The sample data provided with the Training Manual refers to the town of Swellendam and its surroundings. Swellendam is located about 2 hours’ east of Cape Town in the Western Cape of South Africa. The dataset contains feature names in both English and Afrikaans.
誰で無理なくこのデータセットを使用できますが、自分の国や故郷からのデータを使用することを好む方もいるかもしれません。そうすることを選択した場合は、ローカライズされたデータが、モジュール3からモジュール7.2のすべてのレッスンで使用されます。それ以降のモジュールはより複雑なデータソースを使用しており、お住まいの地域ではご使用になれない場合があります。
ノート
このプロセスはコース召集者、または、それらのコースのためにローカライズされたサンプル・データセットをつくりたいより経験あるQGISユーザー向けにしました。デフォルトのデータセットはトレーニングマニュアルとともに提供されていますが、デフォルトのデータセットを置き換えたい場合は、これらの指示に従うことができます。
ノート
The sample data used throughout the manual can be downloaded here: https://github.com/qgis/QGIS-Training-Data/archive/QGIS-Training-Data-v1.0.zip. You can save the files in a folder named exercise_data.
ノート
以下の手順では、QGISの十分な知識を持っており、教材として使用されることを意図していないと仮定します。
デフォルトのデータセットをコースのためのローカライズされたデータに置き換えたい場合、QGISに組み込まれたツールを使って簡単に行うことができます。あなたが使おうとする領域は、都市部と農村部の適当な混合地であり、河川や水面、道路、地域の境界(自然保護区や農場など)などが分かれてる必要があります。
QGISプロジェクトを開く
This will load three layers into your map which relate to OSM’s naming conventions (you may need to Zoom Full to see the vector data).
We need to extract the useful data from these layers, rename them and create corresponding shape files:
This layer contains three fields whose data we will need to extract for use throughout the Training Manual:
You can sample the data your region contains in order to see what kind of results your region will yield. If you find that “landuse” returns no results, then feel free to exclude it.
You’ll need to write filter expressions for each field to extract the data we need. We’ll use the “building” field as an example here:
We now need to save the resulting data as a shapefile for you to use during your course:
Once the buildings layer has been added to the map, you can repeat the process for the natural and landuse fields using the following expressions:
ノート
Make sure you clear the previous filter (via the Layer properties dialog) from the multipolygons layer before proceeding with the next filter expression!
Each resulting data set should be saved in the “epsg4326” directory in your new exercise_data directory (i.e. “water”, “landuse”).
You should then extract and save the following fields from the lines and points layers to their corresponding directories:
Once you have finished extracting the above data, you can remove the multipolygons, lines and points layers.
You should now have a map which looks something like this (the symbology will certainly be very different, but that is fine):
The important thing is that you have 6 layers matching those shown above and that all those layers have some data.
The last step is to create a spatiallite file from the landuse layer for use during the course:
For Module 6 (Creating Vector Data) and Module 8 (Rasters), you’ll also need raster images (SRTM DEM) which cover the region you have selected for your course.
CGIAR-CGI ( http://srtm.csi.cgiar.org/ ) ではいくつか SRTM DEM を提供しており、 http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp からダウンロードできます。
You’ll need images which cover the entire region you have chosen to use. If you kept same data as the training manual, you can use the extent shown in the figure_set_osm_region figure above, otherwise adapt your extent. Keep the GeoTiff format. Once the form is filled, click on the Click here to Begin Search >> button and download the file(s).
必要なファイルをダウンロードしたら、それらを raster/SRTM サブフォルダの下の exercise_data ディレクトリに保存する必要があります。
In Module 6, Lesson 1.2 shows close-up images of three school sports fields which students are asked to digitize. You’ll therefore need to reproduce these images using your new SRTM DEM tiff file(s). There is no obligation to use school sports fields: any three school land-use types can be used (e.g. different school buildings, playgrounds or car parks).
For reference, the images in the example data are:
Having created your localised dataset, the final step is to replace the tokens in the conf.py file so that the appropriate names will appear in your localised version of the Training Manual.
置き換える必要のあるトークンは次のとおりです: