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 is a number of the libraries which can be downloaded-make it easier to perform geospatial Python.

~that the term "geospatial data", refers to information, 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, an D 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 is answered by analyzing geospatial data.

~how geospatial data can be used for visualization.

~how mash-ups can is 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 Develop ment.

~the influence the open source software movement have had on the availability of high quality, freely-available tools for G Eospatial development.

~how various standards organizations has 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.

Python Geospatial Development Reading Note (1)