thelist: TheList

In AustralianAntarcticDivision/raadfiles: File Database Management for 'raadtools'

TheList

Description

Local authority spatial data in Tasmania.

Usage

thelist_files(
  format = c("gdb", "tab", "shp", "asc", "xml", "lyr", "dbf", "zip", "all"),
  pattern = NULL
)

Arguments

format	is used to targe tspecific formats see Details
pattern	is used to string match generally, if this is not NULL then format is ignored

Details

TheList.tas.gov.au is the standard local mapping authority in Tasmania, it was recently upgraded and works very well, and most of the data including newish LiDAR is available within the opendata tree. Also check out tasmap.org for an alternative interface with access to the same services.

These files are broken into sub-regions, administrative areas within the state of Tasmania. At time of checking there were 19 sub-regions, and 544 or so layers (type within format) and 37,616 total files. GDB detection is different to the other more definite formats so the file sets won't be analogous atm. There are Climate Futures Australia (CFA) layer indexes in here as well, it's on the todo list to build a comprehensive index (or access one).

The scheme uses the Map Grid of Australia 1994 (MGA94) on the Geocentric Datum of Australia 1994 (GDA94), an implementation of UTM Zone 55. GDA94 was rolled out in Australia in the early 2000s, Tasmania kept the old UTM scheme (it was AMG66, AGD66) but around the same time Victoria used the opportunity to move to a single-projection for the entire state, to avoid having to switch between zones. NSW took much longer to modernize and standardize around GDA94 and they stumbled forward with their three UTM zones (54, 55, 56), and while Tasmania did it quickly we only have the one zone (no one thought much about Macquarie Island) and Victoria did it more cleverly. I'm not sure how Queensland went, they were adding properties and roads at a very scary rate so probably took much longer than us. The software back then could only just handle an entire city worth of vector roads and cadastre, so experience with higher abstractions was pretty rare. As a nation, we could probably never have agreed on a national LCC projection given that the states had so much mess to sort out themselves, but that's what you see in the USA with its Albers family, and the elided Hawaii and and Alaskan montsrosities . During the time GDA94 was being rolled out the addressing system was being standardized for GPS and modern communication systems, the P-NAF was the original project that took the data from Australia Post. State of the art for address parsing in 2002 was Perl, Google Earth was but a keyhole glimmering in the background in early West Wing episodes, and the idea of "micro-services" was catching on among the venture capital elite. Today the echoes of Oracle and ESRI and RP-Data and ENVI and are still with us.

It was around this time that the large players made their mark in Australia (mid-1990s-early 2000s), MapInfo had a tight hold on many local government authorities (LGAs) because they had the best software, the best formats (TAB, MIF and georeferenced tile TAB for imagery), and somehow got integrated into many state departments. That's why these TAB and MIF formats are here still, shp was the poor interchange cousin, limited to DBF, short field names, no data above the 32-bit index limit, no mixed topologies in a single layer. Aerial imagery was just starting to make an impact and the future business and research interests being recognized. MrSID and ECW were used to integrate large imagery collections into single files and services, while their parent companies waged a furious legal battle around wavelet compression. LizardTech has mostly faded from the scene, but NearMap continues today with "reality as a service", they certainly had the long-game in mind this whole time.

Manifold was in version 5.0 in 2002, and it could read all of these formats as well as provide very accessible rendering, ability to create tiles with links betweeen drawings and images for creating tile sets. ECW was absolutely hot, and ERMapper (Nearmap) had a free viewer that is probably still the best one around until leaflet happened. The point of this long story was to explain that in the early 2000s these files were LARGE and no one had a hope of reading a road line, cadastral parcel, or even address point shapefile for an entire state. We read them in parts, and in pairs or more of parts while we slowly rendered our way around the country building map tile sets deprecated immediately when Google Earth arrived. These days it's a pain to get the file list into one object so you lapply it with the latest R GIS i/o package, but there's really no problem with memory.

This function is here to make it easy to get the file list for Tasmania.

tab, gdb, shp is sf/rgdal ready - gdb works with the directory name, it might work with some of the individual files - I don't know how GDAL otherwise resolves layer names in the same folder but you can give it the path name, this is probably why gdb/, though note that for raster /anything-next-to.adf does work

all will give every thelist file

tab is that glorious ancient format

gdb is a newcomer format, recently reverse engineered by Even

shp is the usual suspect

dbf is the usual suspect's data (ggplot2 calls this metadata)

asc is DEM e.g. list_dem_25m_break_o_day.asc (part of a statewide effort in the early 2000s to build a DEM for Tasmania, it was used to build a networked drainage and topography graph of the state's physical landscape, and this helped spur the development of a powerful imagery orthorectification system and led to some interesting commerical initiatives in general geospatial data)

csv is something else e.g. list_fmp_data.csv

xml,txt is probably just xml, probably only relevant to GDAL and ESRI list_fmp_data_statewide.txt.xml

lyr - style files?

zip - unpackage zips

Arguments are used to pattern match on different aspects of the file name so that anything can be pulled out.

Value

tibble data frame of file names

Examples

## Not run: 
  thelist_files()

  ## to get statewide sets, find the individual groups first and pick one
  grps <- raadfiles:::thelist_groups()
  print(grps)
  #read_all <- function(pattern) {
  #files <- thelist_files(format = "shp", pattern = pattern)
  #do.call(rbind, lapply(files$fullname,  sf::read_sf))
  #}
  #x <- read_all(sample(grps, 1))

## End(Not run)

AustralianAntarcticDivision/raadfiles documentation built on Dec. 20, 2024, 11:06 p.m.