nert: Curated Access to TERN Environmental Raster Data

[max578]

Submitting Author Name: Max Moldovan
Submitting Author Github Handle: @max578
Other Package Authors Github handles: (comma separated, delete if none) @adamhsparks, @RussellAndrewEdson, @wvjgsuhp, @rogerssam
Repository: https://github.com/AAGI-AUS/nert
Version submitted: 1.1.0
Submission type: Standard
Editor: @obrl-soil
Reviewers: TBD

Archive: TBD
Version accepted: TBD
Language: en

---

• Paste the full DESCRIPTION file inside a code block below:

Package: nert
Title: Curated Access to TERN Environmental Raster Data
Version: 1.1.0
Authors@R: c(
    person("Adam H.", "Sparks", , "adamhsparks@gmail.com", role = "aut",
           comment = c(ORCID = "0000-0002-0061-8359")),
    person("Max", "Moldovan", , "max.moldovan@adelaide.edu.au", role = c("cre", "aut"),
           comment = c(ORCID = "0000-0001-9680-8474")),
    person("Russell A.", "Edson", , "russell.edson@adelaide.edu.au", role = "aut",
           comment = c(ORCID = "0000-0002-4607-5396")),
    person("Wasin", "Pipattungsakul", , "wasin.pipattungsakul@adelaide.edu.au", role = "aut"),
    person("Sam", "Rogers", , "sam.rogers@adelaide.edu.au", role = "aut",
           comment = c(ORCID = "0000-0002-8147-1239")),
    person("Grains Research and Development Corporation", role = c("fnd", "cph"),
           comment = c("GRDC Project CUR2210-005OPX (AAGI-CU), UOA2301-005OPX (AAGI-AU)", ROR = "02xwr1996"))
  )
Description: Provides curated access to gridded environmental data
    published by Australia's Terrestrial Ecosystem Research Network
    (TERN; <https://www.tern.org.au/>), spanning national soil
    attribute, soil classification, soil biodiversity, soil moisture,
    actual evapotranspiration, vegetation canopy height and phenology
    products. The package reads Cloud-Optimised GeoTIFF and virtual
    raster files directly from the TERN data server via GDAL
    '/vsicurl' range requests, streaming only the requested spatial and
    temporal subset for efficient data transfer. The environmental
    raster data are returned as terra::SpatRaster objects. A convenient
    helper function is also provided that provides a batch-download
    capability given specific locations and dates, returning the
    extracted data values in an analysis-ready data.table. Access to
    the TERN datasets using this package requires a TERN API key.
License: MIT + file LICENSE
URL: https://aagi-aus.github.io/nert/, https://github.com/AAGI-AUS/nert
BugReports: https://github.com/AAGI-AUS/nert/issues
Depends:
    R (>= 3.5.0)
Imports:
    cli,
    data.table,
    ggplot2 (>= 3.5.0),
    lubridate,
    rlang,
    terra,
    tidyterra,
    utils
Suggests:
    keyring,
    knitr,
    nlme,
    rmarkdown,
    testthat (>= 3.2.0),
    xml2,
    usethis,
    withr
VignetteBuilder:
    knitr
Config/Needs/build: moodymudskipper/devtag
Config/roxygen2/version: 8.0.0
Config/testthat/edition: 3
Config/testthat/parallel: true
Encoding: UTF-8
Language: en-AU
Roxygen: list(markdown = TRUE, roclets = c("collate", "namespace", "rd",
    "devtag::dev_roclet"))
X-schema.org-applicationCategory: Tools
X-schema.org-isPartOf:
    https://grdc.com.au/research/partnerships-and-initiatives/strategic-partnerships/aagi
X-schema.org-keywords: TERN, soil-data, Australia, earth-science,
    data-access

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
  • translation
  • rOpenSci internal tools

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):

nert retrieves gridded environmental raster data directly from Australia's TERN national data server (data retrieval), streaming Cloud-Optimised GeoTIFF and virtual-raster subsets via GDAL /vsicurl range requests. It returns geospatial terra::SpatRaster objects and, via a batch helper, analysis-ready extracted values at user locations and dates (geospatial data).

• Who is the target audience and what are scientific applications of this package?

The target audience is Australian agricultural, soil, and environmental researchers and data analysts, who need programmatic, analysis-ready access to TERN's national gridded raster products without handling TERN's raw storage layout or GDAL /vsicurl mechanics. Scientific applications include soil-attribute and soil-classification mapping, soil-moisture and actual-evapotranspiration time-series extraction, vegetation canopy-height and phenology analysis, and assembling covariates for agronomic and environmental modelling.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

Yes, there is partial overlap, confined to the SLGA (Soil and Landscape Grid of Australia) portion of nert's coverage:

• SLGACloud (GitHub; AusSoilsDSM/SLGACloud) provides helper functions to access TERN Landscapes Cloud-Optimised GeoTIFFs for SLGA, using a TERN Data API key and terra - the same data host, authentication, and technology nert uses for its SLGA datasets.
• slga (CRAN; obrl-soil/slga) downloads geographic subsets of SLGA soil-attribute and terrain/climate rasters via OGC Web Coverage Service (WCS) endpoints.
• ausplotsR (CRAN; ternaustralia/ausplotsR) accesses a different TERN product - point-based AusPlots field-survey vegetation and soil data - not gridded rasters.

