Showing 40 of total 40 results (show query)
ropensci
nasapower:NASA POWER API Client
An API client for NASA POWER global meteorology, surface solar energy and climatology data API. POWER (Prediction Of Worldwide Energy Resources) data are freely available for download with varying spatial resolutions dependent on the original data and with several temporal resolutions depending on the POWER parameter and community. This work is funded through the NASA Earth Science Directorate Applied Science Program. For more on the data themselves, the methodologies used in creating, a web- based data viewer and web access, please see <https://power.larc.nasa.gov/>.
Maintained by Adam H. Sparks. Last updated 10 days ago.
nasameteorological-dataweatherglobalweather-datameteorologynasa-poweragroclimatologyearth-sciencedata-accessclimate-dataagroclimatology-dataweather-variables
24.3 match 101 stars 9.98 score 137 scripts 3 dependents
worldbank
blackmarbler:Black Marble Data and Statistics
Geographically referenced data and statistics of nighttime lights from NASA Black Marble <https://blackmarble.gsfc.nasa.gov/>.
Maintained by Robert Marty. Last updated 19 days ago.
nasanasa-datanasa-earth-datanighttime-lightsraster-dataviirsworldbankzonal-statistics
27.8 match 19 stars 6.13 score 47 scriptsropensci
smapr:Acquisition and Processing of NASA Soil Moisture Active-Passive (SMAP) Data
Facilitates programmatic access to NASA Soil Moisture Active Passive (SMAP) data with R. It includes functions to search for, acquire, and extract SMAP data.
Maintained by Maxwell Joseph. Last updated 2 years ago.
acquisitionextract-datanasapeer-reviewedrastersmap-datasoil-mappingsoil-moisturesoil-moisture-sensor
17.8 match 84 stars 4.97 score 22 scripts
gabrielblain
PowerSDI:Calculate Standardised Drought Indices Using NASA POWER Data
A set of functions designed to calculate the standardised precipitation and standardised precipitation evapotranspiration indices using NASA POWER data as described in Blain et al. (2023) <doi:10.2139/ssrn.4442843>. These indices are calculated using a reference data source. The functions verify if the indices' estimates meet the assumption of normality and how well NASA POWER estimates represent real-world data. Indices are calculated in a routine mode. Potential evapotranspiration amounts and the difference between rainfall and potential evapotranspiration are also calculated. The functions adopt a basic time scale that splits each month into four periods. Days 1 to 7, days 8 to 14, days 15 to 21, and days 22 to 28, 29, 30, or 31, where 'TS=4' corresponds to a 1-month length moving window (calculated 4 times per month) and 'TS=48' corresponds to a 12-month length moving window (calculated 4 times per month).
Maintained by Gabriel Constantino Blain. Last updated 8 months ago.
13.3 match 4 stars 5.08 score 1 scripts 1 dependents
ptaconet
modisfast:Fast and Efficient Access to MODIS Earth Observation Data
Programmatic interface to several NASA Earth Observation 'OPeNDAP' servers (Open-source Project for a Network Data Access Protocol) (<https://www.opendap.org/>). Allows for easy downloads of MODIS subsets, as well as other Earth Observation datacubes, in a time-saving and efficient way : by sampling it at the very downloading phase (spatially, temporally and dimensionally).
Maintained by Paul Taconet. Last updated 5 days ago.
data-cubeearth-science-dataenvironmental-datagpmlandmodisnasaopendapprecipitation-datatemperature-datavegetation-dataviirs
11.5 match 29 stars 5.60 score 13 scriptsropensci
exoplanets:Access NASA's Exoplanet Archive Data
The goal of exoplanets is to provide access to NASA's Exoplanet Archive TAP Service. For more information regarding the API please read the documentation <https://exoplanetarchive.ipac.caltech.edu/index.html>.
Maintained by Tyler Littlefield. Last updated 2 years ago.
16.3 match 13 stars 3.81 score 6 scripts
sevvandi
stxplore:Exploration of Spatio-Temporal Data
A set of statistical tools for spatio-temporal data exploration. Includes simple plotting functions, covariance calculations and computations similar to principal component analysis for spatio-temporal data. Can use both dataframes and stars objects for all plots and computations. For more details refer 'Spatio-Temporal Statistics with R' (Christopher K. Wikle, Andrew Zammit-Mangion, Noel Cressie, 2019, ISBN:9781138711136).
Maintained by Sevvandi Kandanaarachchi. Last updated 2 years ago.
11.0 match 5 stars 4.70 score 7 scripts
pecanproject
PEcAn.data.remote:PEcAn Functions Used for Extracting Remote Sensing Data
PEcAn module for processing remote data. Python module requirements: requests, json, re, ast, panads, sys. If any of these modules are missing, install using pip install <module name>.
