MalaGIS

Sharing GIS Technologies, Resources and News.

In a recent video on MalaGIS's WeChat Channel showcasing national expressway mileage rankings, viewers noted the data appeared outdated. I've now updated the dataset using official National Bureau of Statistics records. Download the verified figures below.

PS: Follow MalaGIS on WeChat Channel, Douyin, and Bilibili for more geospatial content.

Data Overview

Source: National Bureau of Statistics of China
Coverage: 1993–2023
Format: CSV
Granularity: Province-level statistics
Unit: 10,000 km (Note: 1 unit = 10,000 km)

Visualization Guide

Simple visualization can be achieved in QGIS/ArcGIS. Below is a QGIS example:

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A reader recently noted that my earlier guide on purchasing licensed ArcGIS Pro is outdated. Upon review, I confirmed this—Esri no longer offers ArcGIS Desktop 10.8.2 for personal purchase, leaving only ArcGIS Pro available. Essentially, individual users can no longer legally acquire Desktop versions.

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The recent sale of 43 global ports by Li Ka-shing—including two along the Panama Canal—has drawn international attention. I attempted to develop an interactive Cesium visualization showing these ports' geographic distribution, but news reports only mentioned quantities without specific coordinates. This required manual data collection.

PS: Video demonstration available on MalaGIS Video Channel.

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Previously, I shared resources for Downloading and Installing Global Mapper Pro v24.0, but that version is a bit outdated. Now, I'm updating to the Global Mapper Pro v25.1 resource that I'm currently using. This article will share the installation package that I have personally tested and verified to work. Additionally, the installation method for Global Mapper Pro v25.1 is slightly different from that of Global Mapper Pro v24.0, so this article will also introduce the detailed installation steps.

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In a previous article, I introduced a streamlined workflow using DeepSeek + QGIS (Beyond the Hype: Practical Integration of DeepSeek in GIS Workflows). It's undeniable that large language models like ChatGPT and DeepSeek are profoundly transforming the GIS industry. Recently, the domestic AI editor Trae officially launched. After testing it, I'm convinced this tool is essential—it significantly accelerates workflows for both GIS development and data processing!

What is Trae?

If you're unfamiliar with Trae, you might recognize Cursor; if not Cursor, perhaps Windsurf? If those don't ring a bell, have you encountered Cline, CodeGPT, v0, Bolt.new, Tongyi Lingma, or Douban MarsCode? If none sound familiar, it's time to catch up with AI advancements.

Simply put, Trae is a competitor to Cursor—the pioneering AI editor that redefined coding. Unlike autocomplete plugins (e.g., GitHub Copilot), AI IDEs like Trae and Cursor enable comprehensive code modification, refactoring, documentation, and commenting. They support multi-model integration, provide repository-wide intelligence, debug in real-time, and offer interactive AI conversations like DeepSeek.

While I previously used Cursor, its unstable performance in China limited my recommendations. But with DeepSeek's open-source release and localized optimizations, ByteDance's Trae delivers exceptional quality—highly recommended!

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The latest leaked ArcGIS Pro 3.4 learning edition with Chinese localization is now available. I've personally verified its functionality—installation is straightforward. Users interested in exploring can upgrade using this version.

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A colleague recently asked me about a well-known domestic GIS company. Having no direct experience, I inquired in the MalaGIS discussion group. While initial conversations focused on company benefits and salaries, someone discovered an unexpected issue when visiting the company's official website: a certain link led to inappropriate content.

Note: Screenshots would normally be included but cannot be shown for compliance reasons.

As a technical writer, I believe such issues deserve deeper analysis beyond mere observation.

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When creating thematic maps in ArcGIS or QGIS, thematic coloring (choropleth mapping) is a common technique where different regions are colored according to their data values, revealing spatial patterns. Recently, our management requested integrating this functionality into our business system. While we could publish pre-rendered maps from ArcGIS/QGIS through servers like GeoServer, this lightweight feature doesn't warrant heavy infrastructure. Instead, I explored coloring GeoJSON features directly and discovered colormap - an elegant solution.

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While updating to QGIS 3.40.3, I stumbled upon a surprising fact: QGIS is now 23 years old – possibly older than many of its users. It’s remarkable that this powerful open-source GIS software, used worldwide for mapping, data processing, and service publishing, was born in the dial-up internet era. Since Gary Sherman wrote its first line of code in Germany in 2002, QGIS has quietly revolutionized spatial technology for 23 years. Debuting five years before the iPhone and thirteen years before TensorFlow, this open-source GIS has not only survived three technological earthquakes (the dot-com crash, mobile revolution, and AI explosion) but evolved from a basic map viewer into global geospatial infrastructure. Let’s journey through time to uncover how this "living tech fossil" defied commercial giants to become king.

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From late last year to early this year, DeepSeek has undoubtedly dominated the tech landscape. My social feeds—public accounts and short videos—have featured daily updates about DeepSeek, from model comparisons to website glitches and workarounds for full-featured access. Concurrently, industries and institutions have launched an "arms race," with corporate announcements flooding newsfeeds about xxx adopting DeepSeek. Sectors like internet services, finance, construction, and even government agencies are rushing to deploy DeepSeek solutions, as if falling behind would mean obsolescence. The GIS industry is no exception—software vendors and GIS practitioners alike have publicly announced their DeepSeek integrations.

This prompts a question for GIS professionals like myself: After integrating DeepSeek, what comes next? Where are the practical applications for DeepSeek + GIS?

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