In this chapter, we discussed many of the core concepts that underlie GIS development, looked briefly at the history of GIS, examined some of the more common GIS data formats, and got our hands dirty exploring U.S. state maps downloaded from the U.S. Census Bureau website. We have seen that:
- Locations are often, but not always, represented using coordinates.
- Calculating the distance between two points requires you to take into account the curvature of the Earth's surface.
- You must be aware of the units used in geo-spatial data.
- Map projections represent the three-dimensional shape of the Earth's surface as a two-dimensional map.
- There are three main classes of map projections: cylindrical, conic, and azimuthal.
- Datums are mathematical models of the Earth's shape.
- The three most common datums in use are called NAD 27, NAD 83, and WGS 84.
- Coordinate systems describe how coordinates relate to a given point on the Earth's surface.
- Unprojected coordinate systems directly represent points on the Earth's surface.
- Projected coordinate systems use a map projection to represent the Earth as a two-dimensional Cartesian plane, onto which coordinates are then placed.
- Geo-spatial data can represent shapes in the form of points, linestrings, and polygons.
- There are a number of standard GIS data formats you might encounter. Some data formats work with raster data, while others use vector data.
- How to download map data from the U.S. Census site.
- How to install and run GDAL.
- How to analyze downloaded Shapefile data.
- How Shapefile data is organized into geometries.
- How to use the Haversine formula to manually calculate the great circle distance between two points.
In the next chapter, we will look in more detail at the various Python libraries that can be used for working with geo-spatial data.
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.