This plugin provided by OpenPlanetary allow us to access various basemaps of Mars and The Moon. To explore its functionalities install the plugin in QGIS via the Plugins Manager.

Once installed, the OpenPlanetary Tile Loader icon is displayed in the Plugins Toolbar, as illustrated in the picture below:

Once opened, you can add Mars and Moon basemaps into your QGIS Project.

Let’s add the Mars Colour MOLA elevation basemap into our project.

Mars Shaded Grayscale MOLA Elevation

OPM Mars Basemap v0.2

In this way, we can get much closer to the surface of these celestial bodies and learn a lot more about them.

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Sources: 

Original post: Nuevo “plugin” de QGIS: “OpenPlanetary Tile Loader” – https://www.cursosgis.com/nuevo-plugin-de-qgis-openplanetary-tile-loader/

OpenPlanetary Tile Loader plugin – https://plugins.qgis.org/plugins/optileloader/

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First of all, open the QGIS software and install the QuickMapServices plugin by going to the Plugins menu toolbar > Manage and Install plugins. The QGIS Plugins manager opens.

Type “QuickMapServices” in the search box and proceed by installing the plugin.

Once installed, an icon should appear in the Web Toolbar, as demonstrated in the image below:

When we click on this icon, we will see that we are limited to only NASA and OpenStreetMap basemaps. However, we can work this out by selecting the Settings option from this menu.

In the new window that will open, go to the “More services” tab and click on the Get contributed pack. This will add new services/basemaps to your QuickMapServices Plugin.

As a result, we have a list of 14 providers who offer a variety of services/basemaps.

Let’s explore the main basemaps available here.

• The ESRI package is one of the most comprehensive, with 15 available basemaps to add.

• The Google package includes some well-known options.

• In addition, the OSM package includes some interesting options.

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Sources: 

Original post: Quick Map Services: un plugin de uso sencillo para utilizar mapas base en QGIS
– https://www.cursosgis.com/quick-map-services-un-plugin-de-uso-sencillo-para-utilizar-mapas-base-en-qgis/

QuickMapServices plugin – https://plugins.qgis.org/plugins/quick_map_services/ 

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One of these is the “Globe Builder,” plugin, which can add a globe to your map or layout. The plugin can be installed easily by going yo to the Manage and Install Plugins (under the Plugins menu toolbar).

Once installed, you can open the plugin by going to the the Plugins menu toolbar. By clicking on the Build Globe view, a new window will open. It is preferable to maximize it.

In this Globe Builder new window select: data sources according to your preferences, the projection, and the coordinates based on which the Globe will be centered. Following these steps, you can add the Globe to a Map or to a Layout.

If you prefer to change the globe appearance, you can change the settings in the Visualization section (in the same Globe Builder plugin window).

The globe added to a map.

The globe added to a layout.

If you want to learn more about how to use QGIS, TYC GIS offers a variety of training courses at varying levels of difficulty, which are almost certainly relevant to your interests.

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The QGIS OSMDownloader plugin lets you download OSM data while preserving the symbology.

To be able to do that, we first need to install the OSMDownloader plugin.

After the plugin is installed, we can go and activate and deactivate the OSMDownloader toolbar.

Next, with the Download OSM data by rectangle selection button (located in the OSMDownloader plugin toolbar), draw a rectangle over the area of interest to load downloaded *.osm files as QGIS layers.

The OSMDownloader dialog box appears. Specify a location on your computer to save the .osm file.

Click Ok. Depending on the size of the rectangle you drew, the download will take some time. When the download is complete, a Success, the file has been downloaded will pop up.

Now you can see the downloaded files in the Layers Panel as well.

Click Ok. Turn off/deactivate the OpenStreetMap basemap and zoom out slightly.

The OSM layers that are available within the drawn rectangle have now been downloaded to your computer. The OSM symbology is preserved in the layers.

By inspecting their symbology, we can manage the OSM symbology and perform various operations such as changes to the adopted styles, style export, and so on.

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Sources: 

Original post: Descarga de datos de OpenStreetMap (OSM) con simbología en QGIS – https://www.cursosgis.com/descarga-de-datos-de-openstreetmap-osm-con-simbologia-en-qgis/ 

OSMDownloader plugin – https://plugins.qgis.org/plugins/OSMDownloader/ 

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PEARL is a platform developed by “Development Seed” that make use of AI to quickly and effectively run LULC mapping workflows.

As a user you can access the platform for free and see how it works. In order to explore its capabilities we need to register first. To do that, press the Sign Up to Start Mapping and fill in the information required.

Once your account is created and you managed to log in, click on the Launch App button.

Now we can start exploring the application, first we need to give a name to our project.

Once the project is created, we have to draw an area of interest in the map or just upload a GeoJSON file that capture our area of interest (AOI).

Please note that you can only work in certain areas (located in the United States) and the area of interest (AOI) is limited to 100 square kilometres. We will zoom in to an AOI next to the city of Baltimore. Using the Draw area of interest button sketch an area below 100 square kilometres.

Next, go and select a Starter Model. In this screen display you can find more information about the data used by the model, class distribution, training areas, etc.

Once the model is selected, click on Ready for prediction run. Now wait until the predictions are ready and the LULC map for your AOI is generated.

By going to the Refine Results you can refine your results.

Also, by selecting the Export button we can export and download the LULC map on our computer (.tiff format) and use it in QGIS (for example).

PEARL is an easy way to get  LULC data for your projects.

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Original post: PEARL: plataforma que cartografía la cobertura terrestre a través de Inteligencia Artificial – https://www.cursosteledeteccion.com/pearl-plataforma-que-cartografia-la-cobertura-terrestre-a-traves-de-inteligencia-artificial/

PEARL Planetary Computer Land Cover Mapping – https://www.landcover.io/about#guide-models

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With the QGIS Coregistration plugin you can ensure the spatial alignment of all your data in a easy and faster way.

In the example below we have two satellite images (Sentinel-1 and Sentinel-2) which depict a flood event in two different days. The images are acquired by two different sensors and also have different spatial resolution (pixel size).

STEP 1: Open QGIS and install the Coregistration plugin.

Step 2: Go to the Processing Plugin, and from the Coregistration Drop down menu, select the Basic Pixel alignment.

This Qgis algorithm generates a new raster file base on the target image with all properties from the reference image. This process don’t check the content of the pixel, this process adjusts the target image to the closest pixel alignment based on the reference image. The basic pixel alignment process include:

– Reprojection (only if needed)

– Resampling (only if pixel sizes are different)

– Extent/bounds adjustment

Click Ok.

The Sentinel-2 image is now pixel aligned with the Sentinel-1 image.

The Sentinel-2 image was resampled according to Sentinel-1 spatial resolution and adjusted to the same size/extend.

Source: Coregistration plugin – author: Xavier Corredor Llano, SMByC, https://plugins.qgis.org/plugins/Coregistration/. 

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Well, it is a thematic map (a map that illustrate the pattern of a particular variable/subject in a geographic area), in which the geographic areas are altered/twisted out of real shape, in a direct proportional way to the values associated with the variable.

A cartogram or anamorphic map focus therefore on size to efficiently differentiate the spatial distribution of the variable being mapped. The main advantage of these types of maps is that they offer a more intuitive cartographic design and data visualization.

In this tutorial we will find out how to create a cartogram or anamorphic map in QGIS.

Step 1: Open QGIS and install the cartogram3 plugin. This plugin creates continous cartograms (a.k.a. anamorphic maps) from polygon layers.

You can find more information about this pugin here: https://github.com/austromorph/cartogram3

The catrogram3 icon will be added in the QGIS Plugins toolbar.

Step 2: Before opening the cartogram3 plugin, make sure you load into QGIS map canvas a polygon dataset which holds a value for a the variable we want to map.

