Qgis Training Manual

[Gaja Starks]

Hithere!I thank you all for doing massive work in educating and instructing us. I am a new user of this OSM and a big admirer of GIS. I am trying to mentor myself on GIS and I downloaded QGIS training manual only to find OSM used as a source of streets and places datasets. My question is, how do i download datasets of a specified place? Let say I want to download a place like Serengeti National Park in Tanzania.

Other ways to get OSM data is to download OSM extracts, filter it using osmosis and import it as shapefile, geoJSON, ... . For first testing purpose you might be already happy by using the Overpass API for getting small areas with the objects you are interested in. Or you get shapefile for example from Geofabrik.

BUT as you will find out the OSM model isn't designed for a specific purpose (rendering, queries, routing, geocoding, ...) but is an intermediate format that is build to allow easy modelling/tagging of all kind of real world features with geolocation.

So you will need to transform the OSM representation of objects into a style that assists you on your workflow.

For your scenario this mean that you might merge OSM ways with same name into one roadnetwork and create an intelligent filter to unite places modelled as node with place=* tag and ones modelled as boundary relation.

The PyQGIS Cookbook is a great source of information, not only for PyQGIS beginners or plugin developers, but also for C++ developers: it contains a lot of information about the internals of the QGIS API that you cannot really find anywhere else.

The answers to the first question show that the top three first sources of information on how to use QGIS features or solve problems are: 1. search engines, 2. Stack Exchange, and 3. the QGIS User Manual:

This has been a really important infrastructure project for QGIS that has been made possible by support from our donors and sponsors, as well as the generous in-kind contributions of our community members.

As an experienced QGIS user you currently have two main resources: The QGIS manual and the QGIS training manual. In this call we focus on the manual, which is already an excellent resource on available functionality in QGIS.

We would love to see the QGIS manual providing a readable narrative explaining the purpose (with images and illustrations if needed) of each feature. It can also provide short sample snippet where useful, which in many cases you can simply cut and paste into your code and then tweak to get started.

During the Zurich QGIS hackfest we had some extended discussions about migrating our documentation away from LaTeX to sphinx because the latter offers a more approachable syntax for casual documentation writers and has good support for internationalisation via gettext. This week I am going to our first 2012 QGIS hackfest (to be held in Lyon,... Read more

SkyEye was awarded a contract to offer Training and Update the QGIS Manual for Ministry of Natural Resources and Environments, Water Resources Division. It was funded by the Economic-Wide Integration of Climate Change Adaptation and Disaster Risk Reduction to Reduce Climate Change of Communities in Samoa (EWACC).This training went for a span of 2 weeks in which participants from the Water Resource Division and fellow partners were in attendance. SkyEye was tasked with reviewing the previous Manual created by Stuart Young in 2017 and update material; and also offer new possible workflows for the benefit of the Water Resource Division.

In addition to the original topics in the 2017 Training Manual Version, SkyEye added new intermediate and advanced topics in QGIS, GIS and Remote Sensing were also included in the manual with specific use cases requested by the MNRE WRD and other participants. In particular, newer methods for collecting GIS data, identifying water resource restricted areas, land cover areas within catchment areas, catchment and water network delineation, automatic map layouts and 3d visualisation.

QGIS is a free GIS program. It is open source and completely free to use. See the QGIS website here. If you like what you've seen here and would like me to run a training course, get in touch! I run both face-to-face and online training and the content can be modified to suit your requirements.

I have been using QGIS for a number of years now and now use it almost exclusively in my consulting work. I was a MapInfo-Discover user for about 20 years but have now moved exclusively to using QGIS. QGIS has developed significantly over the past few years and now is a viable alternative to the commercially available GIS packages.

I have been running QGIS training courses for geologists over the past few years for the Australian Institute of Geoscientists (AIG) and other organisations. As a spin-off of these training courses is that I had compiled a user manual for geologists and geoscientists. This is freely available in PDF and HTML formats at this web link, please feel free to share. The manual contains information that is not easily located on the web such as plotting rotated structure symbols and using USGS symbols and geological pattern fills. Other sections cover the import and display of geochemical and geophysical data and the selection and processing of remote sensing data such as ASTER and Sentinel 2 images.

