Datasets - Tag - Zhiversehttps://yao-chih.netlify.app/en/tags/datasets/Datasets - Tag - ZhiverseHugo -- gohugo.ioenyaochihh@gmail.com (Josh)yaochihh@gmail.com (Josh)ZhiverseHistorical Typhoon Data Download for Taiwanhttps://yao-chih.netlify.app/en/historical-typhoon-data-download-for-taiwan/Mon, 13 Jul 2026 11:03:14 +0800Authorhttps://yao-chih.netlify.app/en/historical-typhoon-data-download-for-taiwan/

The cover image is a downloaded typhoon satellite image. It is a satellite water vapor cloud image produced by the Central Weather Administration (CWA) using CCU/SSL. The image was captured at 07:10 on July 11, 2026, and was obtained from the Weather Image Archive of the Department of Atmospheric Sciences at Chinese Culture University (Atmospheric Science Research and Application Databank).

This is a small program that was originally written to download typhoon satellite images and related data. Its initial purpose was to collect image data for image recognition research. Since the program was developed at an earlier stage, it still contains several relatively immature implementation approaches. Therefore, this article serves only as a record and reference for the data download process, and does not provide an in-depth discussion of the program architecture or optimization methods. The programming language used in this project is Python.

]]>Global Spatiotemporal Data: Exploring and Downloading Resources from NASA GES DISChttps://yao-chih.netlify.app/en/global-spatiotemporal-data-exploring-and-downloading-resources-from-nasa-ges-disc/Sat, 29 Nov 2025 21:53:36 +0800Authorhttps://yao-chih.netlify.app/en/global-spatiotemporal-data-exploring-and-downloading-resources-from-nasa-ges-disc/<div class="featured-image"> <img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/refs/heads/main/posts/Global%20Spatiotemporal%20Data%20Exploring%20and%20Downloading%20Resources%20from%20NASA%20GES%20DISC/cover%20image.png" referrerpolicy="no-referrer"> </div>GES DISC is a scientific data center under NASA that preserves Earth science–related data and provides free access to all users, making it an excellent source for obtaining spatiotemporal data.Definition of Datasethttps://yao-chih.netlify.app/en/definition-of-dataset/Fri, 09 May 2025 23:30:30 +0800Authorhttps://yao-chih.netlify.app/en/definition-of-dataset/<div class="featured-image"> <img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/main/posts/Definition%20of%20Dataset/cover%20image.png" referrerpolicy="no-referrer"> </div>In this era of big data, our lives are filled with various forms of information. If we treat each piece of data as an observation and collect them together, we can roughly obtain a dataset composed of many individual data points. These datasets can be either structured or unstructured. By organizing and filtering the data to extract useful information and eliminate irrelevant parts, we can create a dataset suitable for analysis, model training, or academic research. A dataset may include different data types such as numbers, text, images, audio, or video, depending on its intended application and the methods used to collect and organize it.