get_site_data_from_NASIS_db: Extract Site Data from a local NASIS Database

Description

Get site-level data from a local NASIS database.

Usage

get_site_data_from_NASIS_db(SS = TRUE, stringsAsFactors = default.stringsAsFactors())

Arguments

fetch data from Selected Set in NASIS or from the entire local database (default: TRUE)

stringsAsFactors

logical: should character vectors be converted to factors? This argument is passed to the uncode() function. It does not convert those vectors that have been set outside of uncode() (i.e. hard coded). The 'factory-fresh' default is TRUE, but this can be changed by setting options(stringsAsFactors = FALSE)

Value

A dataframe.

Details

When multiple "site bedrock" entries are present, only the shallowest is returned by this function.

Examples

Run this code

# NOT RUN {
## Example: export / convert DMS coordinates from NASIS and save to DD import file

# load required libraries
if(require(aqp) &
    require(soilDB) &
    require(rgdal) &
    require(plyr)) {

# get site data from NASIS
s <- try(get_site_data_from_NASIS_db())

if(!inherits(s, 'try-error')) {
  # keep only those pedons with real coordinates
  good.idx <- which(!is.na(s$x))
  s <- s[good.idx, ]
  
  ## this is not universally appropriate!
  # assume missing is NAD83 
  s$horizdatnm[is.na(s$horizdatnm)] <- 'NAD83'
  
  # check: OK
  table(s$horizdatnm, useNA='always')
  
  # convert to NAD83
  old.coords <- cbind(s$x, s$y)
  
    if(nrow(s)) {
      # add temp column for projection information, and fill with proj4 style info
      s$proj4 <- rep(NA, times=nrow(s))
      s$proj4 <- paste('+proj=longlat +datum=', s$horizdatnm, sep='')
      
      # iterate over pedons, and convert to WGS84
      new.coords <- ddply(s, 'siteiid', 
        .progress='text', .fun=function(i) {
          coordinates(i) <- ~ x + y
          proj4string(i) <- CRS(i$proj4)
          i.t <- spTransform(i, CRS('+proj=longlat +datum=WGS84'))
          i.c <- as.matrix(coordinates(i.t))
          return(data.frame(x.new=i.c[, 1], y.new=i.c[, 2]))
        })
      
      # merge in new coordinates
      s <- join(s, new.coords)
      
      # any changes?
      summary(sqrt(apply((s[, c('x', 'y')] - s[, c('x.new', 'y.new')])^2, 1, sum)))
      
      # save to update file for use with "Import of Standard WGS84 Georeference" calculation 
      # in NASIS note that this defines the coordinate source as "GPS", hence the last 
      # column of '1's.
      std.coordinates.update.data <- unique(cbind(s[, c('siteiid', 'y.new', 'x.new')], 1))
      # save to file
      write.table(std.coordinates.update.data, 
                  file='c:/data/sgeoref.txt', col.names=FALSE, 
                  row.names=FALSE, sep='|')
    }
}}
# }