In this tutorial, to create a cartogram or anamorphic map we will use as mapping variable the population number of the African Continent countries.

Step 3: Start the cartogram3 plugin.

• Select the layer for which you want to compute the cartogram/anamorphic map.
• Select the Field where the population number is stored. In our case the pop_est.
• In the Stop Conditions select when the calculations will stop.

The cartogram/amanorphic map is computed. Now we can have a better perspective over the distribution of the population within the African continent.

In the before and after image below, you can have a better perspective on how the geographic areas (countries administrative units) were altered considering the population number in each country.

In the same time you can easily identify which are the largest countries in terms of population number.

SOURCE:

cartogram3 plugin – Author Christoph Fink – https://plugins.qgis.org/plugins/cartogram3/

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Maybe you want to divide raster files into equal parts, or maybe you want to split them based on a given polygon shapefile layer.

Using the Raster Divider and Easy Raster Splitter plugins in QGIS 3.x you can realize this in a easy way. Lets see how you can do it.

1. Raster Divider

First of all the Raster Divider plugin must be installed. For this, go to Plugins > Manage and Install Plugins. Install Raster Divider.

The Raster Divider plugin icon will appear in the QGIS toolbar. Click on it.

In the new window that will open select

• the raster you want to divide,
• the size of the equally divided parts (considering the original raster size) and the
• output folder where the equally divided parts will be exported.

Optionally you can choose to add the results in the map by checking the Add result to map checkbox.

Click Ok.

After the process is complete, all the divided parts will appear in the Layers panel.

Deselect several divided parts found in the Layers panel so you can understand better how this tool works.

The raster was divided in 110 equally parts (4000 x 3000 px).

2. Easy Raster Splitter

Using this plugin you can split your raster file based on a given polygon shapefile layer. In this way it is possible to clip or extract raster parts based on different limits/areas of interest.

Before starting using this plugin, you must install it. In the same way as earlier, go to Plugins > Manage and Install plugins. Install Easy Raster Splitter.

The Easy Raster Splitter button will be added to the QGIS toolbar. Click on it. In the new window that will appear select:

• the raster you want to split 
• the vector layer on which the split will be based
• the method (Clip or Extract). In order to clip the raster considering the limits showed in the image below select Clip. 
• the split option (Split by Feature of Full Vector). Choose Split by Feature and select the raster output name of the new rasters. Choose a field found in the vector layer attribute table. 
• output folder for the split parts

The raster will be clipped in 7 parts accourding to the LIMITS.shp layer.

Remove the raster background black color by going to raster/Layer Proprieties > Transparency > and type 0 in the Additional no data value option.

Click Ok.

The original raster is now clipped considering the 7 areas found within the LIMITS.shp layer.

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SOURCE:

Raster Divider Plugin – Author: Murat Çalışkan – https://plugins.qgis.org/plugins/raster_divider/

Easy Raster Splitter Plugin – Author: Murat Çalışkan – https://plugins.qgis.org/plugins/easy_raster_splitter/ 

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TL; DR, the solution

We will arrive to the solution after taking two simple steps. The first step will be creating a VRT file. A VRT file is a Virtual Dataset that contains all of the images merged. Second and final step will be just to have that file translated to the desired extension.

vrt_path = os.path.join(BASE_PATH, 'prov_vrt.vrt')
vrt = gdal.BuildVRT(vrt_path, list)

result = os.path.join(BASE_PATH, 'merged.tif')
gdal.Translate(result, vrt, format='GTiff')

Here the variable list is a list composed of the path of each and every file we want to merge. This is important, don’t rush with the copypasting or you will get an error.

Complete solution

If you are starting from scratch you will have to import the libraries os and pathlib. They will help us explore folders and files with ease.

