Geo

This article is reposted from Building a High-Performance Elevation API At ColorfulClouds Technology(彩云科技， “cai yun” in Pinyin for 彩云), we are committed to providing users with meteorological data at higher temporal and spatial resolutions. Over the years, we have consistently faced a challenge: due to limitations in elevation data resolution, outdoor activity enthusiasts, particularly those involved in hiking and cross-country activities, often experience noticeable discrepancies between ColorfulClouds’ data and their actual experiences. This issue is especially prominent in mountainous and plateau regions with dramatic elevation changes. ...

The basic development work of tzf and related projects has basically stabilized. In the previous article, there are sporadic information about the development and design process: 2022-05-29, 在 Go 中将经纬度转时区 2022-08-01, Python 中经纬度转时区新的选择 2022-08-27, 用 Go 编写 Python 扩展 2022-09-10, tzf 预览图制作 2022-11-24, tzfpy Rust 重写 This article is the final summary, from the start-up of the project to the gradual optimization and evolution. ...

When dealing with large amounts of scattered data, sometimes we need to provide a read-only query API to visualize on a map. When the amount of data is too large, say millions, it is not appropriate to return it all to the front end for processing on the browser. Some aggregation should be completed within the back-end service to return the aggregated search to the front end. Here’s how to do this with the MongoDB + tile index in Go. ...