Which Characteristics Below Are Unique To Raster Data? (Choose Two.)

A geodatabase is a database that is in some style referenced to locations on the globe. Coupled with this data is normally information known as attribute data. Attribute data more often than not defined as additional information, which can and then exist tied to spatial information.

What types of GIS Data are there?

GIS information can be separated into two categories: spatially referenced data which is represented by vector and raster forms (including imagery) and aspect tables which is represented in tabular format.

Within the spatial referenced data group, the GIS information can exist further classified into 2 different types: vector and raster.

Most GIS software applications mainly focus on the usage and manipulation of vector geodatabases with added components to work with raster-based geodatabases.

Vector information

Vector data is split into iii types: betoken, line (or arc), and polygon data.

Point Data

Bespeak data is most ordinarily used to correspond nonadjacent features and to represent discrete data points. Points take zero dimensions, therefore you can measure neither length or area with this dataset. Examples would exist schools, points of interest, and in the example below, bridge and culvert locations. Point features are also used to correspond abstruse points. For instance, point locations could represent metropolis locations or identify names.

Line Data

Line (or arc) data is used to stand for linear features. Mutual examples would exist rivers, trails, and streets. Line features only have 1 dimension and therefore tin simply be used to measure length. Line features take a starting and ending point. Mutual examples would be road centerlines and hydrology. Symbology most usually used to distinguish arc features from one another are line types (solid lines versus dashed lines) and combinations using colors and line thicknesses. In the example below roads are distinguished from the stream network by designating the roads as a solid blackness line and the hydrology a dashed blue line.

Polygon Data

Polygons are used to stand for areas such as the boundary of a metropolis (on a big scale map), lake, or forest. Polygon features are ii dimensional and therefore can be used to measure the surface area and perimeter of a geographic feature.

Polygon features are almost usually distinguished using either a thematic mapping symbology (color schemes), patterns, or in the example of numeric gradation, a color gradation scheme could be used.

Both line and point characteristic data correspond polygon data at a much smaller scale. They help reduce clutter by simplifying data locations.

Equally the features are zoomed in to, the point location of a school is more realistically represented past a series of edifice footprints showing the physical location of the campus.

Line features of a street centerline file only represent the physical location of the street. If a higher caste of spatial resolution is needed, a street curbwidth file would be used to show the width of the route as well as whatever features such every bit medians and right-of-ways (or sidewalks).

Raster Data

Raster data (also known as grid information) represents the quaternary type of feature: surfaces. Raster data is cell-based and this data category also includes aerial and satellite imagery.

Continuous and Detached Raster Information

There are two types of raster data: continuous and discrete. An case of discrete raster data is population density. Continuous data examples are temperature and elevation measurements. There are also three types of raster datasets: thematic data, spectral data, and pictures (imagery).

Digital Elevation Model (DEM) showing elevation in shades of red and pink. — Digital Height Model (DEM) showing peak.

This example of a thematic raster dataset is chosen a Digital Elevation Model (DEM). Each cell presents a 30m pixel size with an summit value assigned to that prison cell. The area shown is the Topanga Watershed in California and gives the viewer and sympathise of the topography of the region.

This image shows a portion of Topanga, California taken from a USGS DOQ. — This prototype shows a portion of Topanga, California taken from a USGS DOQ.

Each cell contains one value representing the dominate value of that cell. Raster datasets are intrinsic to most spatial analysis.

Spatial hydrology modeling such every bit extracting watersheds and flow lines also uses a raster-based system. Spectral information presents aerial or satellite imagery which is so often used to derive vegetation geologic information by classifying the spectral signatures of each type of feature.

What results from the consequence of converting spatial data location data into a cell based raster format is chosen stairstepping. The name derives from the image of exactly that, the square cells forth the borders of different value types look like a staircase viewed from the side.

Unlike vector data, raster information is formed past each cell receiving the value of the characteristic that dominates the cell. The stairstepping expect comes from the transition of the cells from one value to another. In the image to a higher place the dark green jail cell represents chamise vegetation. This means that the boss feature in that cell expanse was chamise vegetation. Other features such as developed land, water or other vegetation types may be present on the ground in that expanse. As the feature in the jail cell becomes more dominantly urban, the cell is attributed the value for developed land, hence the pink shading.

Data analysis such as extracting slope and aspect from Digital Elevation Models occurs with raster datasets.

This 10 meters shaded relief was developed from downsampled SRTM Plus elevation data. Source: Natural Earth Data. — This 10 meters shaded relief was developed from downsampled SRTM Plus tiptop information. Source: Natural Earth Data.

Zoom in close on a raster dataset and you volition be able to see the private cells.

Zoom in closely to a raster dataset and you will see the individual cells. Image: Grayscale shaded relief of land areas derived from downsampled SRTM Plus elevation data. Source: Natural Earth Data. — Zoom in closely to a raster dataset and yous will see the individual cells. Image: Grayscale shaded relief of land areas derived from downsampled SRTM Plus elevation data. Source: Natural Earth Information.

Raster Images

Aerial and satellite imagery is one blazon of raster data. Raster epitome file types include BMP, TIFF, GIF, and JPEG.

Raster images accompanied by a second file known as a world file. The earth file has the same name as the raster image file just has a different extension. The world file is a text file that contains the map projection data needed to properly georeference the raster image.