR processing, analysis and visualization as a solution to the constraint.
	Specifically, this package provides several commonly used waveform processing methods
	such as Gaussian, adaptive Gaussian and Weibull decompositions, and 
	deconvolution approaches (Gold and Richard-Lucy (RL)) with customized settings. 
	In addition, we also develop some functions to derive commonly used waveform metrics
	for characterizing vegetation structure. Moreover, a new way to directly visualize 
	FW LiDAR data is developed through converting waveforms into points to form the Hyper
	Point cloud (HPC), which can be easily adopted and subsequently analyzed with existing 
	discrete-return LiDAR processing tools such as 'LAStools' and 'FUSION'. Basic explorations of 
	the HPC such as 3D voxelization of the HPC and conversion from original waveforms to 
	composite waveforms are also available in this package. All of these functions are 
	developed based on small-footprint FW LiDAR data, but they can be easily transplanted to
	the large footprint FW LiDAR data such as Geoscience Laser Altimeter System (GLAS) 
	and Global Ecosystem Dynamics Investigation (GEDI) data analysis. References: Zhou et al. (2017a) <doi:10.1016/j.isprsjprs.2017.04.021>;
	Zhou et al. (2017b) <doi:10.1016/j.rse.2017.08.012>; Zhou et al. (2018a) <doi:10.3390/rs10010039>;Zhou et al. (2018b) <doi:10.3390/rs10121949>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: https://github.com/tankwin08/waveformlidar,
BugReports: https://github.com/tankwin08/waveformlidar/issues
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-07-25 22:07:03 UTC; tank
Author: Tan Zhou [aut, cre]
Repository: CRAN
Date/Publication: 2020-08-01 09:20:03 UTC
Built: R 4.0.2; ; 2020-08-02 02:03:46 UTC; windows
