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/>.
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nasameteorological-dataweatherglobalweather-datameteorologynasa-poweragroclimatologyearth-sciencedata-accessclimate-dataagroclimatology-dataweather-variables
9.15 score 107 stars 6 dependents 235 scripts 2.2k downloads
GSODR - Global Surface Summary of the Day ('GSOD') Weather Data Client
Provides automated downloading, parsing, cleaning, unit conversion and formatting of Global Surface Summary of the Day ('GSOD') weather data from the from the USA National Centers for Environmental Information ('NCEI'). The data were retired on 2025-08-29 and are no longer updated. Units are converted from from United States Customary System ('USCS') units to International System of Units ('SI'). Stations may be individually checked for number of missing days defined by the user, where stations with too many missing observations are omitted. Only stations with valid reported latitude and longitude values are permitted in the final data. Additional useful elements, saturation vapour pressure ('es'), actual vapour pressure ('ea') and relative humidity ('RH') are calculated from the original data using the improved August-Roche-Magnus approximation (Alduchov & Eskridge 1996) and included in the final data set. The resulting metadata include station identification information, country, state, latitude, longitude, elevation, weather observations and associated flags. For information on the 'GSOD' data from 'NCEI', please see the 'GSOD' 'readme.txt' file available from, <https://www.ncei.noaa.gov/pub/data/gsod/readme.txt>.
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us-nceimeteorological-dataglobal-weatherweatherweather-datameteorologystation-datasurface-weatherdata-accessus-ncdcdaily-datadaily-weatherglobal-datagsodhistorical-datahistorical-weatherncdcnceiweather-informationweather-stations
7.49 score 99 stars 155 scripts 528 downloads
read.abares - Read Australian Agricultural Data from Government Agencies
Downloads and imports agricultural data from the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) <https://www.agriculture.gov.au/abares> and the Australian Bureau of Statistics (ABS) <https://www.abs.gov.au>. Supports multiple data formats including spreadsheets, comma‑separated value (CSV) files, and geospatial data such as shapefiles and GeoTIFFs. Covers topics such as broadacre crops, livestock, soils, commodities and related agricultural information. The package standardises field names and data formats to improve interoperability and simplify analysis. It also streamlines the import of geospatial data and corrects common issues found in these data sources upon loading.
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agricultureagriculture-dataagriculture-datasetagriculture-trade-dataaustraliadata-retrievalland-use-classificationland-use-dataopen-dataopen-datasetstrade-data
5.29 score 5 stars 1 dependents 5 scripts 192 downloadsgetCRUCLdata - 'CRU' 'CL' v. 2.0 Climatology Client
Provides functions that automate downloading and importing University of East Anglia Climate Research Unit ('CRU') 'CL' v. 2.0 climatology data, facilitates the calculation of minimum temperature and maximum temperature and formats the data into a data.table object or a 'terra' 'SpatRaster' object. 'CRU' 'CL' v. 2.0 data are a gridded climatology of 1961-1990 monthly means released in 2002 and cover all land areas (excluding Antarctica) at 10 arc minutes (0.1666667 degree) resolution. For more information see the description of the data provided by the University of East Anglia Climate Research Unit, <https://crudata.uea.ac.uk/cru/data/hrg/tmc/readme.txt>.
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anglia-cruclimate-datacru-cl2temperaturerainfallelevationdata-accesswindrelative-humiditysolar-radiationdiurnal-temperaturefrostcrupeer-reviewed
5.29 score 17 stars 19 scripts 19 downloadshagis - Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity
Analysis of plant pathogen pathotype survey data. Functions provided calculate distribution of susceptibilities, distribution of complexities with statistics, pathotype frequency distribution, as well as diversity indices for pathotypes. This package is meant to be a direct replacement for Herrmann, Löwer and Schachtel's (1999) <doi:10.1046/j.1365-3059.1999.00325.x> Habgood-Gilmour Spreadsheet, 'HaGiS', previously used for pathotype analysis.
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plant-pathologypathotypepathogen-surveyvirulence analysisdifferential setassessment scalepathotype-complexitiesplant-diseasepopulation-diversities
5.23 score 1 stars 14 scripts 199 downloads
AAGIThemes - AAGI Branding for Graphical and Tabular Outputs
Applies Analytics for the Australian Grains Industry ('AAGI') external brand guidelines to graphics. 'AAGI' colours and font guidelines are applied as useful and reasonable to base graphics, 'ggplot2' figures, 'flextable' and 'gt' objects.
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4.40 score 1 stars 1 dependents 21 scripts
epicrop - SEIR Simulation Modelling of Crop Diseases
Generic simulation modelling of crop diseases using a Susceptible-Exposed-Infectious-Removed ('SEIR') model. This type of model was first described in botanical epidemiology by Zadoks (1971) <doi:10.1094/Phyto-61-600> and implemented in the 'EPIRICE' model by Savary et al. (2012) <doi:10.1016/j.cropro.2011.11.009> detailing the model's development, use and results from modelling global unmanaged epidemics of rice diseases for five major rice diseases, bacterial blight, brown spot, leaf blast, sheath blight and tungro. Specific functions are provided to simulate all of these diseases with a generic 'SEIR' model function that is suitable for parameterising for use with other pathosystems as demonstrated in Savary et al. 2012 and Kim et al. 2015 <doi:10.1016/j.agrformet.2015.01.011> along with two wheat diseases, brown (leaf) rust and Septoria tritici blotch as published in Savary et al. 2015 <doi:10.1007/s10658-015-0650-7>. Functions for fetching and formatting weather data from the NASA POWER database are also provided to simplify the process of running simulations.
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ricewheatbotanical-epidemiologydiseasemodelseiragricultural-modellingagricultural-modelingcrop-protectionagricultural-researchmodellingmodelingseir-modelplant-disease
4.18 score 1 scriptsAAGISurvey - Create AAGI Survey URLs and Analyse AAGI Survey Results
Create 'AAGI' service and support survey URLs interactively or scripted for sharing with partners.
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quarto
4.13 score 1 dependents
AAGIPalettes - AAGI Colours and Colour Palettes
Colour palettes based on the official Analytics for the Australian Grains Industry ('AAGI') comms guide and others designed to work harmoniously with the official 'AAGI' colours while being colour vision deficient (CVD) friendly.
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4.03 score 3 stars 2 dependents 17 scripts
fifo - Extract Australian Agricultural and Ecological Data from Publicly Available Data Set Using GPS Points
Extracts point data for a given GPS coordinate that includes soil data, weather data and GRDC agro-ecological zone information at that point in Australia.
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agricultureaustraliaagroecologysoilsweatherweather-datasoils-dataagriculture-research
3.88 score