Maintained by Bailey Morrison. Last updated 2 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
4.9 match 216 stars 8.74 score 6 scripts 5 dependents
bluegreen-labs
appeears:Interface to 'AppEEARS' NASA Web Services
Programmatic interface to the NASA Application for Extracting and Exploring Analysis Ready Samples services (AppEEARS; <https://appeears.earthdatacloud.nasa.gov/>). The package provides easy access to analysis ready earth observation data in R.
Maintained by Koen Hufkens. Last updated 19 days ago.
7.4 match 11 stars 5.22 score 15 scripts
projectmosaic
mosaicCalc:R-Language Based Calculus Operations for Teaching
Software to support the introductory *MOSAIC Calculus* textbook <https://www.mosaic-web.org/MOSAIC-Calculus/>), one of many data- and modeling-oriented educational resources developed by Project MOSAIC (<https://www.mosaic-web.org/>). Provides symbolic and numerical differentiation and integration, as well as support for applied linear algebra (for data science), and differential equations/dynamics. Includes grammar-of-graphics-based functions for drawing vector fields, trajectories, etc. The software is suitable for general use, but intended mainly for teaching calculus.
Maintained by Daniel Kaplan. Last updated 20 days ago.
4.0 match 13 stars 8.68 score 546 scripts
simon-smart88
shinyscholar:A Template for Creating Reproducible 'shiny' Applications
Create a skeleton 'shiny' application with create_template() that is reproducible, can be saved and meets academic standards for attribution. Forked from 'wallace'. Code is split into modules that are loaded and linked together automatically and each call one function. Guidance pages explain modules to users and flexible logging informs them of any errors. Options enable asynchronous operations, viewing of source code, interactive maps and data tables. Use to create complex analytical applications, following best practices in open science and software development. Includes functions for automating repetitive development tasks and an example application at run_shinyscholar() that requires install.packages("shinyscholar", dependencies = TRUE). A guide to developing applications can be found on the package website.
Maintained by Simon E. H. Smart. Last updated 1 months ago.
5.5 match 20 stars 5.36 score 5 scripts
carlos-alberto-silva
rGEDI:NASA's Global Ecosystem Dynamics Investigation (GEDI) Data Visualization and Processing
Set of tools for downloading, reading, visualizing and processing GEDI Level1B, Level2A and Level2B data.
Maintained by Caio Hamamura. Last updated 5 months ago.
4.4 match 169 stars 6.11 score 85 scripts 1 dependents
rspatial
luna:Tools for Satellite Remote Sensing (Earth Observation) Data Processing
Tools for acquiring and (pre-) processing satellite remote sensing data. Including for downloading data from NASA such as LANDSAT and MODIS.
Maintained by Robert J. Hijmans. Last updated 3 months ago.
6.3 match 34 stars 3.95 score 52 scripts
fbrun-acta
ZeBook:Working with Dynamic Models for Agriculture and Environment
R package accompanying the book Working with dynamic models for agriculture and environment, by Daniel Wallach (INRA), David Makowski (INRA), James W. Jones (U.of Florida), Francois Brun (ACTA). 3rd edition 2018-09-27.
Maintained by Francois Brun. Last updated 6 years ago.
10.3 match 4 stars 2.37 score 59 scripts
hadley
cubelyr:A Data Cube 'dplyr' Backend
An implementation of a data cube extracted out of 'dplyr' for backward compatibility.
Maintained by Hadley Wickham. Last updated 2 years ago.
3.8 match 38 stars 6.44 score 59 scripts 4 dependents
dankelley
ocedata:Oceanographic Data Sets for 'oce' Package
Several Oceanographic data sets are provided for use by the 'oce' package, and for other purposes.
Maintained by Dan Kelley. Last updated 2 years ago.
3.4 match 8 stars 5.07 score 146 scripts
femiguez
apsimx:Inspect, Read, Edit and Run 'APSIM' "Next Generation" and 'APSIM' Classic
The functions in this package inspect, read, edit and run files for 'APSIM' "Next Generation" ('JSON') and 'APSIM' "Classic" ('XML'). The files with an 'apsim' extension correspond to 'APSIM' Classic (7.x) - Windows only - and the ones with an 'apsimx' extension correspond to 'APSIM' "Next Generation". For more information about 'APSIM' see (<https://www.apsim.info/>) and for 'APSIM' next generation (<https://apsimnextgeneration.netlify.app/>).
Maintained by Fernando Miguez. Last updated 2 days ago.
1.7 match 59 stars 9.71 score 68 scripts 2 dependents
mikejohnson51
climateR:climateR
Find, subset, and retrive geospatial data by AOI.
