<aside> ℹ️ Here you can access all educational resources including slides, map, exercise files, etc., for teaching purposes.
</aside>
Slides:
https://drive.google.com/file/d/1ugixJ9XxXsK260X2L1rmZewWm7n6442W/view?usp=sharing&utm_source=notion&utm_medium=referral&utm_campaign=edu_4
Raster data, integral to geographic information systems (GIS), are gathered from diverse sources, including aircraft, drones, satellites, sensors, digital pictures, and scanned maps. These data can be acquired through various means, such as computer processing, camera imaging, or sensor technology.
Some of the primary methods of acquiring raster data are aerial photography, satellite imagery and scanned maps. Aerial photography involves capturing images from drones or aircrafts, which are then imported into a computer and georeferenced. Satellite imagery, on the other hand, is obtained when satellites equipped with specialized digital cameras capture images of the Earth's surface as they orbit. Additionally, scanned maps serve as another valuable source of raster data, providing historical and detailed geographic information.
Drawing describing the diverse origins of raster data: from aerial shots or scanned maps to satellite captures.
Scanned map raster of a 1969 map by Richard Edes Harrison, featured in the National Atlas of the USA by USGS. Access the map using this link.
The process of obtaining raster data from aircraft or satellites involves sensors onboard these platforms capturing information about the Earth's surface. This method, known as remote sensing, enables the acquisition of various types of raster data, including continuous data like elevation models.
Raster data can also be generated through computational methods. This process can involve converting vector data into raster format, where each point in the vector layer corresponds to a pixel in the raster layer, inheriting its attribute value. Conversely, raster data can be converted back into vector format, where each pixel in the raster layer is sampled to generate point, line, or polygon features.
Digital elevation model (DEM) showcasing Mexico City's topography, providing valuable insights into its terrain features and variations. Access the map using this link.
Visualization of elevation data in QGIS: a raster map displaying a digital elevation model (DEM), with sampled pixel centroids representing elevation values from the raster file. This process demonstrates the capability of QGIS tools to perform conversion both ways, from raster to vector point layer and vice versa.
Rasters are matrices of pixels organized into rows and columns, each representing data such as image reflectance, landcover, elevation, or temperature. Pixel values in rasters can be positive or negative, integer or floating point. Integers suit categorical data, while floating points are for continuous surfaces. Pixels can also have a NoData value to indicate data absence.
Each pixel represents an equal portion of the entire image surface, ensuring uniform width and height. The pixel size indicates the raster resolution, while the total number of pixels in the matrix and the area they cover is referred to as the raster coverage or extent.
Pixel dimensions can vary from square kilometers to square centimeters, ensuring accurate representation of the surface and its features. This flexibility provides the necessary level of detail in the image depending on the scale of use.
Illustration depicting the fundamental concepts of raster data such as coverage and raster resolution.