whitebox-tools

An advanced geospatial data analysis platform

https://github.com/jblindsay/whitebox-tools

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
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DOI references
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Academic publication links
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Committers with academic emails
1 of 20 committers (5.0%) from academic institutions
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (13.7%) to scientific vocabulary

Keywords

geomorphology geomorphometry geoprocessing geospatial gis hydrology remote-sensing

Last synced: 6 months ago · JSON representation

Repository

An advanced geospatial data analysis platform

Basic Info

Host: GitHub
Owner: jblindsay
License: mit
Language: Rust
Default Branch: master
Homepage: https://www.whiteboxgeo.com/
Size: 163 MB

Statistics

Stars: 1,052
Watchers: 37
Forks: 176
Open Issues: 161
Releases: 21

Topics

geomorphology geomorphometry geoprocessing geospatial gis hydrology remote-sensing

Created almost 8 years ago · Last pushed about 1 year ago

Metadata Files

Readme License

README.md

Note: Compiled WhiteboxTools binaries for Windows, macOS, and Linux can be found at: https://www.whiteboxgeo.com/download-whiteboxtools/

This page is related to the stand-alone command-line program and Python scripting API for geospatial analysis, *WhiteboxTools**.

The official WhiteboxTools User Manual can be found at this link.

Contents

Description
Getting Help
Downloads and Installation
Building From Source Code

1 Description

WhiteboxTools is an advanced geospatial data analysis platform developed by Prof. John Lindsay (webpage; jblindsay) at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, classification, and common image transformations. WhiteboxTools also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. LiDAR point clouds can be interrogated (LidarInfo, LidarHistogram), segmented, tiled and joined, analyized for outliers, interpolated to rasters (DEMs, intensity images), and ground-points can be classified or filtered. WhiteboxTools is not a cartographic or spatial data visualization package; instead it is meant to serve as an analytical backend for other data visualization software, mainly GIS.

2 Getting help

WhiteboxToos possesses extensive help documentation. Users are referred to the User Manual located on www.whiteboxgeo.com.

3 Pre-compiled binaries

WhiteboxTools is a stand-alone executable command-line program with no actual installation. If you intend to use the Python programming interface for WhiteboxTools you will need to have Python 3 (or higher) installed. Pre-compiled binaries can be downloaded from the Whitebox Geospatial Inc. website with support for various operating systems.

4 Building from source code

It is likely that WhiteboxTools will work on a wider variety of operating systems and architectures than the distributed binary files. If you do not find your operating system/architecture in the list of available WhiteboxTool binaries, then compilation from source code will be necessary. WhiteboxTools can be compiled from the source code with the following steps:

Install the Rust compiler; Rustup is recommended for this purpose. Further instruction can be found at this link.
Download the WhiteboxTools from this GitHub repo. ```
Decompress the zipped download file.
Open a terminal (command prompt) window and change the working directory to the whitebox-tools folder:

```

cd /path/to/folder/whitebox-tools/ ```

Finally, use the Python build.py script to compile the code:

```

python build.py ```

Read the notes in the build.py file for detailed information about customizing the build. In particular, the do_clean, exclude_runner and zip arguments can be used to add or remove functionality during the build process. Running the build script requires a Python environment. (Note, WhiteboxTools itself is pure Rust code.)

Depending on your system, the compilation may take several minutes. Also depending on your system, it may be necessary to use the python3 command instead. When completed, the script will have created a new WBT folder within whitebox-tools. This folder will contain all of the files needed to run the program, including the main Whitebox executable file (whitebox_tools.exe), the Whitebox Runner GUI application, and the various plugins.

Be sure to follow the instructions for installing Rust carefully. In particular, if you are installing on MS Windows, you must have a linker installed prior to installing the Rust compiler (rustc). The Rust webpage recommends either the MS Visual C++ 2015 Build Tools or the GNU equivalent and offers details for each installation approach. You should also consider using RustUp to install the Rust compiler.