Maintained by Mike Johnson. Last updated 3 months ago.
aoiclimatedatasetgeospatialgridded-climate-dataweather
1.9 match 187 stars 8.74 score 156 scripts 1 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
eflores89
nasadata:Interface to Various NASA API's
Provides functions to access NASA's Earth Imagery and Assets API and the Earth Observatory Natural Event Tracker (EONET) webservice.
Maintained by Eduardo Flores. Last updated 9 years ago.
3.7 match 21 stars 4.10 score 12 scriptscarlos-alberto-silva
ICESat2VegR:NASA's Ice, Cloud, and Elevation Satellite (ICESat-2) Data Analysis for Land and Vegetation Applications
Set of tools for downloading, reading, visualizing, processing and exporting NASA's ICESat-2 ATL03 (Global Geolocated Photon Data) and ATL08 (Land and Vegetation Height) products for Land and Vegetation Applications.
Maintained by Caio Hamamura. Last updated 6 months ago.
3.2 match 11 stars 4.57 score 21 scripts
heike
ggpcp:Parallel Coordinate Plots in the 'ggplot2' Framework
Modern Parallel Coordinate Plots have been introduced in the 1980s as a way to visualize arbitrarily many numeric variables. This Grammar of Graphics implementation also incorporates categorical variables into the plots in a principled manner. By separating the data managing part from the visual rendering, we give full access to the users while keeping the number of parameters manageably low.
Maintained by Heike Hofmann. Last updated 4 days ago.
3.5 match 1 stars 4.04 score 73 scripts
caiohamamura
rGEDIsimulator:NASA's Global Ecosystem Dynamics Investigation (GEDI) Simulator for ALS Data
Simulates the fullwaveform GEDI data and calculates metrics based on aerial lidar systems data.
Maintained by Caio Hamamura. Last updated 11 months ago.
4.4 match 7 stars 3.02 score 2 scripts
pvanlaake
ncdfCF:Easy Access to NetCDF Files with CF Metadata Conventions
Network Common Data Form ('netCDF') files are widely used for scientific data. Library-level access in R is provided through packages 'RNetCDF' and 'ncdf4'. Package 'ncdfCF' is built on top of 'RNetCDF' and makes the data and its attributes available as a set of R6 classes that are informed by the Climate and Forecasting Metadata Conventions. Access to the data uses standard R subsetting operators and common function forms.
Maintained by Patrick Van Laake. Last updated 2 days ago.
1.8 match 5.41 score 4 scripts
finleya
spNNGP:Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes
Fits univariate Bayesian spatial regression models for large datasets using Nearest Neighbor Gaussian Processes (NNGP) detailed in Finley, Datta, Banerjee (2022) <doi:10.18637/jss.v103.i05>, Finley, Datta, Cook, Morton, Andersen, and Banerjee (2019) <doi:10.1080/10618600.2018.1537924>, and Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091>.
Maintained by Andrew Finley. Last updated 6 months ago.
3.2 match 6 stars 2.64 score 72 scripts
alessiapini
fdatest:Interval Testing Procedure for Functional Data
Implementation of the Interval Testing Procedure for functional data in different frameworks (i.e., one or two-population frameworks, functional linear models) by means of different basis expansions (i.e., B-spline, Fourier, and phase-amplitude Fourier). The current version of the package requires functional data evaluated on a uniform grid; it automatically projects each function on a chosen functional basis; it performs the entire family of multivariate tests; and, finally, it provides the matrix of the p-values of the previous tests and the vector of the corrected p-values. The functional basis, the coupled or uncoupled scenario, and the kind of test can be chosen by the user. The package provides also a plotting function creating a graphical output of the procedure: the p-value heat-map, the plot of the corrected p-values, and the plot of the functional data.
Maintained by Alessia Pini. Last updated 3 years ago.
3.6 match 2.35 score 37 scripts 1 dependents
hypertidy
L3bin:Integerized Sinusoidal Binning Scheme for Level 3 Data
The NASA Ocean Biology processing Group L3 bin scheme, based on the sinusoidal map projection. Psuedo code for the binning scheme was published in Appendix A of NASA Technical Memorandum 104566, Vol. 32., listed in URL.
Maintained by Michael D. Sumner. Last updated 3 months ago.
2.5 match 4 stars 2.60 score 2 scripts
cran
thregI:Threshold Regression for Interval-Censored Data with a Cure Rate Option
Fit a threshold regression model for Interval Censored Data based on the first-hitting-time of a boundary by the sample path of a Wiener diffusion process. The threshold regression methodology is well suited to applications involving survival and time-to-event data.
Maintained by Man-Hua Chen. Last updated 7 years ago.
