The Application Strategy for Big Data of Forestry

• Main Authors: Yu-ting Shen, 沈玉婷
• Other Authors: Chyi-Rong Chiou
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/35755321872045691807

碩士 === 國立臺灣大學 === 森林環境暨資源學研究所 === 103 === 　“Big Data” issue is essentially not an “all new” issue. It developed by the basis of information technology over the past decade. Because of the high-level digital strategy, large amounts of data has been collected. It makes the past data processing technology and application mode to be challenged, and also makes a new way of thinking of information and knowledge capture. 　Through this study, we review the property of Big Data: its main characteristics are “data volume”, “data velocity” and “data variety” (3V). Actually the definition varies depending on the needs of users. In the technical part, which contains the process of data collection, integration, analysis and visualization of operational presentation, etc. It also related to the heterogeneity of the sources of information integration. Corresponding the issue of technology, the data characteristics can be classified into dynamic and static two categories, and be expected to enhance the efficiency and information are for information capture capabilities. The other side, in application, it is still in the early stages of development of Big Data currently in Taiwan. There are some main development direction to be considered, including that: data acquisition, technical skill, data policy, and also organizational change and capability. 　This study describes Big Data case of forestry applications: “Global Forest Watch (GFW).” The project combines lots of research organizations around the world. It provides information of forest cover, forest change, fires monitoring and decision making tool of forest resource management, in order to monitoring global forest resources and promote resource conservation. In Taiwan, although long-term survey of forest resources, but the ability of get near-real time change information is still insufficient. In this article, using the satellite images try to identify the temporal-changes, discuss how to observe vegetation growth trends from the process of analysis. Finally, try to make suggestions of the future development of Big Data application in Taiwan.