Welcome to the home page for the NIWA QGIS User Group. This is a publicly readable web page hosted by NIWA to support users of QGIS, particularly within NIWA, but any QGIS user is welcome!
Why are we here? Based on the understanding that the benefits from any Open Data initiative revolve around data mash-ups and re-use, providing access to a tool allowing people (including NIWA staff) to use all this free environmental data is an important part of any such initiative. QGIS is a core part of NIWA's information delivery strategy - for NIWA staff as well many of our other clients.
Much like the development of easily used and affordable word processing & spreadsheet software for personal computers enabled pretty much anyone to carry out what used to be specialised tasks, freely available desktop mapping and GIS software are enabling their democratisation and widespread general use. Note that we do not envisage QGIS as necessarily meeting all the needs of all GIS users, but NIWA and many other agencies in New Zealand and globally, are adopting tools like QGIS to enable more widespread use of institutional GIS resources, without the traditional expense associated with commercial GIS software.
So, here we are!Time for first meeting:
A new NIWA year begins, mid-2017...
With the new NIWA financial year starting in July, staff training clicks over another year. Several NIWA staff have identified QGIS and Postgres (with Postgis) as subjects they'd like to learn about.
My request for NIWA Wellington people to get in touch about these yielded the not unexpected result - different people wanting different things... Some want to start at a simple beginning, others have a more complex and detailed requirement... so I'm looking at holding several topic focused seminars, which one or more people can attend, and learn the bits that are relevant for them. Sort of like the local NIWA R-users group seminars organised by Andy McKenzie, but more interactive, so people can try what is being discussed. These will be held at NIWA and directed at NIWA staff, but if numbers permit, open to others to attend as well.
I think it is worth noting that staff also asked for generic GIS and also ArcGIS training. If we look at the common definitions of "doing GIS", it includes managing, querying, visualising, analysing, mapping and reporting on spatial data. This implies that GIS in NIWA includes all the tools staff use to do these activities, rather than just the tools that call themselves "GIS", which includes includes tools like R, Matlab, Python and IDL, as well as ArcMap, QGIS, Mapinfo, GMT, etc. I'll expand on this because I think it is important within NIWA.
NIWA one GIS (see: https://one.niwa.co.nz/display/GIS/one.NIWA+GIS+datasets)comprises an ESRI ArcServer setup, providing data for NIWA ArcMap users, primarily datasets (map layers or feature classes) of wide relevance to NIWA staff. Enter the OGC, and GDAL. NIWA is a member of the Open Geospatial Consortium, an international organisation which defines standards enabling data interoperability and reuse in the geospatial domain. GDAL is an open source library used for accessing many different formats of spatial data. Where these come together, is a couple of OGC standards WMS & WFS (Web Map Service and Web Feature Service) which GDAL supports. So if NIWA one GIS provides compatible WMS & WFS services of the data layers managed there, not only ArcGIS users can access them, but other NIWA GIS users can also. QGIS natively supports both, so QGIS users will be able to. There is also rgdal for R users, mexgdal for Matlab users, a GDAL Python bridge for IDL users, and Python GDAL/OGR tools supporting Python users. So the potential exists to have one NIWA GIS to provide spatial data to virtually everyone in NIWA doing GIS, irrespective of the tool they use, thanks to open source and open standards. Watch this space!!
One of the advantages of QGIS, is that by design it has always supported a high level of integration. It does not pretend to provide spatial data management capabilities, instead it tries to bring a range of spatial tools (Postgis, SAGA, GRASS, R, Python and others) together in a common framework, working directly with your existing spatial data, wherever and however it is currently managed.. In NIWA QGIS is used to directly access, query and map Specify data from the NIC stored in a non-spatial MySQL database, fisheries data from NIWA's research trawl database, remote sensing netCDF data, etc... so for people who prefer a tool that accesses and integrates well with existing data, I suggest QGIS is a good start, and is likely to meet all your needs. For R and Python users, QGIS has been well integrated with these almost since it first started being developed, and as another Open Source project, shares many libraries with these and other tools (in addition to GDAL), meaning the learning curve may well be simpler for those already familiar with some of the other tools.
One example of effective integration is Postgres, the open source relational database (with Postgis to manage, query and analyse spatial data). R is one of the programming language that can be used to write Postgres functions, so the result of an SQL query can be an R-rendered graphic representing the data, rather than just the data. Or an R user can easily access data from Postgres databases copied directly into their local R workspace, and QGIS supports embedded R functions as well as Postgres connectivity. Recent training workshops held overseas have included Postgres, QGIS and R as 3 components of an integrated suite, which is a useful approach for NIWA staff.
2014 report comparing ArcGIS with QGIS
For a formal comparison between ArcGIS and QGIS click here.
This study was undertaken to assess the implications of migrating a specific existing ESRI implementation to QGIS. As such,it compares the capabilities of QGIS compared with existing workflows developed over time around an ESRI installation. For those considering implementing a new GIS system, many of the compatibility issues are likely to be largely irrelevant, as are some other issues (and costs) such as data migration.
This approach obviously highlights the inability of QGIS to work with ESRI proprietary formats, and does not always investigate how a task may be accomplished with QGIS, but undertaken differently from the ESRI approach, although some such situations are covered.
It does compare some advanced analytical capabilities, and in some cases considers the use of plugins & the ability of QGIS to utilise other applications (notably GRASS. SAGA, GDAL and TauDEM) to undertake geoprocessing tasks which QGIS does not support natively.
It mentions the combination of QGIS/Postgis/Geoserver as a better comparison with ARC Server, but does not really consider other open source applications which can also be used to build a more complete open source GIS suite, such as Geonetwork for metadata manangement, or commercial tools like Geocat Bridge to enable a higher level of interoperability between ESRI and the open source/open standards based tools. The ability of Arc GIS to share a native Postgis datastore with QGIS is not described, and some approaches which might use Arc as a central server with desktop access for users via QGIS in a mixed model are also not investigated in any great depth, although the possibility is mentioned.
The report does generally describe the limitations of what it covers, and provides a useful comparison.
Accessing MPI research trawl data with QGIS
Abstract: NIWA manages several research databases for MPI Fisheries, which QGIS can be used to access. This demonstration will show how QGIS can be used to access & display research trawl survey data, eg:
These data can be overlaid with topo maps or marine charts, freely downloadable from LINZ.
Anyone familiar with the trawl data, stratified surveys or pretty much any species observation/distribution data should find this useful and relatively easy. The trawl database has several decades of species catch data, which can be accessed and viewed.
An additional feature is the use of the QGIS Action tool (originally developed by Gavin Macaulay of NIWA) to retrieve catch data from the database by clicking on a station on the map - this is particularly useful as it allows users to retrieve non-spatial data reference to a point on a map - the catch data (and underlying catch database table) contains no position data, but can still be retrieved in QGIS.
The demonstration is based around this pdf document - a How-To guide to access research trawl data.
Click to view for a more detailed view of Landcare Research's freely available NZ basemap! (internet mapping with QGIS)
Please feel free to add comments & suggestions.
Questions can go here, but the mailing list is preferable.
If anyone wants to help manage these wiki pages, please let me know!!!
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