When our frontend team requested updated administrative division codes, I leveraged the 2024 national standard vector map dataset (Approval No. GS(2024) 0650) shared in our previous article. This official dataset contains accurate administrative codes within its attribute tables, making it ideal for extraction.
Building upon our previous sharing of district/county-level administrative division data, we now provide the 2024 updated version sourced from China's official platform. This dataset addresses limitations in earlier versions (e.g., data gaps, insufficient detail) while maintaining cartographic compliance.
Following our previous article on the https://malagis.com/gis-data-share-2010-2020-global-forest-age-distribution-gami-data.html, this guide demonstrates netCDF visualization techniques in QGIS, eliminating the need for specialized tools like IDL.
TorchGeo is a PyTorch domain library, similar to torchvision, specifically designed for geospatial data. It provides datasets, samplers, transforms, and pretrained models to help machine learning practitioners work with geospatial data and enable remote sensing experts to explore machine learning solutions.
When tasked with downloading decades of monthly GIS data from a restricted website, I encountered aggressive CAPTCHA challenges that blocked batch downloads. As a lazy GIS professional unwilling to perform repetitive manual downloads, I developed an automated solution.
Amidst China's strategic focus on secure and controllable information technology systems, the domestic innovation ecosystem has ushered in unprecedented opportunities. The rise of homegrown operating systems, databases, middleware, and GIS software has fortified information security while providing new technological foundations for the GIS industry. Within this context, innovations in GIS cartography transcend traditional spatial visualization, advancing toward intelligent, personalized, and real-time applications that unlock new possibilities for creating high-value maps.
With the rapid development of AI technologies—such as in our earlier article A First Look at Using Segment Anything for GIS and the booming trend of generative AI—many GIS professionals might wonder: is there an AI tool that can help with vectorization tasks? The answer is yes. In this article, we will explore how to use an AI-powered plugin in QGIS to automate vectorization.
When extending ArcGIS Python functionality (e.g., using openpyxl for Excel integration), installing supplementary packages becomes necessary. This guide demonstrates manual and automated installation methods for both online and offline scenarios.
Using Python within ArcGIS requires foundational Python knowledge. The following modules support Python integration:
While developing a workflow involving spatial data duplication, an analyst requested help with client requirements:
① Convert individual polygons to WKT format in TXT files
② Merge multiple polygons into MultiPolygon WKT format
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