In this code glob will help us filter the files in the folder to only those with the extension TIF.

from pathlib import Path
from osgeo import gdal
import os

folder_path = r"C:\Users\Usuario\Desktop\input"
BASE_PATH = os.path.dirname(os.path.abspath(folder_path))
folder = Path(folder_path)

l = []

for f in folder.glob('**/*.tif'):
    f_path = f.as_posix()
    l.append(f_path)

vrt_path = os.path.join(BASE_PATH, 'prov_vrt.vrt')
vrt = gdal.BuildVRT(vrt_path, l)

result = os.path.join(BASE_PATH, 'merged.tif')
gdal.Translate(result, vrt, format='GTiff')

The processing script found in the toolbox as well as the use of gdal_merge imply that every image to be merged has to be loaded previously in memory. The code above bypasses this step, thus avoiding all the problems related to lack of memory.

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First of all, you need to have the QGIS software installed on your computer. After this you can install the Semi-Automatic Classification plugin using the Manage and Install Plugins option.

The Semi-Automatic Classification Plugin will be installed. Two toolbars and a Panel will be added to your QGIS Graphical Interface. You can find more information about this by reading the User Manual of the Semi-Automatic Classification Plugin.

In this exercise we will use the Working Toolbar from where we can access the Main Interface Window.

The Main Interface Window is composed of several tabs. We will go and click on Download Products. But in order to be able to download products we need to provide some Login credentials.

Next, go to the Login data sub-tab. Here you will need to fill in the login information (depending on what kind of data you want to download).

For example if you want to download Sentinel 2 satellite images you will need to fill in the Copernicus Open Access Hub credentials – https://scihub.copernicus.eu/dhus/#/home.

If you do not have an account you need to create it. After this step is completed, go to Search sub-tab. Meanwhile in the QGIS map canvas, add the OpenStreetMap Basemap. If you encounter difficulties in adding the OpenStreetMap Basemap you can find some information here – https://www.giscourse.com/how-to-add-openstreetmap-basemaps-in-qgis-3-0/.

You can add the OpenStreetMap in the map using the OpenStreetMap button in the Semi-Automatic Classification Plugin window.

After the Basemap is added, in the Search sub-tab, go to the Set Area in the map button (red cross on a orange background) and select an area of interest in the map. Use the left click and then the right click to draw a rectangle.

We will download a Sentinel 2 image around the city of Lisabona, Portugal. After the rectangle is drawn, select the time interval you are interested in and click on Find button.

In the Product List, all the available images, form the period of time selected will appear. Next, we will select the image which suits us and Click on Run. But before that, make sure you check the

• Preprocess images (checking this box will end up in converting the data to surface reflectance). More information can be found in the Semi-Automatic Classification Plugin user manual (page 146) – https://readthedocs.org/projects/semiautomaticclassificationmanual/downloads/pdf/latest/.
• Load bands in QGIS

Now, you can click on Run. Select a folder to download the image and click Select Folder.

The download will start. If your download will not start keep trying until it starts.

After the download is complete, all the Sentinel 2 bands will appear also in the Layers Panel.

Next, we will create a virtual raster (a mosaic of the list of input GDAL-supported rasters). This means that we will merge all the bands to a single raster (which will be considered a multiband raster).

Go to Raster > Miscellaneous > Build Virtual Raster….

In the new window, in the Input Layers, select only the bands that have a 10 m Spatial Resolution (band 2 – blue, 3 – green, 4 – red and 8 – NIR). For more information about Sentinel 2 bands and their spatial resolution check the next link https://en.wikipedia.org/wiki/Sentinel-2. 

Select a new name and location for your new mosaic. Click Run.

Open a new QGIS project and add the newly created raster. Symbolize it as: Render type – Multiband color (RGB – red – green – blue) – (Red Band – Band 3; Green Band – Band 2; Blue Band – Band 1). This is also called Natural Colour Composite.

You can change the color composite to a false one (NIR – red – green). In the Layer Proprieties window will be (Red Band – Band 8 NIR; Green Band – Band 3 Red; Blue Band – Band 2 Green).

Source: Congedo Luca (2016). Semi-Automatic Classification Plugin Documentation. DOI: http://dx.doi.org/10.13140/RG.2.2.29474.02242/1

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