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- Generate an automatic report with QGIS and Data Plotly: integrate graphics into a PDF atlas
Having seen how to create and export a series of graphs with Data Plotly, let’s move on to the next step: integrating these graphs into a QGIS atlas or automated report. This method can be used… - Automatically export a series of feature-based graphics with QGIS and Python (without Data Plotly)
In our previous articles, we looked at how to create graphs in QGIS with Data Plotly. Today, we’re going one step further: automate the generation of a graph by range (or any other entity), exporting the… - Crossing spatial selection and graphic analysis in QGIS with Data Plotly
In our previous article, we discovered how to use the Data Plotly plugin to create graphs directly in QGIS. Today, let’s go a step further and learn how to dynamically filter the data displayed in graphs,… - Visualize your GIS data in QGIS with the Data Plotly plugin
QGIS is a powerful Geographic Information System (GIS) software, renowned for its modularity thanks to its numerous plugins. Among these, Data Plotly stands out for its ability to create interactive graphics directly from GIS layers. A… - Heatmaps and hotspot maps in QGIS
Heatmaps and hotspot maps in QGIS: understanding the differences In spatial analysis, heatmaps and hotspot maps are two powerful techniques for revealing concentrations or areas of interest from geographic data. While their appearance may be similar… - Easily add base maps to QGIS: three practical methods compared
Introduction Adding map backgrounds is a key step in visualizing spatial data with QGIS. Whether it’s to contextualize your layers, create a beautiful printable map, or simply to better interpret your data, quickly having a background… - QGIS: A New “SQL Query” Option in the Layer Context Menu
Starting with QGIS version 3.42, a subtle but powerful feature has been added to the context menu of vector layers: the “SQL Query…” option. This improvement provides a direct and user-friendly interface for running SQL queries,… - QGis and geoparquet
History of Parquet and GeoParquet 1. Apache Parquet – The original format History: Objective: GeoParquet – Geospatial extension of Parquet History : Year Event 2021 (April) First exchanges on GitHub and in open source communities to… - ENC maps in QGis with Postgis(1)
This subject comprises two articles. The first deals with importing ENC S57 files into a Postgresql/postgis database. The second deals with setting up an automatic symbology equivalent to nautical charts. You can download all the scripts…
Why do we prefer Open Source software?
Geomatics is a discipline at the crossroads of geography and computer science, which involves using software tools to collect, store, analyze and represent spatial data. In this field, the use of open source software offers many advantages.
First of all, what is open source software? It’s software whose source code is publicly available and can therefore be modified and distributed by anyone. It also means that the software is often free, in the sense that it can be used without license fees. The open source movement was born in the 1990s with the emergence of Linux, an open source operating system based on the Unix kernel. Since then, many other open source software products have emerged, covering a wide range of fields, including geomatics. Licenses play an essential role in the operation of open source software. The GPL. General Public License is one of the most common in the open source world. It guarantees fundamental freedoms for users, including the freedom to use, modify and redistribute the software. Many libraries, frameworks and open source tools used in geomatics are distributed under the GPL license.
One of the major advantages of open source geomatics software is its flexibility. Developers have access to the software’s source code, enabling them to adapt it to their specific needs. For example, if you’re using open source geospatial data visualization software and want to add a specific feature, you can modify the source code to implement it.
Another important feature of open source software is the community of developers that surrounds it. These communities are made up of volunteer programmers who actively contribute to the development and improvement of open source software. They share their knowledge, resolve bugs and provide support to users. This ensures the software’s longevity and scalability, as new versions and features are continually developed.
Among the most popular open source geomatics software are GIS-based geographic information systems such as QGIS, which offer a user-friendly graphical interface and powerful spatial analysis functions. There are also libraries such as GDAL and proj, which can be used to manipulate geospatial data in a wide range of formats. As far as geospatial databases are concerned, PostgreSQL with the PostGIS extension is a popular open source solution. It enables efficient storage and processing of spatial data. In addition, open source tools such as Geoserver or MapServer can be used to publish this data on the web. In the field of cartography, the free and open source Mapnik software offers a powerful solution for custom map creation and tile generation. In addition to geomatics-specific software, more general open source solutions such as Python, R and Java can also be used to analyze and manipulate geospatial data.
In conclusion, using open source software in geomatics offers many advantages. They are flexible, scalable and benefit from an active community of developers. What’s more, they offer genuine interoperability with other software and can be used in a variety of environments, including Windows, MacOS and Linux. However, it should be remembered that the use of open source software does not mean that all software used in a geomatics project must be open source. It is common practice to integrate proprietary software into an open source environment, using open protocols and data formats to ensure greater interoperability.
In short, the open source world offers a multitude of solutions for geomatics, allowing users to access, modify and redistribute software source code according to their specific needs. This fosters freedom, innovation and collaboration within the community of open source geomatics software users and developers.