Showing 24 of total 24 results (show query)
bluegreen-labs
ecmwfr:Interface to 'ECMWF' and 'CDS' Data Web Services
Programmatic interface to the European Centre for Medium-Range Weather Forecasts dataset web services (ECMWF; <https://www.ecmwf.int/>) and Copernicus's Data Stores. Allows for easy downloads of weather forecasts and climate reanalysis data in R. Data stores covered include the Climate Data Store (CDS; <https://cds.climate.copernicus.eu>), Atmosphere Data Store (ADS; <https://ads.atmosphere.copernicus.eu>) and Early Warning Data Store (CEMS; <https://ewds.climate.copernicus.eu>).
Maintained by Koen Hufkens. Last updated 1 months ago.
cdsclimate-datacopernicusecmwf-apiecmwf-services
12.0 match 111 stars 10.08 score 156 scripts 3 dependents
pepijn-devries
CopernicusMarine:Search Download and Handle Data from Copernicus Marine Service Information
Subset and download data from EU Copernicus Marine Service Information: <https://data.marine.copernicus.eu>. Import data on the oceans physical and biogeochemical state from Copernicus into R without the need of external software.
Maintained by Pepijn de Vries. Last updated 3 months ago.
19.5 match 25 stars 5.88 score 20 scripts 2 dependents
mlampros
CopernicusDEM:Copernicus Digital Elevation Models
Copernicus Digital Elevation Model datasets (DEM) of 90 and 30 meters resolution using the 'awscli' command line tool. The Copernicus (DEM) is included in the Registry of Open Data on 'AWS (Amazon Web Services)' and represents the surface of the Earth including buildings, infrastructure and vegetation.
Maintained by Lampros Mouselimis. Last updated 3 months ago.
awscliawscliv2copernicusdigital-elevation-model
17.8 match 17 stars 5.23 score 1 scripts
kwb-r
kwb.satellite:R Package for Working with Satellite Data from Various Providers (Copernicus, GoogleEarthEngine)
R Package with functions for working with satellite data of Copernicus Climate Data Store (https://cds.climate.copernicus.eu) or GoogleEarthEngine (https://earthengine.google.com/).
Maintained by Michael Rustler. Last updated 3 years ago.
copernicuscopernicus-climate-data-storegoogle-earth-engineproject-keyssatellite-data
29.4 match 1 stars 3.00 score 2 scripts
zivankaraman
CDSE:'Copernicus Data Space Ecosystem' API Wrapper
Provides interface to the 'Copernicus Data Space Ecosystem' API <https://dataspace.copernicus.eu/analyse/apis>, mainly for searching the catalog of available data from Copernicus Sentinel missions and obtaining the images for just the area of interest based on selected spectral bands. The package uses the 'Sentinel Hub' REST API interface <https://dataspace.copernicus.eu/analyse/apis/sentinel-hub> that provides access to various satellite imagery archives. It allows you to access raw satellite data, rendered images, statistical analysis, and other features. This package is in no way officially related to or endorsed by Copernicus.
Maintained by Zivan Karaman. Last updated 1 months ago.
copernicusearth-observationremote-sensing
16.6 match 15 stars 4.91 score 12 scripts
dankelley
oce:Analysis of Oceanographic Data
Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature. This package is discussed extensively by Kelley (2018) "Oceanographic Analysis with R" <doi:10.1007/978-1-4939-8844-0>.
Maintained by Dan Kelley. Last updated 15 hours ago.
3.8 match 146 stars 15.42 score 4.2k scripts 18 dependents
cldossantos
pacu:Precision Agriculture Computational Utilities
Support for a variety of commonly used precision agriculture operations. Includes functions to download and process raw satellite images from Sentinel-2 <https://documentation.dataspace.copernicus.eu/APIs/OData.html>. Includes functions that download vegetation index statistics for a given period of time, without the need to download the raw images <https://documentation.dataspace.copernicus.eu/APIs/SentinelHub/Statistical.html>. There are also functions to download and visualize weather data in a historical context. Lastly, the package also contains functions to process yield monitor data. These functions can build polygons around recorded data points, evaluate the overlap between polygons, clean yield data, and smooth yield maps.
Maintained by dos Santos Caio. Last updated 2 days ago.
5.4 match 14 stars 6.82 score 9 scripts
agrdatasci
ag5Tools:Toolbox for Downloading and Extracting Copernicus AgERA5 Data
Tools for downloading and extracting data from the Copernicus "Agrometeorological indicators from 1979 to present derived from reanalysis" <https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview> (AgERA5).
Maintained by David Brown. Last updated 4 months ago.
agriculture-researchagrometeorologicalclimate-data
6.4 match 8 stars 5.32 score 13 scripts
xavi-rp
LPDynR:Land Productivity Dynamics Indicator
It uses 'phenological' and productivity-related variables derived from time series of vegetation indexes, such as the Normalized Difference Vegetation Index, to assess ecosystem dynamics and change, which eventually might drive to land degradation. The final result of the Land Productivity Dynamics indicator is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing productivity. See www.sciencedirect.com/science/article/pii/S1470160X21010517/ for a description of the methods used in the package to calculate the indicator.