3.6 match 1.48 score 1 dependents
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
cortinah
hockeystick:Download and Visualize Essential Climate Change Data
Provides easy access to essential climate change datasets to non-climate experts. Users can download the latest raw data from authoritative sources and view it via pre-defined 'ggplot2' charts. Datasets include atmospheric CO2, methane, emissions, instrumental and proxy temperature records, sea levels, Arctic/Antarctic sea-ice, Hurricanes, and Paleoclimate data. Sources include: NOAA Mauna Loa Laboratory <https://gml.noaa.gov/ccgg/trends/data.html>, Global Carbon Project <https://www.globalcarbonproject.org/carbonbudget/>, NASA GISTEMP <https://data.giss.nasa.gov/gistemp/>, National Snow and Sea Ice Data Center <https://nsidc.org/home>, CSIRO <https://research.csiro.au/slrwavescoast/sea-level/measurements-and-data/sea-level-data/>, NOAA Laboratory for Satellite Altimetry <https://www.star.nesdis.noaa.gov/socd/lsa/SeaLevelRise/> and HURDAT Atlantic Hurricane Database <https://www.aoml.noaa.gov/hrd/hurdat/Data_Storm.html>, Vostok Paleo carbon dioxide and temperature data: <doi:10.3334/CDIAC/ATG.009>.
Maintained by Hernando Cortina. Last updated 4 months ago.
carboncarbon-dioxide-datacarbon-emissionsclimateclimate-changeclimate-dataclimate-scienceggplot2methanenoaasea-icesea-levelstemperature-datawarming-stripes
0.8 match 50 stars 4.70 score 8 scriptscran
cenROC:Estimating Time-Dependent ROC Curve and AUC for Censored Data
Contains functions to estimate a smoothed and a non-smoothed (empirical) time-dependent receiver operating characteristic curve and the corresponding area under the receiver operating characteristic curve and the optimal cutoff point for the right and interval censored survival data. See Beyene and El Ghouch (2020)<doi:10.1002/sim.8671> and Beyene and El Ghouch (2022) <doi:10.1002/bimj.202000382>.
Maintained by Kassu Mehari Beyene. Last updated 2 years ago.
3.5 match 1.00 score
geanders
hurricaneexposure:Explore and Map County-Level Hurricane Exposure in the United States
Allows users to create time series of tropical storm exposure histories for chosen counties for a number of hazard metrics (wind, rain, distance from the storm, etc.). This package interacts with data available through the 'hurricaneexposuredata' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/geanders/hurricaneexposure>. The size of the 'hurricaneexposuredata' package is approximately 20 MB. This work was supported in part by grants from the National Institute of Environmental Health Sciences (R00ES022631), the National Science Foundation (1331399), and a NASA Applied Sciences Program/Public Health Program Grant (NNX09AV81G).
Maintained by Brooke Anderson. Last updated 5 years ago.
0.5 match 35 stars 6.71 score 49 scripts 1 dependents
rstub
swephR:High Precision Swiss Ephemeris
The Swiss Ephemeris (version 2.10.03) is a high precision ephemeris based upon the DE431 ephemerides from NASA's JPL. It covers the time range 13201 BCE to 17191 CE. This package uses the semi-analytic theory by Steve Moshier. For faster and more accurate calculations, the compressed Swiss Ephemeris data is available in the 'swephRdata' package. To access this data package, run 'install.packages("swephRdata", repos = "https://rstub.r-universe.dev", type = "source")'. The size of the 'swephRdata' package is approximately 115 MB. The user can also use the original JPL DE431 data.
Maintained by Ralf Stubner. Last updated 9 months ago.
0.5 match 10 stars 6.28 score 64 scripts 2 dependents
sazpark
fermicatsR:Fermi Large Area Telescope Catalogs
Data from various catalogs of astrophysical gamma-ray sources detected by NASA's Large Area Telescope (The Astrophysical Journal, 697, 1071, 2009 June 1), on board the Fermi gamma-ray satellite. More information on Fermi and its data products is available from the Fermi Science Support Center (http://fermi.gsfc.nasa.gov/ssc/).
Maintained by Pablo Saz Parkinson. Last updated 9 years ago.
0.8 match 1 stars 2.70 score 1 scripts
chadr
droptest:Simulates LOX Drop Testing
Generates simulated data representing the LOX drop testing process (also known as impact testing). A simulated process allows for accelerated study of test behavior. Functions are provided to simulate trials, test series, and groups of test series. Functions for creating plots specific to this process are also included. Test attributes and criteria can be set arbitrarily. This work is not endorsed by or affiliated with NASA. See "ASTM G86-17, Standard Test Method for Determining Ignition Sensitivity of Materials to Mechanical Impact in Ambient Liquid Oxygen and Pressurized Liquid and Gaseous Oxygen Environments" <doi:10.1520/G0086-17>.
Maintained by Chad Ross. Last updated 7 years ago.
0.5 match 1 stars 2.70 score 8 scripts
