Package: LSRS 0.2.0

LSRS: Land Surface Remote Sensing

Rapid satellite data streams in operational applications have clear benefits for monitoring land cover, especially when information can be delivered as fast as changing surface conditions. Over the past decade, remote sensing has become a key tool for monitoring and predicting environmental variables by using satellite data. This package presents the main applications in remote sensing for land surface monitoring and land cover mapping (soil, vegetation, water...). Tomlinson, C.J., Chapman, L., Thornes, E., Baker, C (2011) <doi:10.1002/met.287>.

Authors:Mehdi Sarparast

LSRS_0.2.0.tar.gz
LSRS_0.2.0.zip(r-4.5)LSRS_0.2.0.zip(r-4.4)LSRS_0.2.0.zip(r-4.3)
LSRS_0.2.0.tgz(r-4.4-any)LSRS_0.2.0.tgz(r-4.3-any)
LSRS_0.2.0.tar.gz(r-4.5-noble)LSRS_0.2.0.tar.gz(r-4.4-noble)
LSRS_0.2.0.tgz(r-4.4-emscripten)LSRS_0.2.0.tgz(r-4.3-emscripten)
LSRS.pdf |LSRS.html
LSRS/json (API)

# Install 'LSRS' in R:
install.packages('LSRS', repos = c('https://mehdisarparast.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

10 exports 0.00 score 0 dependencies 10 scripts 132 downloads

Last updated 7 years agofrom:26a6261016. Checks:OK: 7. Indexed: yes.

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Doc / VignettesOKAug 25 2024
R-4.5-winOKAug 25 2024
R-4.5-linuxOKAug 25 2024
R-4.4-winOKAug 25 2024
R-4.4-macOKAug 25 2024
R-4.3-winOKAug 25 2024
R-4.3-macOKAug 25 2024

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