Owner

Name: John Lindsay
Login: jblindsay
Kind: user
Location: Canada
Company: University of Guelph

Website: https://jblindsay.github.io/ghrg/index.html
Twitter: whiteboxgeo
Repositories: 16
Profile: https://github.com/jblindsay

Geomorphometrist. Whitebox Developer. Works at University of Guelph. Co-founder of Whitebox Geospatial Inc.

GitHub Events

Total

Issues event: 25
Watch event: 95
Issue comment event: 23
Push event: 1
Pull request review event: 2
Pull request event: 4
Fork event: 15

Last Year

Issues event: 25
Watch event: 95
Issue comment event: 23
Push event: 1
Pull request review event: 2
Pull request event: 4
Fork event: 15

Committers

Last synced: 6 months ago

All Time

Total Commits: 788
Total Committers: 20
Avg Commits per committer: 39.4
Development Distribution Score (DDS): 0.071

Past Year

Commits: 1
Committers: 1
Avg Commits per committer: 1.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
John Lindsay	j**y@u**a	732
Timofey Samsonov	t**v@g**u	14
Dharhas Pothina	d**s@g**m	10
jfbourdon	j**n@g**m	7
Jean-François Bourdon	3**n@u**m	4
Qiusheng Wu	g**s@g**m	4
Alexander Bruy	a**y@g**m	2
Duncan Hornby	d**h@g**k	2
luz paz	l**z@u**m	2
Afrancioni	a**o@u**a	1
Andrew Gene Brown	b**g@g**m	1
Dan K	d**k@g**m	1
Doug	d**1@g**m	1
Fabrizio Guglielmino	g**o@g**m	1
Katrin Leinweber	9**r@u**m	1
Kim Lindgren	k**n@s**e	1
Marco Bettini	m**i@s**t	1
Souleymane Maman Nouri Souley	s**y@u**v	1
Yvan Le Bras	y**s@i**r	1
iwismer	i**c@i**a	1

Committer Domains (Top 20 + Academic)

uoguelph.ca: 2 iwismer.ca: 1 irisa.fr: 1 uta.cv: 1 synthesis3.it: 1 slu.se: 1 geodata.soton.ac.uk: 1 geogr.msu.ru: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 344
Total pull requests: 86
Average time to close issues: 3 months
Average time to close pull requests: 3 months
Total issue authors: 207
Total pull request authors: 23
Average comments per issue: 3.01
Average comments per pull request: 1.23
Merged pull requests: 29
Bot issues: 0
Bot pull requests: 17

Past Year

Issues: 27
Pull requests: 5
Average time to close issues: 5 days
Average time to close pull requests: 16 minutes
Issue authors: 24
Pull request authors: 2
Average comments per issue: 0.48
Average comments per pull request: 0.8
Merged pull requests: 2
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

jfbourdon (26)
cefect (12)
CarlosGrohmann (11)
InsolublePancake (10)
mlavy (9)
Hornbydd (8)
giswqs (6)
alexbruy (5)
fluviotect (5)
brownag (5)
zdila (5)
geotom (5)
jfprieur (4)
williamlidberg (4)
csmemoe-aquaveo (3)

Pull Request Authors

jfbourdon (34)
dependabot[bot] (17)
giswqs (5)
halieute (4)
tsamsonov (4)
mholling (3)
seahawks8 (3)
Hornbydd (2)
brownag (2)
dharhas (1)
iwismer (1)
Atreyagaurav (1)
dankovacek (1)
Afrancioni (1)
glebpinigin (1)

Top Labels

Issue Labels

bug (52) feature request (37) feedback (7) QGIS plugin (5) documentation (4) windows (3) Rust (2) question (2) high priority (2) Linux (2) unix (1) R repo (1) wontfix (1)

Pull Request Labels

dependencies (17)

Packages

Total packages: 2
Total downloads: unknown

Total dependent packages: 1
(may contain duplicates)
Total dependent repositories: 1
(may contain duplicates)
Total versions: 20

proxy.golang.org: github.com/jblindsay/whitebox-tools

Documentation: https://pkg.go.dev/github.com/jblindsay/whitebox-tools#section-documentation
License: mit
Latest release: v2.4.0+incompatible
published almost 2 years ago

Versions: 16
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.4%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 6 months ago

conda-forge.org: whitebox_tools

WhiteboxTools is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. WhiteboxTools also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. LiDAR point clouds can be interrogated (LidarInfo, LidarHistogram), segmented, tiled and joined, analyized for outliers, interpolated to rasters (DEMs, intensity images), and ground-points can be classified or filtered. WhiteboxTools is not a cartographic or spatial data visualization package; instead it is meant to serve as an analytical backend for other data visualization software, mainly GIS.

