![]() ![]() Geospatial data in vector format are often stored in a shapefile format (. Image Source: Colin Williams (NEON) Introduction to the Shapefile File Format Which Stores Points, Lines, and Polygons Each object type has a different structure. There are 3 types of vector objects: points, lines or polygons. Thus, the outlines of plot boundaries, lakes, oceans, and states or countries are often represented by polygons. ![]() Polygons: A polygon consists of 3 or more vertices that are connected and “closed”. This line is composed of a series of segments, each “bend” in the road or stream represents a vertex that has defined x, y location. For instance, a road or a stream may be represented by a line. Lines: Lines are composed of many (at least 2) vertices, or points, that are connected. Examples of point data include: sampling locations, the location of individual trees or the location of plots. Points: Each individual point is defined by a single x, y coordinate. The organization of the vertices determines the type of vector that you are working with. Vector data are composed of discrete geometric locations (x, y values) known as vertices that define the “shape” of the spatial object. ![]() If you wish to dive more deeply into working with spatial data, check out the intermediate earth data science textbook chapter on spatial vector data. This lesson is an introduction to working with spatial data. Plot a shapfile in Python using Geopandas - gpd.plot().Open a shapefile in Python using Geopandas - gpd.read_file().Describe the characteristics of 3 key vector data structures: points, lines and polygons.Learning ObjectivesĪfter completing this lesson, you will be able to: You will also learn how to open, explore and plot vector data using the Geopandas package in Python. In this lesson, you will be introduced to the spatial vector data structure and the shapefile file format (. ![]()
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