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Get up and running with ArcGIS, a true geographic information system (GIS) that allows you to dig into highly accurate geospatial data in a way other mapping applications can't compete with. It's great creating maps, analyzing data for land use studies and other reports, and preparing data for use in an application or database. Let Adam Wilbert show you how to display, analyze, and illustrate geospatial data with ArcGIS. He explores how to import data from multiple sources, manage it with the ArcGIS catalog, and then start making maps. Learn how to lay out your data in the ArcMap component; add symbols, scale bars, and legends; and get your maps out of ArcGIS and into the real world, whether it's for printing or export to another application.
The geospatial data that you will be working with can commonly be categorized into two distinct groups or storage formats. The first kind of data that I want to talk about is stored as a vector format. Vector data is categorized by three classes of features that all revolve around storing coordinate pairs, points, lines, and polygons. Coordinates can be latitude longitude pairs. Or use some other coordinate system, such as a distance in feet or meters from a known location. The simplest vector data element is a single coordinate pair that describes a single point. Think of point data as a push pin that you stick in the map.
With point data you can locate cities on small scale maps, like a wall poster of the United States. Or individual features in a community, like fire hydrants, or manhole covers. Point data is also useful for tracking purposes. Say a fleet of delivery vehicles, or the current location of a plane as it flies across the country. Or for identifying the location of natural or cultural events. If you have two or more points, you can connect them to a line feature. Lines are perfect for describing boundary lines. On maps, we have all kinds of boundaries. From the borders between countries, down to voting or Census district within a city, to lot lines between neighboring parcels of land.
Lines are also useful for routing information, the most obvious being a road network, or delineating bus routes. And finally, if you have enough points to surround an area, you create polygon features. Polygons are great at describing any features that take up space on the ground. They can also accommodate features of any scale. Think of a county or a state or a country or so forth. On larger maps, polygons are useful for describing city limits, or the footprints of a building. By far the most common way to store vector data is the Esri Shapefile. And it's been around since the early 1990s. The shapefile format has experienced widespread adoption because it has relatively simple structure that can be used nearly every GIS out there.
The shapefile is actually composed of at least three separate files on the hard drive that work together to provide and store data. The file extentions shp, shx, and dbf. The shp component is the actual shape or geometry portion of the data. The shx file is a spatial index that organizes the individual shapes. And the dbf file is a database file that stores attribute values about the shape. Shapefiles can also have additional files mixed in to the package, including the projection, a coordinate system of the data that was created, and files that store metadata about when the shape file was created, by whom, and for what purpose.
It's important to note that shape files can only store a single type of data, either point, line, or polygon at a time and shape files can only store straight edges. So if you're trying to saw a curved feature into shape file you'll have to approximate the shape with a lot of little straight edges. Other sources of vector data include computer aided design or CAD drawings such as those created by architects and civil engineers. Or spreadsheets or other tabular data sources containing data points and location attributes. A geodatabase is a collection of related data that can be linked together to ease editing procedures and for organizing projects and are another common source of vector data.
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