General-purpose geospatial tools (terra, rstac, gdalcubes, geodata) require the user to already know each dataset's URLs, structure, projection, and temporal coverage.

nert differs, and aims to be best-in-category by breadth and consistency rather than by being the only SLGA option. It provides a single curated, validated read_*() / collect_tern_data() API across seven TERN gridded product families - SLGA soil attributes, soil classification (ASC), soil biodiversity, soil moisture (SMIPS), actual evapotranspiration, vegetation canopy height, and phenology - whereas the existing tools are each single-product (SLGA-only or AusPlots-only). It abstracts TERN's raw storage layout, streams only the requested spatial-temporal subset via GDAL /vsicurl, and adds a batch point-extraction helper returning analysis-ready data.tables. For the SLGA subset specifically, nert is complementary to SLGACloud and slga. Its distinct contribution is unified, consistent, validated access across the wider TERN raster archive.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Not applicable. nert accesses openly published, non-personal environmental raster data. It involves no human subjects, personal, or otherwise sensitive data.

• 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.

No pre-submission inquiry was made, scope fit (data retrieval / geospatial data) is considered clear.

• Explain reasons for any pkgcheck items which your package is unable to pass.

pkgcheck (v0.1.3.6) was run against the submission commit and reports "Your package is in great shape!". All structural checks pass: package name available, contributing file, roxygen2, DESCRIPTION URL and BugReports fields, at least one HTML vignette, examples for all functions, package website, continuous integration, 100% test coverage, and R CMD check with no errors and no warnings. There are no failing pkgcheck items.

Three informational (non-failing) notes are reported:

• Examples are guarded (nine functions use if (interactive()), one uses \dontrun()) because every data call requires a live TERN API key and therefore cannot execute in a noninteractive check and this safeguards against errors on CRAN.
• "Function names are duplicated in other packages": some exported names coincide with functions in unrelated CRAN packages. This is informational and does not create a namespace conflict.
• "Some goodpractice linters failed": minor style notes from goodpractice's linter set.

(Note for anyone rerunning pkgcheck locally: its continuous-integration check queries the GitHub API and reports a false negative when run without a GitHub token. With API access, as in the ropensci-review-bot environment, it passes. nert has GitHub Actions CI across Ubuntu devel/release/oldrel, macOS and Windows, plus lintr, test-coverage and pkgdown, all currently passing.)

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.

Use of Generative AI

• Generative AI tools were used to produce some of the material in this submission.

Generative AI coding tools were used as a part of the package's development. A reference implementation for one dataset (SMIPS) was written by hand, and that pattern was then generalised with AI assistance to the other TERN datasets the package covers. The AI-assisted code was afterwards reviewed and revised line-by-line by the package maintainers, and its external facts (dataset identifiers, file-path templates, temporal ranges, units) were checked against TERN's live data services and metadata before release.

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.

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---

Matches are generated by the 'pkgmatch' package, based on inverse-term frequencies; see the main function documentation for details.

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Checks for nert (v1.1.0)

git hash: 2827c7dc

• ✔️ Package name is available
• ✔️ has a 'contributing' file.
• ✔️ uses 'roxygen2'.
• ✔️ 'DESCRIPTION' has a URL field.
• ✔️ 'DESCRIPTION' has a BugReports field.
• ✔️ Package has at least one HTML vignette
• ✔️ All functions have examples.
• ✔️ Repository has a website
• ✔️ Package has continuous integration checks.
• ✔️ Package coverage is 100%.
• ✔️ R CMD check found no errors.
• ✔️ R CMD check found no warnings.
• 👀 Some goodpractice linters failed.
• 👀 Function names are duplicated in other packages
• 👀 Examples should not use \dontrun{} unless really necessary.

(Checks marked with 👀 may be optionally addressed.)