One of the strengths of QGIS is the ability to utilise external font styles and patterns. Geological symbols and pattern fills from the USGS have been converted to SVG (scaled vector graphics) files. A full description of the USGS patterns and symbols can be found here.

I have created a series of print layout templates for A0, A1, A2, A3 and A4 in landscape and portrait orientations and these can be downloaded from here.I have created this page with information on SVG (scaled vector graphics) files and their use in QGIS.

It is possible to install the SCP using the official repository.This repository allows for the installation of the latest version of SCP (master), in some cases also before the availability thereof in the QGIS repository.Therefore, this can be useful if you need a fix or a new function that is still not available in the QGIS repository.Moreover, the master version in the SCP repository can be installed along with the version available in the QGIS repository.

In general, it is preferable to avoid thermal infrared bands.If you are using Landsat 4, 5 or 7 you should select bands: 1, 2, 3, 4, 5, 7 avoiding band 6 that is thermal infrared; for Landsat 8 you should select bands: 2, 3, 4, 5, 6, 7.Landsat 8 band 1 is generally avoided because it is very similar to the blue band and it is mainly used for coastal aerosol study.Landsat thermal infrared band is excluded from classifications because values are mainly related to object temperature.

All Landsat 1,2, and 3 MSS and Landsat 4, 5, 7, and 8 images downloaded from and processed with the Level 1 Product Generation System (LPGS) can be converted to reflectance automatically by the SCP; products generated by the LPGS have a MTL file included that is required for the conversion.Since version 3.1.1 the SCP can also convert images from the Global Land Cover Facility (images available for free from ). In particular, images having an old format of the MTL file (or a .met file) can be processed through the automatic conversion to reflectance and the DOS correction. However, some images do not have the required information and cannot be processed. Also, notice that some images available from the Global Land Cover Facility are already converted to reflectance. For this process, image bands must be renamed in order to remove the final 0 if present (e.g. rename B10 to B1).

Yes, you can convert also images downloaded from the web (actually the conversion is recommended).You should move all the bands (.jp2 files) and if available the .xml file whose name contains MDT_SAFL1C in the same directory.Then select this directory in Sentinel-2 conversion.Images are converted to reflectance.

During the conversion to reflectance, pixels of 20m bands are split in 4 pixels of 10m whose values are the same as the original 20m pixel.The purpose of this operation is to allow for the calculation between all the bands, without changing original values.

Yes, you can clip the images before the conversion to reflectance and then copy the MTL file (contained in the Landsat dataset) inside the directory with the clipped bands.If you want to apply the DOS correction (which is an image based technique) you should convert the original Landsat bands (the entire image) and then clip the conversion output (i.e. bands converted to reflectance).

If you want to apply the DOS correction to an entire band which has NoData values (the black border with value = 0) then you have to check the checkbox Use NoData value and set the value to 0.This is because DOS is an image based technique, and NoData values must be excluded from the calculation.

Several materials have similar spectral signatures (e.g. soil and built-up, or forest and other types of dense low vegetation), which can cause classification errors if ROIs, and spectral signatures thereof, are not acquired correctly.In order to improve the results, you can try to collect more ROIs over these areas, in order to train the algorithm for these very similar areas, also, display the spectral signatures of these areas in Spectral Signature Plot to assess their similarity.You can also use a Signature threshold for these signatures in order to reduce the variability thereof (only pixels very similar to the input signatures will be classified).The Land Cover Signature Classification is also useful for classifying specific materials that can be spectrally similar to other ones.

Yes, it is possible if all the images have the same number of bands.However, if images are acquired in different months, land cover changes (especially of vegetation state) will affect the spectral signature (i.e. the same pixel has different spectral signature in different periods).Atmospheric effects could also affect the images differently.That could reduce classification accuracy.Therefore, it is suggested to collect always the ROIs and spectral signatures for every image.

3a8082e126