Maintained by Xavier Rotllan-Puig. Last updated 6 months ago.
copernicus-global-land-serviceearth-observationland-degradationland-productivityvegetation
6.3 match 8 stars 4.90 score 5 scripts
mattmar
rasterdiv:Diversity Indices for Numerical Matrices
Provides methods to calculate diversity indices on numerical matrices based on information theory, as described in Rocchini, Marcantonio and Ricotta (2017) <doi:10.1016/j.ecolind.2016.07.039>, and Rocchini et al. (2021) <doi:10.1101/2021.01.23.427872>.
Maintained by Matteo Marcantonio. Last updated 19 days ago.
3.6 match 15 stars 7.65 score 44 scripts 1 dependents
rstudio
rticles:Article Formats for R Markdown
A suite of custom R Markdown formats and templates for authoring journal articles and conference submissions.
Maintained by Christophe Dervieux. Last updated 5 days ago.
2.0 match 1.5k stars 11.93 score 188 scripts 3 dependents
jeffreyevans
spatialEco:Spatial Analysis and Modelling Utilities
Utilities to support spatial data manipulation, query, sampling and modelling in ecological applications. Functions include models for species population density, spatial smoothing, multivariate separability, point process model for creating pseudo- absences and sub-sampling, Quadrant-based sampling and analysis, auto-logistic modeling, sampling models, cluster optimization, statistical exploratory tools and raster-based metrics.
Maintained by Jeffrey S. Evans. Last updated 12 days ago.
biodiversityconservationecologyr-spatialrasterspatialvector
1.7 match 110 stars 9.55 score 736 scripts 2 dependents
mapme-initiative
mapme.biodiversity:Efficient Monitoring of Global Biodiversity Portfolios
Biodiversity areas, especially primary forest, serve a multitude of functions for local economy, regional functionality of the ecosystems as well as the global health of our planet. Recently, adverse changes in human land use practices and climatic responses to increased greenhouse gas emissions, put these biodiversity areas under a variety of different threats. The present package helps to analyse a number of biodiversity indicators based on freely available geographical datasets. It supports computational efficient routines that allow the analysis of potentially global biodiversity portfolios. The primary use case of the package is to support evidence based reporting of an organization's effort to protect biodiversity areas under threat and to identify regions were intervention is most duly needed.
Maintained by Darius A. Görgen. Last updated 3 months ago.
environmenteogismapmespatialsustainability
1.8 match 35 stars 9.24 score 287 scripts
ropensci
bowerbird:Keep a Collection of Sparkly Data Resources
Tools to get and maintain a data repository from third-party data providers.
Maintained by Ben Raymond. Last updated 4 days ago.
ropensciantarcticsouthern oceandataenvironmentalsatelliteclimatepeer-reviewed
1.9 match 50 stars 7.16 score 16 scripts 1 dependentsropensci
rOPTRAM:Derive Soil Moisture Using the OPTRAM Algorithm
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. et al., 2017. <https://doi.org/10.1016/j.rse.2017.05.041> .
Maintained by Micha Silver. Last updated 1 months ago.
1.7 match 9 stars 5.73 score 6 scriptsmlampros
fitbitViz:'Fitbit' Visualizations
Connection to the 'Fitbit' Web API <https://dev.fitbit.com/build/reference/web-api/> by including 'ggplot2' Visualizations, 'Leaflet' and 3-dimensional 'Rayshader' Maps. The 3-dimensional 'Rayshader' Map requires the installation of the 'CopernicusDEM' R package which includes the 30- and 90-meter elevation data.
Maintained by Lampros Mouselimis. Last updated 1 years ago.
blogdownfitbitfitbit-apigithub-actionsvisualization
1.7 match 9 stars 4.65 score 1 scripts
eea
hdar:'REST' API Client for Accessing Data on 'WEkEO HDA V2'
Provides seamless access to the WEkEO Harmonised Data Access (HDA) API, enabling users to query, download, and process data efficiently from the HDA platform. With 'hdar', researchers and data scientists can integrate the extensive HDA datasets into their R workflows, enhancing their data analysis capabilities. Comprehensive information on the API functionality and usage is available at <https://gateway.prod.wekeo2.eu/hda-broker/docs>.
Maintained by Matteo Mattiuzzi. Last updated 2 days ago.
