Introduction to Geographic Information Systems (GIS)
Vector and Raster Data in GIS
The digital GIS representations of geographic features are called vector and raster data. Vector data are designed for discrete objects and are represented with pairs of x, y coordinates.
- Point features have a single pair of coordinates. Examples include a tree or an electric pole.
- Lines are represented with a start node and a stop node, and usually several vertices between these nodes, all having defined positions (pairs of x, y coordinates). Examples include roads or streams.
- Polygons are features with an outline built as a closed ring, meaning the start node and the stop node of the outline share the same location. Examples include buildings or lakes.
In vector data, each feature has a set of attributes linked to it as a row in the attribute table with defined fields. Vector data can store topology (adjacency, containment) but are treated as being homogenous within each feature.
Raster data are designed for continuous fields and are represented with a regularly tessellated grid of usually square cells. One location in the grid (e.g., the center of the top-left cell) has a reference to real-world coordinates. Each cell usually contains a single value. Raster data creates a complete coverage of the area and is thus good to use for describing elevation or temperature but can also be used for discrete objects such as land cover classes.
- Point features are represented as one cell with data.
- Line features are represented as several adjacent cells in a row.
- Polygon features are represented with one or many cells depending on the cell size (raster resolution).
Topology cannot be stored in raster format.
Advantages of Raster and Vector Data
Raster Data Advantages:
- Simple data structure
- Can store continuous surface data (e.g., temperature)
- Simpler overlay analysis
- Several statistical analysis tools available
Examples include surface analysis (slope, aspect, hill-shade) using elevation data, water-based analysis in catchments, statistical analysis (zonal and focal functions), and weighted overlay.
Vector Data Advantages:
- Exact geometry
- Many attributes for each feature
- Defined topology
- Simpler transformations between coordinate systems
Examples include measuring distance and area, overlay analysis such as buffer and intersect, and network analysis.
Reasons for Projecting the Earth’s Surface
- Printed maps are flat and used as both input and output from GIS.
- Raster data can only represent a flat surface due to its regular structure.
- It is easier to measure distances on a plane surface.
- A plane is needed to be able to see the whole earth in one picture.
Properties of Map Projections
Conformal map projections preserve shapes of small objects. The distortion is the same in all directions (angles), and the projection is therefore good to use for navigation with a compass.
Equal area projections have correct areas, but shapes are distorted, and so are directions. The conformal property cannot be combined with the equal area property, and both types will generally distort distances.
What is Remote Sensing?
Remote sensing is a method for collecting data about the surface of the earth without being in direct contact with its objects, such as with a camera in an airplane or a sensor in a satellite. The three key aspects of resolution are:
- Spatial (ground resolution)
- Spectral (number of spectral bands that are sensed)
- Temporal (how often the sensor passes over the same spot)
Examples of use include meteorological satellites measuring global weather conditions and sea temperatures, land use change detection using data from different years (finding clear-cuts in Swedish forests), detection of pollution in water, and natural disaster assessments (storms, wildfires, tsunamis).
Collecting Geographic Data: Field Sampling
Taking samples in the field is one way of getting reference data for phenomena that are being sensed remotely to calibrate and evaluate the interpretation of sensor data (images). Field samples can also be a check of classifications in maps or GIS data or be samples of continuous field data (forest stand stocking or agricultural soil characteristics) that are used for interpolation. It is cost-efficient to combine available data with field sampling.
Different Passive Sensors
Passive sensors utilize the reflectance of external energy sources (like the sun) or blackbody radiation, whereas active sensors utilize the reflectance of a signal emitted by the sensor-system itself.
Examples of passive sensors:
- Passive infrared satellite-mounted sensors like Landsat, which are used for depicting vegetation.
- Conventional passive digital cameras mounted in airplanes for producing highly resolved reference information (on changing landscapes).
Note: The provided examples also included active sensors (RADAR and SONAR). Only passive sensor examples are listed here as requested.
Estimating Feature Length in a GIS
The length of a real-world feature in a GIS will always be shorter due to generalization. How much shorter is determined by the scale that is used. In a large-scale map, the number of vertices will be greater, and the length of segments smaller than in a small-scale map.
Choropleth Maps, Multivariate Representation, and Cartograms
Choropleth Map: A choropleth map holds a polygon representation where each polygon holds a constant attribute value. For example, a county map of Sweden (nominal scale) or a county-wise representation of inhabitant numbers (ratio scale) are typical choropleths.
Multivariate Representation: In multivariate representation, individual symbols carry multiple attribute values. An example might be a naval chart where current is represented with a field of arrows that are coded for speed with their respective colors and for direction with their respective orientations.
Cartogram: Cartograms are maps that lack planimetric correctness and distort area or distance in the interest of some specific objective. An everyday example is underground or bus-line cartograms, where dwindling lines have been straightened out for the sake of clarity.
Fundamental Elements of a Map Layout
- Title
- Legend
- Scale bar (and/or ratio)
- Projection (and geographic datum)
- Data source (copyright)
- North arrow (if needed)
- Map grid (when using geographic coordinates)
- Author and date
- Inset map (if needed)