MalaGIS

Sharing GIS Technologies, Resources and News.

A few days ago, while casually browsing, I heard experts in a group chat mention that NVIDIA has officially opened access to the GLM-4.7 and minimax-m2.1 models for free use. For someone like me, who even refuses to pay a 10 RMB repositioning fee for shared bikes, this immediately caught my attention! After a day of intermittent practical testing for GIS documentation writing and GIS development, while these models aren't as good as top-tier paid ones yet, they are quite adequate for daily GIS tasks. If you're currently on a tight budget and your daily GIS development work isn't too complex, you might want to give them a try. Given the current GIS market and economic climate, every bit of savings helps.

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In recent years, terms featuring the word "cloud" have become incredibly popular, from public cloud and private cloud to cloud-native, cloud-edge integration, and even national land cloud, planning cloud, etc. It seems almost every industry is moving to the cloud. But have you ever wondered, when we talk about so-called "cloud" data, are those streams of 1s and 0s literally traveling through the sky from a physical perspective?

Actually, no. In fact, over 90% of global international data traffic is transmitted through cables lying in the dark depths of the ocean. From the short video you just watched, to cross-border financial transactions, and even the answers you get from Gemini or ChatGPT, are all exchanged via lengthy submarine cables. But where exactly are they laid? Which countries are international communication hubs? How do different cables differ in bandwidth and operators? Today, let me recommend a must-bookmark professional tool website for all GISers — Submarine Cable Map.

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In recent years, applications such as digital museums, digital cultural heritage preservation, and digital scenic spots have become commonplace online. The 3D reconstruction technology behind them impresses with its stunning visual appeal—using just a screen, it can deliver an immersive experience. Nowadays, this kind of immersive virtual experience has permeated various industries. For example, in the popular game Black Myth: Wukong, the "Little Western Paradise" scene was created by capturing and reconstructing the Thousand-Buddha Cliffside Temple (Qianfo'an) in Xi County, Linfen, Shanxi Province. Similarly, Assassin's Creed: Unity used 3D technology to recreate the majestic Notre-Dame de Paris, achieving a remarkable synergy between the virtual and the real.

Above: The Thousand-Buddha Cliffside Temple in Xi County, Linfen, Shanxi Province.

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On the evening of December 17, 2025, a strange incident occurred in Nanjing: citizens found that the Baidu, Gaode, and Tencent maps on their phones all "went on strike," and even Apple's built-in navigation was not spared. Some people were located "swimming" in Xuanwu Lake, while others riding shared bikes were prompted to be 57 kilometers away... The official announcement stated that this was due to temporary interference with satellite signals, though the military frequency bands of BeiDou were unaffected.

In a previous article Navigating Without GPS: Exploring Alternative Positioning Technologies - MalaGIS, we introduced several navigation and positioning methods besides GPS and BeiDou systems. However, those methods are either require professional equipment, need specific hardware support in phones, or are technologies that are not yet ready for large-scale commercial application. So, some friends have asked: how can I test if my GPS/BeiDou signal is being interfered with in such a situation, or how can I determine the credibility of my signal? Today, we recommend a method and tool for those who need it.

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It has been some time since the GPS and BeiDou signal anomaly incident in Nanjing. While the cause of the incident remains debated, an interesting question has been frequently discussed in the 'Malagis' GIS group recently: If one day, both our GPS and BeiDou signals are abnormal, and we don't have access to military-grade bands, how can we determine our location? The author has previously written a bit on this topic. Drawing from the group members' discussions and collected materials, here is a summary. Corrections are welcome if any inaccuracies are found.

Before delving into this topic, let's introduce a new concept: All-source Positioning. In this era of the Internet of Everything, the heavily relied-upon GPS is not omnipotent. Satellite signals cannot penetrate thick reinforced concrete or travel underwater. All-source positioning involves integrating various other sensors to provide alternative solutions when GPS fails. So, what are the current common solutions? Let's explore them.

