![]() Satellite imagery is a perfect example, very sensitive cameras image. Raster data is a consequence of how the data was first collected. Data is always represented as a grid but not necessarily a rectangular grid. Now let's think about raster GIS data sets. We also need to use vector GIS data sets to create choropleth, as the only way to represent country or any geospatial boundary is with a smooth line. We use vector GIS to represent precise locations and use them for creating geo scatter plots. Vector GIS data sets are composed of points and or lines. This means that calculating overlaps always results in an overestimate of the true area. Whereas in a raster world, everything is represented as a grid. ![]() This means that we can also precisely calculate the area that they overlap. In the vector GIS world, the range of our masks is the perfect circle. This problem can be represented in either vector or raster world. Let's imagine two cell towers or radio masks and how to range of these towers overlap. And finally, you'll need to be able to understand which type of data you have. An ability to tell when data has to be vector or raster. An understanding of why rater and vector data sets are different. There are three things I need you to take away with this video. And finally you'll use completely different data visualizations to communicate information about these data types. You need to analyze or wrangle these data sets differently, which means different R packages. Fundamentally, they're stored in different formats, which means different file types. You need a completely different workflow for vector and raster GIS data sets. GIS data comes in two completely different flavors, vector or raster.
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