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README.Rmd
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---
output: github_document
editor_options:
chunk_output_type: console
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%",
dpi = 72
)
```
[](https://www.repostatus.org/#active)
[](https://cran.r-project.org/package=FedData)
[](https://github.com/metacran/cranlogs.app)
[](https://github.com/metacran/cranlogs.app)
[](https://travis-ci.org/ropensci/FedData)
[](https://codecov.io/github/ropensci/FedData?branch=master)
[](https://doi.org/10.5281/zenodo.596344)
[](https://github.com/ropensci/onboarding/issues/13)
`FedData` is an *R* package implementing functions to automate downloading geospatial data available from several federated data sources (mainly sources maintained by the US Federal government).
**FedData version 2.5 will be the final minor CRAN release of FedData 2. FedData 3 will be released in the coming months, but some code built on FedData 2 will not be compatible with FedData 3.**
Currently, the package enables extraction from seven datasets:
* The [National Elevation Dataset (NED)](http://ned.usgs.gov) digital elevation models (1 and 1/3 arc-second; USGS)
* The [National Hydrography Dataset (NHD)](http://nhd.usgs.gov) (USGS)
* The [Soil Survey Geographic (SSURGO) database](http://websoilsurvey.sc.egov.usda.gov/) 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)](http://www.ncdc.noaa.gov/data-access/land-based-station-data/land-based-datasets/global-historical-climatology-network-ghcn), coordinated by National Climatic Data Center at NOAA
* The [Daymet](https://daymet.ornl.gov/) gridded estimates of daily weather parameters for North America, version 3, available from the Oak Ridge National Laboratory's Distributed Active Archive Center (DAAC)
* The [International Tree Ring Data Bank (ITRDB)](http://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring), coordinated by National Climatic Data Center at NOAA
* The [National Land Cover Database (NLCD)](https://www.mrlc.gov/)
* The [NASS Cropland Data Layer](https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php) from the National Agricultural Statistics Service
This package is designed with the large-scale geographic information system (GIS) use-case in mind: cases where the use of dynamic web-services is impractical due to the scale (spatial and/or temporal) of analysis. It functions primarily as a means of downloading tiled or otherwise spatially-defined datasets; additionally, it can preprocess those datasets by extracting data within an area of interest (AoI), defined spatially. It relies heavily on the [**sp**](https://cran.r-project.org/package=sp), [**raster**](https://cran.r-project.org/package=raster), and [**rgdal**](https://cran.r-project.org/package=rgdal) packages.
This package has been built and tested on a source (Homebrew) install of *R* on macOS 10.14 (High Sierra), and has been successfully run on Ubuntu 14.04.5 LTS (Trusty), Ubuntu 16.04.1 LTS (Xenial) and binary installs of *R* on Mac OS 10.14 and Windows 10.
### Development
+ [Kyle Bocinsky](http://bocinsky.io) - Crow Canyon Archaeological Center, Cortez, CO
### Contributors
+ Dylan Beaudette - USDA-NRCS Soil Survey Office, Sonora, CA
+ Scott Chamberlain - ROpenSci and Museum of Paleontology at UC Berkeley
### Install `FedData`
+ From CRAN:
```{r eval = FALSE}
install.packages('FedData')
```
+ Development version from GitHub:
```{r eval = FALSE}
install.packages("devtools")
devtools::install_github("ropensci/FedData")
```
+ Linux (Ubuntu 14.04.5 or 16.04.1):
First, in terminal:
```bash
sudo add-apt-repository ppa:ubuntugis/ppa -y
sudo apt-get update -q
sudo apt-get install libssl-dev libcurl4-openssl-dev netcdf-bin libnetcdf-dev gdal-bin libgdal-dev
```
Then, in R:
```{r eval = FALSE}
update.packages("survival")
install.packages("devtools")
devtools::install_github("ropensci/FedData")
```
### Demonstration
This demonstration script is available as an R Markdown document in the GitHub repository: [https://github.com/ropensci/FedData](https://github.com/ropensci/FedData).