1.2 match 3 stars 4.88 score 3 scripts
e-sensing
sits:Satellite Image Time Series Analysis for Earth Observation Data Cubes
An end-to-end toolkit for land use and land cover classification using big Earth observation data, based on machine learning methods applied to satellite image data cubes, as described in Simoes et al (2021) <doi:10.3390/rs13132428>. Builds regular data cubes from collections in AWS, Microsoft Planetary Computer, Brazil Data Cube, Copernicus Data Space Environment (CDSE), Digital Earth Africa, Digital Earth Australia, NASA HLS using the Spatio-temporal Asset Catalog (STAC) protocol (<https://stacspec.org/>) and the 'gdalcubes' R package developed by Appel and Pebesma (2019) <doi:10.3390/data4030092>. Supports visualization methods for images and time series and smoothing filters for dealing with noisy time series. Includes functions for quality assessment of training samples using self-organized maps as presented by Santos et al (2021) <doi:10.1016/j.isprsjprs.2021.04.014>. Includes methods to reduce training samples imbalance proposed by Chawla et al (2002) <doi:10.1613/jair.953>. Provides machine learning methods including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolutional neural networks proposed by Pelletier et al (2019) <doi:10.3390/rs11050523>, and temporal attention encoders by Garnot and Landrieu (2020) <doi:10.48550/arXiv.2007.00586>. Supports GPU processing of deep learning models using torch <https://torch.mlverse.org/>. Performs efficient classification of big Earth observation data cubes and includes functions for post-classification smoothing based on Bayesian inference as described by Camara et al (2024) <doi:10.3390/rs16234572>, and methods for active learning and uncertainty assessment. Supports region-based time series analysis using package supercells <https://jakubnowosad.com/supercells/>. Enables best practices for estimating area and assessing accuracy of land change as recommended by Olofsson et al (2014) <doi:10.1016/j.rse.2014.02.015>. Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.
Maintained by Gilberto Camara. Last updated 1 months ago.
big-earth-datacbersearth-observationeo-datacubesgeospatialimage-time-seriesland-cover-classificationlandsatplanetary-computerr-spatialremote-sensingrspatialsatellite-image-time-seriessatellite-imagerysentinel-2stac-apistac-catalogcpp
0.5 match 494 stars 9.50 score 384 scripts
willemijnvroege
RCGLS:Download and Open Data Provided by the Copernicus Global Land Service
Download and open manifest files provided by the Copernicus Global Land Service data <https://land.copernicus.eu/global/>. The manifest files are available at: <https://land.copernicus.vgt.vito.be/manifest/>. Also see: <https://land.copernicus.eu/global/access/>. Before you can download the data, you will first need to register to create a username and password.
Maintained by Willemijn Vroege. Last updated 4 years ago.
3.8 match 1.00 score 2 scripts
ecor
geotopbricks:An R Plug-in for the Distributed Hydrological Model GEOtop
It analyzes raster maps and other information as input/output files from the Hydrological Distributed Model GEOtop. It contains functions and methods to import maps and other keywords from geotop.inpts file. Some examples with simulation cases of GEOtop 2.x/3.x are presented in the package. Any information about the GEOtop Distributed Hydrological Model source code is available on www.geotop.org. Technical details about the model are available in Endrizzi et al (2014) <https://gmd.copernicus.org/articles/7/2831/2014/gmd-7-2831-2014.html>.
Maintained by Emanuele Cordano. Last updated 2 months ago.
0.5 match 4 stars 4.83 score 112 scriptsropensci
camsRad:Client for CAMS Radiation Service
Copernicus Atmosphere Monitoring Service (CAMS) Radiation Service provides time series of global, direct, and diffuse irradiations on horizontal surface, and direct irradiation on normal plane for the actual weather conditions as well as for clear-sky conditions. The geographical coverage is the field-of-view of the Meteosat satellite, roughly speaking Europe, Africa, Atlantic Ocean, Middle East. The time coverage of data is from 2004-02-01 up to 2 days ago. Data are available with a time step ranging from 15 min to 1 month. For license terms and to create an account, please see <http://www.soda-pro.com/web-services/radiation/cams-radiation-service>.
Maintained by Lukas Lundstrom. Last updated 5 years ago.
0.5 match 9 stars 4.65 score 10 scripts
hypertidy
whatarelief:Get topography elevation and online imagery data
Obtain elevation data, topography relief for any region on the Earth. Topography and bathymetry data is supported by default. Sensible defaults exist for usage, with a matrix of entire planet topography(and bathymetry) returned. The geographic extent can be modified (from whole-planet) to a simple region in longitude/latitude by 'xmin,xmax,ymin,ymax' range, or by specifying a grid exactly with extent, dimension, projection in generic or spatial formats ('terra' or 'raster'). Online sources for data are used, 'GEBCO' General Bathymetric Chart of the Oceans (GEBCO) as a background (to ~500m resolution), and Copernicus GLO-30 Digital Elevation Model for higher resolution (to ~30m resolution). Custom source/s of topography may be input to override defaults, links to file/s or URLs as required.
Maintained by Michael D. Sumner. Last updated 1 years ago.
0.5 match 50 stars 4.51 score 13 scripts
ybrugnara
dataresqc:C3S Quality Control Tools for Historical Climate Data
Quality control and formatting tools developed for the Copernicus Data Rescue Service. The package includes functions to handle the Station Exchange Format (SEF), various statistical tests for climate data at daily and sub-daily resolution, as well as functions to plot the data. For more information and documentation see <https://datarescue.climate.copernicus.eu/st_data-quality-control>.
Maintained by Yuri Brugnara. Last updated 2 years ago.
0.8 match 2.70 score 7 scripts