Package License: MIT + file LICENSE

---

1. Package Dependencies

Details of Package Dependency Usage (click to open)

The table below tallies all function calls to all packages ('ncalls'), both internal (r-base + recommended, along with the package itself), and external (imported and suggested packages). 'NA' values indicate packages to which no identified calls to R functions could be found. Note that these results are generated by an automated code-tagging system which may not be entirely accurate.

type	package	ncalls
internal	base	273
internal	stats	11
internal	graphics	5
imports	data.table	4
imports	lubridate	2
imports	rlang	2
imports	terra	2
imports	cli	1
imports	tidyterra	NA
imports	utils	NA
suggests	keyring	NA
suggests	knitr	NA
suggests	nlme	NA
suggests	rmarkdown	NA
suggests	testthat	NA
suggests	xml2	NA
suggests	usethis	NA
suggests	withr	NA
linking_to	NA	NA

Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table.

base

list (73), date (27), c (24), args (19), sprintf (16), dir (14), version (14), if (10), is.null (9), length (8), for (7), vapply (6), paste (5), names (4), as.integer (3), toupper (3), as.Date (2), drop (2), format (2), is.na (2), paste0 (2), tryCatch (2), all (1), by (1), col (1), gsub (1), ifelse (1), match (1), nrow (1), options (1), regexec (1), regmatches (1), rep (1), seq (1), seq_along (1), setdiff (1), suppressWarnings (1), Sys.Date (1), Sys.getenv (1), unlist (1), with (1)

stats

alias (6), end (2), start (2), setNames (1)

graphics

axis (5)

data.table

data.table (3), fcase (1)

lubridate

tz (1), year (1)

rlang

arg_match (2)

terra

rast (1), vect (1)

cli

cli_abort (1)

NOTE: Some imported packages appear to have no associated function calls; please ensure with author that these 'Imports' are listed appropriately.

---

2. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

• code in R (100% in 16 files) and
• 5 authors
• 3 vignettes
• 1 internal data file
• 8 imported packages
• 48 exported functions (median 8 lines of code)
• 2 non-exported functions in R (median 2 lines of code)

---

Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:

• loc = "Lines of Code"
• fn = "function"
• exp/not_exp = exported / not exported

All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown() function

The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.

measure	value	percentile	noteworthy
files_R	16	83.5
files_vignettes	4	96.1
files_tests	25	98.4
loc_R	1483	87.2
loc_vignettes	468	77.3
loc_tests	2594	96.2	TRUE
num_vignettes	3	94.9
data_size_total	14006	53.7
data_size_median	14006	69.1
n_fns_r	50	86.9
n_fns_r_exported	48	91.5
n_fns_r_not_exported	2	61.7
n_fns_per_file_r	4	78.7
num_params_per_fn	3	62.8
loc_per_fn_r	8	56.4
loc_per_fn_r_exp	8	54.5
loc_per_fn_r_not_exp	2	50.5
doclines_per_fn_exp	7	43.6
doclines_per_fn_not_exp	24	98.2	TRUE
fn_call_network_size	52	81.7

---

2a. Network visualisation

Click to see the interactive network visualisation of calls between objects in package

---

3. goodpractice and other checks

Details of goodpractice checks (click to open)

3a. Continuous Integration Badges

GitHub Workflow Results

id	name	conclusion	sha	run_number	date
28634440690	lint.yaml	success	2827c7	94	2026-07-03
28634440722	pkgdown.yaml	success	2827c7	218	2026-07-03
28634440703	R-CMD-check.yaml	success	2827c7	262	2026-07-03
28634440718	test-coverage.yaml	success	2827c7	190	2026-07-03

---

3b. goodpractice results

Test coverage with covr

Package coverage: 100

Cyclocomplexity with cyclocomp

The following function have cyclocomplexity >= 15:

function	cyclocomplexity
collect_tern_data	21

Static code analyses with lintr

lintr found the following 127 potential issues:

message	number of times
Avoid duplicate arguments in function calls.	1
Avoid implicit assignments in function calls.	9
Avoid undesirable operator <<-.	4
Combine inputs to vectorized functions first to take full advantage of vectorization, e.g., as.Date(c(x, y)) only runs the more expensive as.Date() once as compared to c(as.Date(x), as.Date(y)).	1
Construct file paths with file.path(...) instead of paste0(x, "/", y, "/", z).	2
expect_false(x) is better than expect_true(!x), and vice versa.	1
expect_length(x, n) is better than expect_identical(length(x), n)	12
Lines should not be more than 80 characters.	86
Supply an explicit value for stringsAsFactors for this code to work before and after R version 4.0.	1
toString(.) is more expressive than paste(., collapse = ", ").	7
Use expect_identical(x, y) by default; resort to expect_equal() only when needed, e.g.	3

Other goodpractice checks

✖️ All internal functions are used
✖️ Package names in Title/Description are single-quoted

---

4. Other Checks

Details of other checks (click to open)

✖️ The following 2 function names are duplicated in other packages:

• • get_key from weatherOz
• • read_asc from eyelinker

---

Package Versions

package	version
pkgstats	0.2.3.2
pkgcheck	0.1.3.6

---

Editor-in-Chief Instructions:

This package is in top shape and may be passed on to a handling editor.

This package has some noteworthy properties, see 'Package Statistics' details above.

[maurolepore]

Thanks @max578 for sharing your work with rOpenSci and for your efforts in submitting it in great shape.
I'll discuss fit in scope with the editorial board. Will be back soon.

[maurolepore]

After discussing with the editorial board we believe this submission is in scope. I'll start the search for a handling editor.

[maurolepore]

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