MalaGIS

Sharing GIS Technologies, Resources and News.

CesiumJS is one of the core engines for 3D earth and 3D map development on the web. It is widely used in photorealistic 3D, oblique photography, BIM, and other scenarios, and serves as the "standard client" for the 3D Tiles ecosystem. On June 1, 2026, the Cesium team released CesiumJS 1.142, focusing on large-scale data rendering performance, the integration of vector tiles with 3D Tiles, and improvements to the low-level BufferPrimitive rendering capabilities. Here is an introduction based on the official Releases.

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In GIS scenarios such as digital twins, urban modeling, and terrain mapping, point cloud data acquired by LiDAR is increasingly becoming a core asset. However, point cloud data is characterized by its large volume and diverse formats. To efficiently publish massive LAS and LAZ files to the web for loading by 3D engines like Cesium, a complex process of tiling, compression, and coordinate system transformation is often required. Although open-source point cloud tiling tools exist on the market, most still rely on the pnts format of 3D Tiles 1.0 and offer limited support for the LAZ compression format and very large datasets. We recently discovered an open-source tool: Point Tiler, which supports converting point cloud data into the v1.1 version of 3D Tiles.

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As a "benchmark framework" in the GIS field for 3D globe and map development, Cesium's monthly updates consistently deliver practical feature optimizations and technical breakthroughs for developers. In February, the three core tools—CesiumJS, Cesium for Unreal, and Cesium for Unity—received synchronized updates, and the Cesium ion cloud processing engine underwent comprehensive enhancements.

CesiumJS v1.138

As the benchmark for 3D WebGIS, the v1.138 release of CesiumJS this month focused on memory optimization and compatibility fixes. The development team refactored Megatexture, switching to WebGL2's Texture3D for handling volumetric rendering. This significantly reduces runtime memory consumption during voxel rendering. For large-scale 3D geological data, meteorological cloud imagery, and similar scenarios, this translates to smoother loading and interaction. The update also resolved several routine bugs, including image distortion on Intel Arc GPUs and abnormal label sizing for certain fonts and special characters.

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As a GIS frontend developer, I work extensively with various large-scale graphics libraries: OpenLayers, Leaflet, Mapbox GL JS, Cesium, Turf.js... These libraries often contain tens of thousands of lines of code. I wonder if you've encountered situations during development where you needed to modify the source code within node_modules. For example, in my old projects using OpenLayers 6.x, some third-party plugins were no longer updated. In such cases, upgrading to newer plugin versions would require upgrading the OpenLayers version, which is often an impossible workload for a project delivered years ago.

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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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This afternoon, while I was browsing the Mala GIS group, a user named @zheer discovered a pop-up demanding unpaid wages in an open-source Cesium examples project. This immediately piqued my interest, so I opened it to explore. The project summarizes common effects in Cesium development with over 200 demos, and also includes over 100 demos developed with ThreeJS. It's lamentable that such a talented developer had to resort to using an open-source project to plead for their wages, which is quite disheartening.

Open-source project address: https://jiawanlong.github.io/

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Last year, our team introduced how to load lunar datasets in Cesium. Now, one year later, Cesium has officially begun supporting the Mars dataset—Cesium Mars. Cesium Mars is a 3D Tileset designed to enable developers and researchers to quickly create visualizations and simulations of Mars. The dataset integrates laser altimeter data (MOLA) from NASA's Mars Global Surveyor (MGS), high-resolution stereo camera imagery (HRSC) from ESA's Mars Express, and color satellite image rendering, realistically recreating the visual appearance of Mars.

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In a previous article "Maptalks: An Open-Source Alternative to Cesium for Geospatial Visualization", we introduced maptalks as an alternative framework to Cesium. Recently, we discovered another open-source 2D/3D engine: three-tile. Designed for lightweight implementation with ongoing functional improvements, it already meets significant development demands. Here is a brief introduction.

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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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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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