空間大數據(Spatial Big Data)是大數據分析領域中的其中一種資料型態，而隨著政府開放資料(Open data)的發展趨勢，以空間大數據為基礎的政策分析與公共管理，事實上也隨著開源軟體(Open Source Code)的免費與普及，而有愈來愈多的空間大數據分析成果。其次，隨著空間數據的可取得程度日益便利，例如犯罪地點、交通事故與違規地點、長照服務地點、公車站牌位置等，這些與公共服務有關的空間資料，相信都是深具政策與管理意涵的空間大數據。
因此，本課程的目標，就是讓學生具備分析這些有價值的空間大數據的基本能力。本課程將說明空間大數據的基本資料型態，接著透過空間大數據的分析案例，帶領學生實際進行空間大數據的分析練習；另外，同學將實際使用GIS軟體QGIS，學習空間大數據分析的操作技能。
（修課同學以自備筆記型電腦為佳）
Spatial Big Data is one of the data types in the field of large data analysis. In fact, with the development trend of the government opening data, policy analysis and public management based on space data, in fact Also, with the free and popularization of Open Source Code, there is an increasing number of spaces for analysis. Secondly, with the increasing availability of space data, such as crime locations, traffic accidents and violation locations, long-term service locations, bus stop locations, etc., these space data related to public services are believed to be highly policy-based and Manage the space of meaning.
Therefore, the goal of this course is to allow students to have the basic ability to analyze these valuable space large data. This course will explain the basic data types of space large data, and then lead students to actually conduct analysis and practice of space large data through analysis cases of space large data; in addition, students will actually use GIS software QGIS to learn the operation of space large data analysis Skill.
(It is best for students who study in the courses to prepare a self-written notebook computer)
1.空間大數據分析講義。
2.石計生、黃映翎，2017，當代Q地理資訊系統:從人文社會到大數據，雙葉。
1. Space large data analysis explanation.
2. Shi Jingsheng, Huang Yingling, 2017, Contemporary Q Geographic Information System: From Humanities and Society to Large Data, Double Leaf.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 隨堂QGIS操作練習成果(練習A-G) 隨堂QGIS操作練習成果(練習A-G) Lutong QGIS operation training results (practice A-G) |
70 | 每位同學要自行完成練習，老師檢視學習成果後評分。 |
| 出席率出席率 Attendance rate |
10 | 全勤給10分；缺席(含請假)3次以上者，0分；缺席(含請假)達6次者，扣考。 |
| 期末學習心得期末學習心得 Final learning experience |
20 |
