MalaGIS

Sharing GIS Technologies, Resources and News.

In previous articles such as "Revisiting Locating User Positions Using IP Addresses (ip2region)" and "Summary of Methods for Locating User Positions Using IP Addresses", we introduced many methods and tools for IP geolocation. These include GeoIP, ipip, ip2region, as well as numerous third-party service providers like Amap and Baidu. Among them, some are online, some are offline, some are paid, and some are free. A few days ago, the editor came across another interesting open-source IP geolocation library: public-ip-address.

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During GIS project delivery, situations with weak or no network connectivity are frequently encountered. Typically, we need to manually download map tiles from various providers. Currently, there are numerous map downloaders available on the market, both free and paid. Upon closer thought, this process isn't particularly complex; it essentially breaks down into three steps: defining the area of interest, downloading all tiles within that area, and exporting. Therefore, while working on a project, the author searched for a simple, small-scale downloader and ultimately found one on GitHub: OfflineMapDownloader.

Project Introduction

Original Project Repository:

https://github.com/0015/OfflineMapDownloader

After testing, the author identified several significant issues, primarily in the following three areas:

1. It only supports OpenStreetMap and ArcGIS Online.
2. It does not support downloading tiles for regions in China.
3. The downloaded .mbtiles files cannot be opened in QGIS.

The issue with China regions was particularly critical, rendering the tool unusable for the author. Consequently, the author made some simple fixes and created a new version. The author's version repository:

https://github.com/sailor103/OfflineMapDownloader

This version primarily addresses the three aforementioned problems. It can now correctly export maps for Chinese regions and supports opening the files in QGIS, as shown below:

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In today's era of booming real-world 3D technology, OSGB format models are widely used. However, "how to publish efficiently and browse smoothly" has always been a pain point for developers: slow loading, large file sizes, laggy interactions on mobile devices... Even star engines like Cesium struggle with issues such as "bloated architecture and subpar mobile experience." In mid-January this year, Zhongke Tuxin open-sourced a lightweight real-world 3D model publishing engine — Wish3D. It claims to be free and open-source, accessible for both individuals and enterprises without barriers. The editor saw it in the MalagiGIS group yesterday and immediately downloaded it for a test drive. Overall, it's indeed fast, but there are several minor issues. Let's share the experience today.

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Recently, while working on an offline map deployment project, I found that the transfer efficiency was relatively low and offline deployment cumbersome when dealing with massive amounts of scattered tile files. Initially, I considered using a ZIP package for transfer and extraction, but later discovered that a format already existed which implements this concept and does so even better: MBTiles. MBTiles is a map tile storage specification based on an SQLite database. It packages thousands of independent map tiles (PNG, JPG, or vector PBF) into a single .mbtiles file.

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On January 5, 2026, Mapbox, a leading global location services platform, officially announced the launch of its Mapbox 3D Lanes feature, designed to address the common problem of taking wrong turns at complex intersections. The Mapbox 3D Lanes feature includes lane geometry, lane markings, and 3D models of overpasses and tunnels, helping drivers follow their routes more easily.

How Effective Is It?

Frankly, our team was immediately captivated by the released preview images. After all, when it comes to aesthetic appeal, Mapbox has never been one to shy away from a challenge.

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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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