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/

The post “OpenPlanetary Tile Loader” QGIS plugin first appeared on GIS Course | TYC GIS Training.

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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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/ 

The post QuickMapServices Plugin – an easy way to add basemaps in QGIS first appeared on GIS Course | TYC GIS Training.

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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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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Sources: 

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

The post PEARL: ML and AI land cover mapping platform first appeared on GIS Course | TYC GIS Training.

To access this map you need to https://esa-worldcover.org/en.

Click on the EXPLORE button. The WorldCover Viewer will open.

On the left, under the layers panel you can see the viewer available datasets. Click on them to activate and deactivate them. Zoom in to an area of interest. 

In order to be able to download the products available, go to the DOWNLOAD button. This requires to log in. If you do not have an account yet, go to Register and create one.

Once logged in, the download can be done. Select the tile product of interest (or multiple products).

Click Next in the right lower corner. A new window will open.

Click Download. The download will take a while.

After the download is complete, you can use the newly downloaded files in your projects. You can open the files in any GIS software, like for example ArcGIS Pro.

Source: ESA – Worldwide land cover mapping – https://esa-worldcover.org/en

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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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The study of diseases

Epidemiology is the study of horizontal and vertical structure of disease infection, transmission, diffusion, magnitude, age group and sex of the diseases with reference to space and time. Geographical Information Systems have become increasingly relevant in the study of diseases for their ability to represent the spatial component. GIS offer an insight into the environmental causes and spatial trends of health-related events.

Use cases

The first time spatial information was used to study a pandemic goes back to 1854. The feat of Dr. John Snow is widely known. Dr. Snow was studying the 1854 outbreak of cholera as he began to map the cases on his neighbourhood. The map allowed him to discover that most cases appeared around a certain well. When the well was disabled the outbreak ended. That year 23000 people died due to cholera, the worst figure in the history of Great Britain. The fifth pandemic, in 1875, had less impact on the country due to improved water supplies and quarantine measures.

Another example of GIS being used in epidemiology is the case of Dengue. Countries like India have used this tool to monitor outbreaks of Dengue fever and control the disease. Mapping and detection of risk areas is a complex task that requires the assessment of multiple criteria.

The World Health Organization refers to GIS as valuable tools for assessing and managing epidemics. More recently, GIS helped officials in South Korea trace the disease and limit the spread by tracking down individuals who had been in contact with cases of corona virus. South Korea has been widely praised for his success in tackling the impact of the virus.

Final word

GIS was known to be useful for assessing environmental risks and for managing rescue operations after natural disasters. But previously we’ve shown they are of application in public health too. As the number of technologies associated with GIS grows the capabilities of GIS will grow too.

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Dr. John Snow (do not confuse it with the King beyond the wall) is considered to be the first to use typical Geographic Information Systems tools to analyze an emergency situation. The English doctor determined, after making a spatial analysis of the infection cases of cholera, that the cholera outbreak that occurred in London in 1854 was due to the spread through contaminated wells.

Before he created his revolutionary map, people believed that cholera spreads around by miasma in the air.

It is considered that this was the beginning of GIS in epidemiology. We encourage you to learn more about its history.

Following the outbreak of COVID-19 (a type of coronavirus originating from China in late 2019), numerous maps and web viewers that collect the state of the pandemic in real time have emerged. In this post we are going to show you some of them.

1. Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU)

LINK – https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html

One of the first web viewers developed as a result of the spread of COVID-19 and, perhaps, the most complete of all, is the one developed by the John Hopkins University in the United States. It shows a complete dashboard with lists, charts and maps of confirmed cases. In addition to the infected population, it also includes cases of recovery and death by country and date.

This viewer is built using ESRI’s ArcGIS Online platform, and collects information from numerous official sources. It has two great advantages:

The data is updated almost in real time (they show more recent updates than some of the sources they use).

The information is openly available on your GitHub for everyone, so anyone can download it and create their own maps and analysis.

2. World Health Organization – Novel Coronavirus (COVID-19) Situation

LINK – https://experience.arcgis.com/experience/

Following a similar scheme to the previous one, the World Health Organization has published its own online viewer with the status of COVID-19. It also uses the ESRI platform to display a dashboard with the current status of the pandemic. It uses data collected by the WHO itself and updates the data several times a day.

3. European Centre for Disease Prevention and Control

LINK – https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases

Although it is not an interactive viewer as in the previous cases, the European Union, through CEPCE, has launched a website that shows the current situation of COVID-19 globally. It displays the information in the form of tables, graphs and maps, and is updated daily. As a point in favor, there is the possibility of easily downloading the data in EXCEL format.

If you know more COVID-19 viewers and sources of spatial information, do not hesitate to leave them in the comments.

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OTHER SOURCES:

WORLD METER – https://www.worldometers.info/coronavirus/

The post Coronavirus (COVID-19) maps – online resources first appeared on GIS Course | TYC GIS Training.

But if you want also to visualize, manage and analyze your data you can use the QGIS software and its QuickOSM plugin.

With the QuickOSM plugin, you can download OSM data thanks to the Overpass API. The Overpass API acts as a database over the web: the client sends a query to the API and gets back the data set that corresponds to the query (for more information check the next link https://wiki.openstreetmap.org/wiki/Overpass_API).

In QGIS first of all you need to bring into your map canvas the OpenStreetMap Basemap. Then zoom in to your area of interest. In this exercise we choose an area south of Madrid City, around Ciudad Real.

In the next step we will proceed and install the QuickOSM Plugin. Go to Plugins > Manage and Install Plugins. Type OuickOSM in the Search Box and Install Plugin.

Go to Vector > QuickOSM to check if the plugin was installed correctly. You can also access the QuickOSM plugin by activating the QuickOSM Toolbar.

A new window will open. Here you need to select the Key – in our case we will select the highway key as we want to download the roads network of the zoom in area (Ciudad Real City).

the Value – subdivisions of the Key. In order to download all we will leave the first option selected (Query on all values).

the Limits of the download area – in our case we will select the Canvas Extend. This means that all OSM objects with the key “highway” in the Canvas Extend will be downloaded.

Click on Run Query.

The Query was successfully and you will receive a message. 3 layers have been loaded into your QGIS map canvas.

Deactivating the OpenStreetMap basemap we can observe better the layers just loaded.

3 layers (point, polygon and line type) are loaded. They represent elements related to the “highway” key such as: pedestrian areas (as polygon features), traffic signals, crossing points (as point features) and roads (as line features). Check their Attribute Table.

NOTE: These layers are temporary ones. In order to save them into your computer you must export them and save them.

Now you have a set of data which will help you in your future GIS analysis.

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