Data from Public Bicycle Hire Systems

  Mark Padgham   | OCTOBER 17, 2017

A new rOpenSci package provides access to data to which users may already have directly contributed, and for which contribution is fun, keeps you fit, and helps make the world a better place. The data come from using public bicycle hire schemes, and the package is called bikedata. Public bicycle hire systems operate in many cities throughout the world, and most systems collect (generally anonymous) data, minimally consisting of the times and locations at which every single bicycle trip starts and ends.

FedData - Getting assorted geospatial data into R

  Kyle Bocinsky   | AUGUST 24, 2017

The package FedData has gone through software review and is now part of rOpenSci. FedData includes functions to automate downloading geospatial data available from several federated data sources (mainly sources maintained by the US Federal government). Currently, the package enables extraction from six datasets: The National Elevation Dataset (NED) digital elevation models (1 and 1⁄3 arc-second; USGS) The National Hydrography Dataset (NHD) (USGS) The Soil Survey Geographic (SSURGO) database from the National Cooperative Soil Survey (NCSS), which is led by the Natural Resources Conservation Service (NRCS) under the USDA, The Global Historical Climatology Network (GHCN), coordinated by National Climatic Data Center at NOAA, The Daymet gridded estimates of daily weather parameters for North America, version 3, available from the Oak Ridge National Laboratory’s Distributed Active Archive Center (DAAC), and The International Tree Ring Data Bank (ITRDB), coordinated by National Climatic Data Center at NOAA.

Random GeoJSON and WKT with randgeo

  Scott Chamberlain   |   Noam Ross   | APRIL 20, 2017

randgeo generates random points and shapes in GeoJSON and WKT formats for use in examples, teaching, or statistical applications. Points and shapes are generated in the long/lat coordinate system and with appropriate spherical geometry; random points are distributed evenly across the globe, and random shapes are sized according to a maximum great-circle distance from the center of the shape. randgeo was adapted from to have a pure R implementation without any dependencies as well as appropriate geometry.

ccafs - client for CCAFS General Circulation Models data

  Scott Chamberlain   | MARCH 1, 2017

I’ve recently released the new package ccafs, which provides access to data from Climate Change, Agriculture and Food Security (CCAFS; General Circulation Models (GCM) data. GCM’s are a particular type of climate model, used for weather forecasting, and climate change forecasting - read more at ccafs falls in the data client camp - its focus is on getting users data - many rOpenSci packages fall into this area.

The rOpenSci geospatial suite

  Scott Chamberlain   | NOVEMBER 22, 2016

Geospatial data - data embedded in a spatial context - is used across disciplines, whether it be history, biology, business, tech, public health, etc. Along with community contributors, we’re working on a suite of tools to make working with spatial data in R as easy as possible. If you’re not familiar with geospatial tools, it’s helpful to see what people do with them in the real world. Example 1

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