Homepage: https://github.com/jblindsay/whitebox-tools
License: MIT
Latest release: 2.2.0
published over 3 years ago

Versions: 4
Dependent Packages: 1
Dependent Repositories: 1

Rankings

Stargazers count: 14.8%

Forks count: 15.7%

Average: 20.9%

Dependent repos count: 24.1%

Dependent packages count: 29.0%

Last synced: 6 months ago

Dependencies

Cargo.lock cargo

113 dependencies

whitebox-common/Cargo.lock cargo

alga 0.9.3
approx 0.3.2
autocfg 0.1.7
autocfg 1.0.1
bitflags 1.2.1
byteorder 1.4.2
cfg-if 1.0.0
cloudabi 0.0.3
fuchsia-cprng 0.1.1
generic-array 0.12.3
getrandom 0.1.16
libc 0.2.86
libm 0.2.1
matrixmultiply 0.2.4
nalgebra 0.18.1
num-complex 0.2.4
num-integer 0.1.44
num-rational 0.2.4
num-traits 0.2.14
pdqselect 0.1.0
ppv-lite86 0.2.10
rand 0.6.5
rand 0.7.3
rand_chacha 0.1.1
rand_chacha 0.2.2
rand_core 0.3.1
rand_core 0.4.2
rand_core 0.5.1
rand_hc 0.1.0
rand_hc 0.2.0
rand_isaac 0.1.1
rand_jitter 0.1.4
rand_os 0.1.3
rand_pcg 0.1.2
rand_pcg 0.2.1
rand_xorshift 0.1.1
rawpointer 0.2.1
rdrand 0.4.0
rstar 0.7.1
typenum 1.12.0
wasi 0.9.0+wasi-snapshot-preview1
winapi 0.3.9
winapi-i686-pc-windows-gnu 0.4.0
winapi-x86_64-pc-windows-gnu 0.4.0

whitebox-lidar/Cargo.lock cargo

adler 0.2.3
adler32 1.2.0
alga 0.9.3
alloc-no-stdlib 2.0.1
alloc-stdlib 0.2.1
approx 0.3.2
autocfg 0.1.7
autocfg 1.0.1
bitflags 1.2.1
brotli 3.3.0
brotli-decompressor 2.3.1
byteorder 1.4.2
bzip2 0.3.3
bzip2-sys 0.1.10+1.0.8
cc 1.0.66
cfg-if 1.0.0
chrono 0.4.19
cloudabi 0.0.3
crc32fast 1.2.1
flate2 1.0.20
fuchsia-cprng 0.1.1
generic-array 0.12.3
getrandom 0.1.16
hermit-abi 0.1.18
late-static 0.3.0
libc 0.2.86
libm 0.2.1
lzw 0.10.0
matrixmultiply 0.2.4
miniz_oxide 0.3.7
miniz_oxide 0.4.3
msdos_time 0.1.6
nalgebra 0.18.1
num-complex 0.2.4
num-integer 0.1.44
num-rational 0.2.4
num-traits 0.2.14
num_cpus 1.13.0
pdqselect 0.1.0
pkg-config 0.3.19
podio 0.1.7
ppv-lite86 0.2.10
rand 0.6.5
rand 0.7.3
rand_chacha 0.1.1
rand_chacha 0.2.2
rand_core 0.3.1
rand_core 0.4.2
rand_core 0.5.1
rand_hc 0.1.0
rand_hc 0.2.0
rand_isaac 0.1.1
rand_jitter 0.1.4
rand_os 0.1.3
rand_pcg 0.1.2
rand_pcg 0.2.1
rand_xorshift 0.1.1
rawpointer 0.2.1
rdrand 0.4.0
rstar 0.7.1
time 0.1.44
typenum 1.12.0
wasi 0.9.0+wasi-snapshot-preview1
wasi 0.10.0+wasi-snapshot-preview1
winapi 0.3.9
winapi-i686-pc-windows-gnu 0.4.0
winapi-x86_64-pc-windows-gnu 0.4.0
zip 0.3.3

