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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/cybergis
课程评论：没有评论
课程名称：网络地理信息系统入门（Getting Started with CyberGIS） 课程概述：本课程旨在向学生介绍网络地理信息系统（CyberGIS），探讨基于高级网络基础设施的地理信息科学与系统（GIS），以及在地理数据科学背景下的高性能计算、大数据和云计算的最新进展。课程强调学习网络地理信息系统的前沿进展及其背后的地理数据科学原理。 课程大纲： 1. 课程导览 - 描述：学生将熟悉课程内容、同学及学习环境，同时获得参与课程所需的技术技能。 2. 模块1：什么是网络GIS？ - 描述：本模块介绍网络GIS和地理数据科学的基础知识，包括地理信息科学与系统的定义及相关概念，先进网络基础设施的基本构成，以及网络GIS如何将网络基础设施与GIS相结合，产生更大效益。我们还将探讨地理大数据的复杂性与挑战，以及地理数据科学如何提供解决方案，并回顾需要网络GIS和地理数据科学来应对的科学应用和需求。 3. 模块2：使用Python进行地理可视化 - 描述：学生将学习使用Python进行地理数据可视化和网页制图的技术，包括使用Matplotlib、Basemap和Cartopy绘制地理数据及创建地图，使用Mplleaflet和Folium库创建和分享网页地图，以及简介GeoPandas的基本使用方法。 4. 模块3：地理对象操作及大数据处理基础 - 描述：本模块介绍使用Python地理空间库操作地理对象的技术，包括使用Shapely和RasterIO库操纵矢量和光栅数据。接着，学生将学习Hadoop框架在处理大地理数据中的应用，了解Hadoop的基本组成部分和特征，以及如何通过Hadoop分布式文件系统（HDFS）进行数据处理，并通过MapReduce编程模型处理纽约市出租车数据的实例。 5. 模块4：理论基础与未来趋势 - 描述：本模块将学习网络GIS的理论基础，涉及计算强度计算，结合应用案例研究来实现这些理论概念，最后探讨未来的趋势。 该课程旨在为学生提供网络GIS领域的基础知识和实践技能，帮助他们在地理数据科学的快速发展中把握前沿技术。
Name:Course Orientation
Description:You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
Name:Module 1: What is CyberGIS?
Description:In this module, we will get introduced to the basics of CyberGIS and Geospatial Data Science. First, we'll learn about the definition of Geographic information science and systems, and related concepts. Next, we'll get introduced to the basics of advanced cyberinfrastructure and its components. Then we will see how CyberGIS combines Cyberinfrastructure and GIS to produce a sum that is greater than its parts. We will see the components of CyberGIS and the community and sciences it supports. Then, we look at geospatial big data, specifically the complexity and challenges it presents in terms of data representation, sharing, and privacy. We then look at how Geospatial Data Science provides tools to resolve the challenges posed by big geospatial data. Finally, we conclude the lesson by looking at scientific applications and drivers that require CyberGIS and Geospatial Data Science to address the problems posed by them.
Name:Module 2: Geospatial Visualization using Python
Description:In this module, students will get introduced to techniques for geospatial visualization and Web mapping using Python. First we'll learn about the basics of plotting geospatial data and creating maps using Matplotlib, Basemap, and Cartopy. Next, we will learn techniques to create and share our Web maps using Mplleaflet and Folium libraries. Lastly, we will see a brief introduction to GeoPandas and how to use it to do simple plot, simple geometry, and conduct basic spatial operations.
Name:Module 3: Geospatial Object Manipulation and an Introduction to Taming Big Data with Hadoop
Description:In this module, students will get first get introduced to techniques for manipulating geospatial objects using geospatial libraries in Python. Specifically, we will learn how to manipulate both vector and raster data objects using Shapely and RasterIO libraries. Next, students get introduced to using the Hadoop paradigm for taming big geospatial data. Specifically, we will learn the fundamentals of how to process big spatial data with Hadoop. Students will get a brief introduction to the Hadoop framework, its major components, and its characteristics, and will learn about Hadoop Distributed File System (HDFS), its architecture and simple commands to interact with it. We will also learn about the MapReduce computing paradigm and see an example of how it may be applied using Hadoop streaming API to process New York City taxi data.
Name:Module 4: Theoretical Foundations and Future Trends
Description:In this module, we will learn about the theoretical underpinnings of CyberGIS. We will start the module by looking into theoretical foundations of cyberGIS, specifically looking at the computational intensity calculations. Then we will apply the theoretical concepts to an application case study learning how to calculate this computational intensity. Lastly, we will conclude the module and course by looking at some future trends.
This course is intended to introduce students to CyberGIS—Geospatial Information Science and Systems (GIS)—based on advanced cyberinfrastructure as well as the state of the art in high-performance computing, big data, and cloud computing in the context of geospatial data science. Emphasis is placed on learning the cutting-edge advances of cyberGIS and its underlying geospatial data science principles.
