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.
We're sharing the third edition of the bestselling book Python for Data Analysis, including complete sample code repositories, PDF version, and online access links.
Following our previous article 《「GIS Data」Global Maximum Personal Income Tax Rates for 2023》, many readers requested guidance on visualizing the data. This guide demonstrates a rapid technique to acquire global administrative boundaries using native QGIS functionality - no plugins required.
Note: While remarkably simple, this approach requires boundary verification, particularly for China.
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.
Following our previous article 《https://malagis.com/arcgis-pro-3-1-6-installation-problem-solution.html》, we're sharing a community-developed utility that addresses persistent application anomalies. This tool efficiently resets user configurations to resolve multiple operational failures.
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:
We're sharing a valuable 2023 global soil erodibility dataset acquired through complex application procedures. This resource is particularly useful for GIS researchers conducting soil erosion studies.
In response to community inquiries regarding forest cover data analysis (e.g., correlation with PM2.5 levels), we present a comprehensive 2020 global forest coverage dataset available through multiple access methods: WMS services, Google Earth Engine (GEE), or direct download.
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