December confirms a clear evolution in the QGIS ecosystem, with a rise in plugins focused on artificial intelligence, advanced analysis, and external data flow integration. Several extensions mark a convergence between QGIS and previously peripheral fields: cloud, big data, automated remote sensing, and generative AI.<\/p>\n\n\n\n

There is also a constant effort to improve the daily productivity of geomatics professionals through tools for calculating, editing, and disseminating data.<\/p>\n\n\n\n

Finally, the diversity of the plugins released illustrates the vitality of the community and QGIS’s ability to remain a central platform for both exploratory analysis and more industrial processing chains.<\/p>\n\n\n\n

<\/span>Why a monthly update?<\/span><\/h2>\n\n\n\n
The official QGIS plugin repository now has over 2,000 extensions, and new tools are added every week. These plugins allow you to:<\/p>\n\n\n\n
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automate repetitive tasks,<\/li>\n\n\n\n
facilitate access to national repositories,<\/li>\n\n\n\n
improve data quality,<\/li>\n\n\n\n
work faster and more accurately,<\/li>\n\n\n\n
or simply add features that are not available in the core QGIS software.<\/li>\n<\/ul>\n\n\n\n
Keeping track of these new developments means staying up to date in a constantly evolving GIS environment.<\/p>\n\n\n\n
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<\/span>Selection method<\/span><\/h2>\n\n\n\n
The list below is based on newly created plugins that were officially approved in the QGIS repository in December 2025, focusing on those that can immediately enhance a professional workflow.<\/p>\n\n\n\n
Let’s now take a closer look at a few plugins that stand out this month for their functional appeal or potential for professional use.<\/p>\n\n\n\n
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<\/span>🧩 Presentation of selected plugins<\/span><\/h2>\n\n\n\n
<\/span>⭐ GeoAI \u2014 Qiusheng Wu<\/span><\/h3>\n\n\n\n
Category: AI & remote sensing<\/p>\n\n\n\n
GeoAI confirms the arrival of artificial intelligence directly in QGIS. The plugin offers several AI-assisted analysis tools applied to geospatial data, particularly for raster imagery. Highly active and already popular, it is establishing itself as an emerging benchmark for exploring the uses of AI in GIS.<\/p>\n\n\n\n
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<\/span>🧠 SamGeo \u2014 Qiusheng Wu<\/span><\/h3>\n\n\n\n
Category: Image segmentation<\/p>\n\n\n\n
Based on the \u201cSegment Anything\u201d model, SamGeo automatically segments objects in geospatial images. It is a powerful tool for analyzing orthophotos, satellite images, or drone data without entering into complex deep learning workflows.<\/p>\n\n\n\n
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<\/span>🗺️ QGIS2VectorTiles \u2014 Jossef Kanter<\/span><\/h3>\n\n\n\n
Category: Webmapping<\/p>\n\n\n\n
This plugin facilitates the conversion of QGIS layers into vector tiles. It meets a growing need for modern web distribution (MapLibre, OpenLayers, etc.) and is clearly geared towards professional interactive mapping applications.<\/p>\n\n\n\n
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<\/span>📊 Hotspot Analysis v3.0.2<\/span><\/h3>\n\n\n\n
Category: Spatial Analysis<\/p>\n\n\n\n
A major new version of a well-known plugin, Hotspot Analysis identifies significant spatial concentrations. Widely used in urban planning, the environment, and social sciences, it has gained in stability and maturity.<\/p>\n\n\n\n
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<\/span>⚙️ ProcessingPowerPack \u2014 Matthias Kuhn<\/span><\/h3>\n\n\n\n
Category: Advanced processing<\/p>\n\n\n\n
Developed by a key player in the QGIS ecosystem, this plugin enriches the Processing toolbox with new algorithms. It is primarily intended for advanced users and trainers who want to take processing automation to the next level.<\/p>\n\n\n\n
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<\/span>✏️ Dynamic Field Calculator \u2014 Micha\u0142 Sikora<\/span><\/h3>\n\n\n\n
Category: Productivity<\/p>\n\n\n\n
A welcome improvement to the field calculator, with a more dynamic and interactive approach. This plugin is clearly aimed at speeding up common attribute management tasks for all QGIS user profiles.<\/p>\n\n\n\n
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<\/span>📝 Edit Tracking Tools \u2014 Renju A J<\/span><\/h3>\n\n\n\n
Category: Collaboration & Data Quality<\/p>\n\n\n\n
Edit Tracking Tools allows you to track and record changes made to layers. This is a frequent requirement in multi-user contexts, particularly for local authorities, design offices, and collaborative projects.<\/p>\n\n\n\n
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<\/span>🌊 HyperCoast \u2014 Qiusheng Wu<\/span><\/h3>\n\n\n\n
Category: Environment & Coastal<\/p>\n\n\n\n
HyperCoast offers tools dedicated to coastal zone analysis. In a context of climate change and coastal erosion, this plugin offers targeted functions for the study and monitoring of coastal environments.<\/p>\n\n\n\n
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<\/span>💧 Landsat Water Mask \u2014 Jake Longenecker<\/span><\/h3>\n\n\n\n
Category: Remote Sensing<\/p>\n\n\n\n
This plugin automates the creation of water masks from Landsat images. Easy to use and effective, it is designed for users working in hydrology, the environment, or water surface monitoring.<\/p>\n\n\n\n
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<\/span>☁️ openEO (v2.0 RC) \u2014 moreGeo GmbH<\/span><\/h3>\n\n\n\n
Category: Cloud & Big Data<\/p>\n\n\n\n
openEO connects QGIS to cloud-based Earth observation data and computing backends. Version 2.0 marks an important step toward hybrid workflows combining desktop GIS and remote computing.<\/p>\n\n\n\n
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<\/span>🗄️ Databricks DBSQL Connector \u2014 Danny Wong<\/span><\/h3>\n\n\n\n
Category: GIS & Data Engineering<\/p>\n\n\n\n
This plugin allows you to connect to Databricks via DBSQL. It illustrates the gradual convergence between QGIS and Big Data environments, and opens up interesting prospects for enterprise GIS applications.<\/p>\n\n\n\n
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<\/span>🌿 iNaturalist Import \u2014 Yves Durivault<\/span><\/h3>\n\n\n\n
Category: Participatory science<\/p>\n\n\n\n
iNaturalist Import facilitates the integration of naturalist observations from the iNaturalist platform into QGIS. An excellent example of a bridge between citizen science, education, and spatial analysis.<\/p>\n\n\n\n
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<\/span>🔍Monitoring conclusion \u2013 Key trends<\/span><\/h2>\n\n\n\n
Several strong trends emerged this month.<\/p>\n\n\n\n
First, the integration of AI into QGIS is no longer anecdotal: plugins such as GeoAI and SamGeo show that advanced methods are becoming directly accessible from the GIS interface.<\/p>\n\n\n\n
Second, connecting to external environments (cloud, analytical databases, vector tiles) is emerging as a major focus, reflecting the shift in practices towards hybrid architectures.<\/p>\n\n\n\n
Finally, despite these innovations, the fundamental needs of geomatics professionals remain very much present: data reliability, traceability of edits, and workflow efficiency.<\/p>\n\n\n\n
An interesting balance is emerging between technological innovation and the consolidation of professional practices.<\/p>\n\n\n\n
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