Python Geospatial Development reading note(1)

chapter 1, Summary:

In this chapter, we briefly introduced the Python programming language and the main concepts behind geospatial development. We have seen:

　　~That Python is a very high-level language eminently suited to the task of geospatial development.

　　~That there are a number of libraries which can be downloaded to make it easier to perform geospatial development work in Python.

　　~That the term "geospatial data" refers to information that is located on the earth's surface using coordinates.

　　~That the term "geospatial development" refers to the process of writing computer programs that can access, manipulate, and display geospatial data.

　　~That the process of accessing geospatial data is non-trivial, thanks to differing file formats and data standards.

　　~What types of questions can be answered by analyzing geospatial data.

　　~How geospatial data can be used for visualization.

　　~How mash-ups can be used to combine data(often geospatial data) in useful and interesting ways.

　　~How Google Maps, Google Earth, and the development of cheap and portable GPS units have "democratized" geospatial development.

　　~The influence the open source software movement has had on the availability of high quality, freely-available tools for geospatial development.

　　~How various standards organizations have defined formats and protocols for sharing and storing geospatial data.

　　~The increasing use of geolocation to capture and work with geospatial data in surprising and useful ways.