whitebox-raster/Cargo.lock cargo

adler32 1.2.0
alga 0.9.3
approx 0.3.2
autocfg 0.1.7
autocfg 1.0.1
bitflags 1.2.1
byteorder 1.4.2
cfg-if 1.0.0
chrono 0.4.19
cloudabi 0.0.3
fuchsia-cprng 0.1.1
generic-array 0.12.3
getrandom 0.1.16
hermit-abi 0.1.18
late-static 0.3.0
libc 0.2.86
libm 0.2.1
lzw 0.10.0
matrixmultiply 0.2.4
miniz_oxide 0.3.7
nalgebra 0.18.1
num-complex 0.2.4
num-integer 0.1.44
num-rational 0.2.4
num-traits 0.2.14
num_cpus 1.13.0
pdqselect 0.1.0
ppv-lite86 0.2.10
rand 0.6.5
rand 0.7.3
rand_chacha 0.1.1
rand_chacha 0.2.2
rand_core 0.3.1
rand_core 0.4.2
rand_core 0.5.1
rand_hc 0.1.0
rand_hc 0.2.0
rand_isaac 0.1.1
rand_jitter 0.1.4
rand_os 0.1.3
rand_pcg 0.1.2
rand_pcg 0.2.1
rand_xorshift 0.1.1
rawpointer 0.2.1
rdrand 0.4.0
rstar 0.7.1
time 0.1.44
typenum 1.12.0
wasi 0.9.0+wasi-snapshot-preview1
wasi 0.10.0+wasi-snapshot-preview1
winapi 0.3.9
winapi-i686-pc-windows-gnu 0.4.0
winapi-x86_64-pc-windows-gnu 0.4.0

whitebox-runner/Cargo.lock cargo

256 dependencies

whitebox-vector/Cargo.lock cargo

alga 0.9.3
approx 0.3.2
autocfg 0.1.7
autocfg 1.0.1
bitflags 1.2.1
byteorder 1.4.2
cfg-if 1.0.0
chrono 0.4.19
cloudabi 0.0.3
fuchsia-cprng 0.1.1
generic-array 0.12.3
getrandom 0.1.16
libc 0.2.86
libm 0.2.1
matrixmultiply 0.2.4
nalgebra 0.18.1
num-complex 0.2.4
num-integer 0.1.44
num-rational 0.2.4
num-traits 0.2.14
pdqselect 0.1.0
ppv-lite86 0.2.10
rand 0.6.5
rand 0.7.3
rand_chacha 0.1.1
rand_chacha 0.2.2
rand_core 0.3.1
rand_core 0.4.2
rand_core 0.5.1
rand_hc 0.1.0
rand_hc 0.2.0
rand_isaac 0.1.1
rand_jitter 0.1.4
rand_os 0.1.3
rand_pcg 0.1.2
rand_pcg 0.2.1
rand_xorshift 0.1.1
rawpointer 0.2.1
rdrand 0.4.0
rstar 0.7.1
time 0.1.44
typenum 1.12.0
wasi 0.9.0+wasi-snapshot-preview1
wasi 0.10.0+wasi-snapshot-preview1
winapi 0.3.9
winapi-i686-pc-windows-gnu 0.4.0
winapi-x86_64-pc-windows-gnu 0.4.0

Cargo.toml cargo

whitebox-common/Cargo.toml cargo

whitebox-lidar/Cargo.toml cargo

whitebox-plugins/Cargo.toml cargo

whitebox-raster/Cargo.toml cargo

whitebox-runner/Cargo.toml cargo

whitebox-tools-app/Cargo.toml cargo

whitebox-vector/Cargo.toml cargo