Fundamentals of GIS: Vector vs. Raster
At the heart of GIS lie two primary types of data: vector and raster. These data types serve as fundamental building blocks, each offering unique capabilities and applications within the GIS framework.
Vector data represent spatial features such as discrete points, lines, and polygons, each associated with tabular data attributes. On the other hand, raster data represent information as a grid of cells, where each cell contains an attribute value. This distinction between spatial features and tabular data attributes is crucial in understanding GIS data structures.
While vector data capture the geometry of geographic features along with their corresponding attribute data, raster data represent spatial phenomena through a grid-based approach, enabling the storage of continuous data such as elevation or temperature across the landscape.
Vector layers
Vector layers are a cornerstone of Geographic Information Systems (GIS), serving as the foundation for representing geographic data in digital form. These layers delineate spatial features such as points, lines, and polygons, enabling the visualization and analysis of complex geographical phenomena.
Among the most widely used formats for storing vector data is the Shapefile format, known for its compatibility and ease of integration within GIS software suites. However, with the rise of web mapping applications, formats like GeoJSON have gained prominence for their lightweight and human-readable structure based on JavaScript Object Notation (JSON).
This diversity in vector data formats underscores the adaptability and versatility of GIS technology, catering to a wide range of needs and applications.
Rasters
Raster data, another essential component of GIS, presents geographic information in a grid-like format consisting of cells, each holding an attribute value. Unlike vector data, which represents spatial features discretely, raster data represents continuous or categorical information across a spatial extent.
Continuous raster data, exemplified by aerial photographs or elevation models, captures gradual changes in geographic phenomena across the grid cells. These continuous surfaces derive their values from fixed reference points, such as sea level in elevation models, allowing for precise analysis of topographic variations.
In contrast, discrete raster data categorizes pixels into specific thematic classes, such as land cover types or soil classifications. Unlike continuous data, discrete raster values are constrained to predefined classes, facilitating clear delineation between different thematic categories and enabling detailed land cover analysis.
If you’d like to learn more about Geographic Information Systems, we’ve published more of this series on the Fundamentals of GIS on YouTube.
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