Implementation of OPTRAM algorithm to derive soil moisture from remote sensing imagery #612
Description
Date accepted: 2024-06-05
Submitting Author Name: Micha Silver
Submitting Author Github Handle: @micha-silver
Other Package Authors Github handles: (comma separated, delete if none) @github_handle1, @github_handle2
Repository: https://gitlab.com/rsl-bidr/roptram
Version submitted: 0.0.1.000
Submission type: Standard
Editor: @adamhsparks
Reviewers: @harryeslick, @obrl-soil
Archive: TBD
Version accepted: TBD
Language: en
- Paste the full DESCRIPTION file inside a code block below:
Package: rOPTRAM
Title: Derive soil moisture using the OPTRAM algorithm
Version: 0.0.1.000
Authors@R: c(
person("Micha", "Silver", , "silverm@post.bgu.ac.il", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-1128-1325")),
person("Arnon", "Karnieli", , "karnieli@bgu.ac.il", role = c("ctb", "fnd"),
comment = c(ORCID = "0000-0001-8065-9793"))
)
Description: The OPtical TRapezoid Model (OPTRAM) derives soil moisture
based on the linear relation between a vegetation index
and Land Surface Temperature (LST). The Short Wave Infra-red (SWIR) band
is used as a proxy for LST. See:
Sadeghi, M., Babaeian, E., Tuller, M., Jones, S.B., 2017.
The optical trapezoid model:
A novel approach to remote sensing of soil moisture
applied to Sentinel-2 and Landsat-8 observations.
Remote Sensing of Environment 198, 52–68,
https://doi.org/10.1016/j.rse.2017.05.041 .
License: GPL (>= 3) + file LICENSE
URL: https://gitlab.com/rsl-bidr/roptram.git
BugReports: https://gitlab.com/rsl-bidr/
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Depends:
R (>= 4.1.0)
Imports:
dplyr,
ggplot2,
sf,
terra,
tools,
utils
Suggests:
geojsonio,
geojsonlint,
stats,
sen2r (> 1.5.0),
testthat (>= 3.0.0),
xml2
Config/testthat/edition: 3
Scope
-
Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):
- data retrieval
- data extraction
- data munging
- data deposition
- data validation and testing
- workflow automation
- version control
- citation management and bibliometrics
- scientific software wrappers
- field and lab reproducibility tools
- database software bindings
- geospatial data
- text analysis
-
Explain how and why the package falls under these categories (briefly, 1-2 sentences):
This package includes acquiring satellite imagery, and preparing spatially explicit soil moisture raster grids. -
Who is the target audience and what are scientific applications of this package?
Researchers in ecology, agriculture, sustainability. Agricultural management of grazing lands, reforestration. -
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?
No -
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?
Yes -
If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.
-
Explain reasons for any
pkgcheckitems which your package is unable to pass.
Technical checks
Confirm each of the following by checking the box.
- I have read the rOpenSci packaging guide.
- I have read the author guide and I expect to maintain this package for at least 2 years or to find a replacement.
This package:
- does not violate the Terms of Service of any service it interacts with.
- has a CRAN and OSI accepted license.
- contains a README with instructions for installing the development version.
- includes documentation with examples for all functions, created with roxygen2.
- contains a vignette with examples of its essential functions and uses.
- has a test suite.
- has continuous integration, including reporting of test coverage.
Publication options
-
Do you intend for this package to go on CRAN?
-
Do you intend for this package to go on Bioconductor?
-
Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:
MEE Options
- The package is novel and will be of interest to the broad readership of the journal.
- The manuscript describing the package is no longer than 3000 words.
- You intend to archive the code for the package in a long-term repository which meets the requirements of the journal (see MEE's Policy on Publishing Code)
- (Scope: Do consider MEE's Aims and Scope for your manuscript. We make no guarantee that your manuscript will be within MEE scope.)
- (Although not required, we strongly recommend having a full manuscript prepared when you submit here.)
- (Please do not submit your package separately to Methods in Ecology and Evolution)
Code of conduct
- I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.