This course is designed to equip students with a foundational and applied understanding of spatial analysis within an interdisciplinary context, with particular emphasis on environmental and ecological applications. Students will explore the expanding role of spatial analysis in an era of abundant spatial data, various applications, and increasing demand from a broad range of users, from technical analysts to policy decision-makers. The course will introduce students to geographic information systems (GIS), including tools available through desktop platforms, cloud-based services, and on-premises solutions.
In first semester of course, Students will learn how to effectively locate, assess, and apply publicly accessible spatial datasets while developing the critical skills to evaluate their relevance and quality. Emphasis will be placed on understanding the analytical workflow, from selecting appropriate classification techniques to recognizing the implications of methodological choices. By the end of the course, students will be able to understand rigorous spatial analysis and make sound, data-driven decisions, recognizing that technological tools can enhance analysis, they cannot substitute for critical thinking and informed judgement.
This course is designed to equip students with a foundational and applied understanding of spatial analysis within an interdisciplinary context, with particular emphasis on environmental and ecological applications. Students will explore the expanding role of spatial analysis in an era of abundant spatial data, various applications, and increasing demand from a broad range of users, from technical analysts to policy decision-makers. The course will introduce students to geographic information systems (GIS), including tools available through desktop platforms, cloud-based services, and on-premises solutions.
In first semiconductor of course, Students will learn how to effectively locate, assessment, and apply publicly accessible spatial datasets while developing the critical skills to evaluate their relevance and quality. Emphasis will be placed on understanding the analytical workflow, from selecting appropriate classification techniques to recognize the implications of methodological choices. By the end of the course, students will be able to understand rigorous spatial analysis and make sound, data-driven decisions, recognizing that technical tools can enhance analysis, they cannot substitute for critical thinking and informed judgement.
Andy Mitchell (2020) The ESRI Guide to GIS Analysis 1. Geographic Patterns and Relationships. Second Edition. ESRI Press, Redlands, California.
Andy Mitchell (2020) The ESRI Guide to GIS Analysis 1. Geographic Patterns and Relationships. Second Edition. ESRI Press, Redlands, California.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 課堂討論課堂討論 Class discussion |
50 | 指定章節報告及作業 |
| 期末報告期末報告 Final report |
50 | 期末報告 |