#### Load `FedData` and define a study area
```{r results="hide", message=FALSE}
# FedData Tester
library(FedData)
library(magrittr)
# Extract data for the Village Ecodynamics Project "VEPIIN" study area:
# http://veparchaeology.org
vepPolygon <- polygon_from_extent(raster::extent(672800, 740000, 4102000, 4170000),
proj4string = "+proj=utm +datum=NAD83 +zone=12")
```
#### Get and plot the National Elevation Dataset for the study area
```{r results="hide", message=FALSE}
# Get the NED (USA ONLY)
# Returns a raster
NED <- get_ned(template = vepPolygon,
label = "VEPIIN")
# Plot with raster::plot
raster::plot(NED)
```
#### Get and plot the Daymet dataset for the study area
```{r results="hide", message=FALSE, warning=FALSE}
# Get the DAYMET (North America only)
# Returns a raster
DAYMET <- get_daymet(template = vepPolygon,
label = "VEPIIN",
elements = c("prcp","tmax"),
years = 1980:1985)
# Plot with raster::plot
raster::plot(DAYMET$tmax$X1985.10.23)
```
#### Get and plot the daily GHCN precipitation data for the study area
```{r results="hide", message=FALSE}
# Get the daily GHCN data (GLOBAL)
# Returns a list: the first element is the spatial locations of stations,
# and the second is a list of the stations and their daily data
GHCN.prcp <- get_ghcn_daily(template = vepPolygon,
label = "VEPIIN",
elements = c('prcp'))
# Plot the NED again
raster::plot(NED)
# Plot the spatial locations
sp::plot(GHCN.prcp$spatial,
pch = 1,
add = TRUE)
legend('bottomleft',
pch = 1,
legend="GHCN Precipitation Records")
```
#### Get and plot the daily GHCN temperature data for the study area
```{r results="hide", message=FALSE}
# Elements for which you require the same data
# (i.e., minimum and maximum temperature for the same days)
# can be standardized using standardize==T
GHCN.temp <- get_ghcn_daily(template = vepPolygon,
label = "VEPIIN",
elements = c('tmin','tmax'),
years = 1980:1985,
standardize = TRUE)
# Plot the NED again
raster::plot(NED)
# Plot the spatial locations
sp::plot(GHCN.temp$spatial,
add = TRUE,
pch = 1)
legend('bottomleft',
pch = 1,
legend = "GHCN Temperature Records")
```
#### Get and plot the National Hydrography Dataset for the study area
```{r results="hide", message=FALSE}
# Get the NHD (USA ONLY)
NHD <- get_nhd(template = vepPolygon,
label = "VEPIIN")
# Plot the NED again
raster::plot(NED)
# Plot the NHD data
NHD %>%
lapply(sp::plot,
col = 'black',
add = TRUE)
```
#### Get and plot the NRCS SSURGO data for the study area
```{r results="hide", message=FALSE, warning=FALSE}
# Get the NRCS SSURGO data (USA ONLY)
SSURGO.VEPIIN <- get_ssurgo(template = vepPolygon,
label = "VEPIIN")
# Plot the NED again
raster::plot(NED)
# Plot the SSURGO mapunit polygons
plot(SSURGO.VEPIIN$spatial,
lwd = 0.1,
add = TRUE)
```
#### Get and plot the NRCS SSURGO data for particular soil survey areas
```{r results="hide", message=FALSE}
# Or, download by Soil Survey Area names
SSURGO.areas <- get_ssurgo(template = c("CO670","CO075"),
label = "CO_TEST")
# Let's just look at spatial data for CO675
SSURGO.areas.CO675 <- SSURGO.areas$spatial[SSURGO.areas$spatial$AREASYMBOL=="CO075",]
# And get the NED data under them for pretty plotting
NED.CO675 <- get_ned(template = SSURGO.areas.CO675,
label = "SSURGO_CO675")
# Plot the SSURGO mapunit polygons, but only for CO675
plot(NED.CO675)
plot(SSURGO.areas.CO675,
lwd = 0.1,
add = TRUE)
```
#### Get and plot the ITRDB chronology locations in the study area
```{r results="hide", message=FALSE}
# Get the ITRDB records
ITRDB <- get_itrdb(template = vepPolygon,
label = "VEPIIN",
recon.years = 850:2000,
calib.years = 1924:1983,
measurement.type = "Ring Width",
chronology.type = "ARSTND")
# Plot the NED again
raster::plot(NED)
# Map the locations of the tree ring chronologies
plot(ITRDB$metadata$geometry,
pch = 1,
add = TRUE)
legend('bottomleft',
pch = 1,
legend = "ITRDB chronologies")
```
#### Get and plot the National Land Cover Dataset for the study area
```{r results="hide", message=FALSE}
# Get the NLCD (USA ONLY)
# Returns a raster
NLCD <- get_nlcd(template = vepPolygon,
year = 2016,
dataset = "Land_Cover",
label = "VEPIIN")
# Plot with raster::plot
raster::plot(NLCD)
# You can also download the Canopy (2011 only) or impervious datasets:
NLCD_canopy <- get_nlcd(template = vepPolygon,
year = 2011,
dataset = "Tree_Canopy",
label = "VEPIIN")
# Plot with raster::plot
raster::plot(NLCD_canopy)
NLCD_impervious <- get_nlcd(template = vepPolygon,
year = 2016,
dataset = "Impervious",
label = "VEPIIN")
# Plot with raster::plot
raster::plot(NLCD_impervious)
```
#### Get and plot the NASS Cropland Data Layer for the study area
```{r results="hide", message=FALSE}
# Get the NASS (USA ONLY)
# Returns a raster
NASS <- get_nass(template = vepPolygon,
year = 2016,
label = "VEPIIN")
# Plot with raster::plot
raster::plot(NASS)
# Get the NASS classification table
raster::levels(NASS)[[1]]
```
-----------
### Acknowledgements
This package is a product of SKOPE ([Synthesizing Knowledge of Past Environments](http://www.openskope.org)) and the Village Ecodynamics Project. This software is licensed under the [MIT license](https://opensource.org/licenses/MIT).
FedData was reviewed for [rOpenSci](https://ropensci.org) by [\@jooolia](https://github.com/jooolia), and was greatly improved as a result. [rOpenSci](https://ropensci.org) onboarding was coordinated by [\@sckott](https://github.com/sckott).
<!-- [](https://ropensci.org) -->