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In the previous article 'Apple's Source Code Leak Incident: Key Takeaways for GIS Frontend Development', the author mentioned the Apple front-end source code 'leak' incident and highlighted several serious security risks in current front-end development. So, besides improving developers' skills, is there a more perfect detection mechanism for these risks? If you are a team leader, how can you avoid these problems as much as possible? The author believes that in addition to proper build configuration and production environment security hardening, a mechanism for continuous detection of sensitive information submitted to the repository is needed, and Gitleaks is such a tool.

What is Gitleaks?

Gitleaks is an open-source tool that can scan Git repositories (including commit history) or directories/files to detect hardcoded sensitive information, such as passwords, API keys, tokens, credentials, etc. It supports multiple scanning modes (e.g., git mode, dir mode, stdin mode) as well as custom rules, ignore rules, baseline reports, etc. Its installation methods are flexible: it supports Homebrew (Mac), Docker images, Go source builds, etc. The community is active, with nearly 24k stars on GitHub, and it is widely adopted.

In short: if your project may have sensitive credentials, tokens, or keys (especially in front-end, back-end, DevOps, CI/CD processes) accidentally submitted or left in history, Gitleaks is a tool that significantly adds assurance.

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A few days ago, while working on a GIS dashboard development, I encountered a highly peculiar issue: the map worked perfectly in the development environment but failed to display in the production environment. After a thorough investigation, I finally discovered that the GeoJSON data in the production environment was problematic. The data team might have manually edited and accidentally deleted some content during the GeoJSON export process, resulting in incomplete data. Since no comprehensive validation was performed beforehand, this caused the map to fail to load.

After identifying the problem, I decided to create a validation tool to prevent similar issues in the future. I tested several methods available online and have summarized a few reliable ones to share with you. The core idea is: Attempt to convert each GeoJSON file into an ArcGIS format (such as a feature class). If the conversion is successful, the file is considered valid; if it fails, capture the error and log it.

Method 1: Using Geoprocessing Tools for Manual Batch Processing (Suitable for a Small Number of Files)

This method leverages the error handling mechanism of geoprocessing tools but requires manual setup.

First, place all the GeoJSON files you need to check in the same folder. Then, open the Geoprocessing pane (Analysis > Tools), search for and find the JSON To Features tool. This official tool for converting GeoJSON is strict with format requirements, making it very suitable for checking validity. In the tool interface, click the folder icon next to the Input JSON parameter. Locate the GeoJSON folder and select multiple files (hold Ctrl or Shift keys). Finally, set an output location and click Run.

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Recently, a hot topic has been the Apple source code leak incident. Due to negligence by a developer, Apple failed to disable the sourcemap functionality in the production environment during the deployment of the App Store web version, leading to the exposure of the complete frontend code. This incident quickly sparked heated discussions within the tech community. Although only frontend logic code was leaked, containing no user data or security vulnerabilities, it served as a wake-up call for the frontend development field. The author takes this opportunity to discuss some lessons that can be learned for GIS frontend development.

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While recently researching how to load Bing Maps in ArcGIS Pro, the author conducted a simple packet capture of Bing Maps and discovered an unusual phenomenon. When requesting tile data, Bing Maps uses a request format that is noticeably different from common approaches. For example, services like Gaode Map typically pass xyz parameters, which correspond to x and y coordinates and the zoom level z. In contrast, Bing Maps passes a single integer parameter instead of three separate xyz values. How does this work? The image below shows a packet capture of Bing Maps requesting remote sensing imagery.

The image below shows a packet capture of Gaode Map requests.

Clearly, the request format of Bing Maps differs from that of Gaode Map. Bing Maps uses an integer parameter, while Gaode Map uses xyz parameters. So how is the Bing Maps request format generated?

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Users of ArcGIS Pro who wish to customize advanced features often rely on Python scripts, as many functions of ArcGIS Pro itself are implemented using Python. However, directly installing various Python packages in the built-in environment can easily lead to compatibility issues (especially since Python packages often have compatibility problems between versions). Therefore, ArcGIS Pro comes with a built-in Conda environment and packages the environment that ArcGIS Pro depends on as a read-only environment. This ensures that ArcGIS Pro remains stable and does not fail to run due to arbitrary modifications by users. As shown in the figure below, the software clearly indicates that the default environment cannot be modified.

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