Finding and Using GIS Data

1. Introduction
2. Types of Resolution
3. LiDAR
4. Data Sources

Satellite Imagery, Aerial Photography, and Other Rasters

While GIS data commonly involves features such as points, lines, and polygons (known collectively as the vector data model), satellite imagery, aerial photography, and other datasets such as elevation and land cover is represented in GIS through the raster data model.

Finding raster data is much like finding vector data, but there are some unique aspects that you will need to keep in mind:

• Raster data is made up of cells, often squares, that completely cover the area of interest.  These cells or pixels are assigned some value such as elevation, category of land use, or a color value.
• Resolution and scale are very important for raster datasets--a value called cell size is used to determine how much physical space on the ground is represented by a single pixel.
• Complex raster datasets can be organized into multiple bands representing different variables along a similar theme.  For example, a LandSAT true-color image is compiled from the Red, Green, and Blue bands of the image.  The value assigned to each value is the intensity of the red, blue, or green light received by the sensor.

It's also important to remember that this model of storing data can occupy much more space on your hard drives or cloud storage.  Since a single image can contain hundreds-of-thousands or even millions of pixels, it is not uncommon to work with high resolution raster datasets exceeding the storage capability of your laptop or workstation.  Data management is critical.

Types of Resolution

Spatial resolution
The size of a pixel that is recorded in a raster image – typically pixels may correspond to square areas ranging in side length from 1 to 1,000 metres (3.3 to 3,280.8 ft).

Spectral resolution
The wavelength of the different frequency bands recorded – usually, this is related to the number of frequency bands recorded by the platform. Current Landsat collection is that of seven bands, including several in the infrared spectrum, ranging from a spectral resolution of 0.07 to 2.1 μm. The Hyperion sensor on Earth Observing-1 resolves 220 bands from 0.4 to 2.5 μm, with a spectral resolution of 0.10 to 0.11 μm per band.

Radiometric resolution
The number of different intensities of radiation the sensor is able to distinguish. Typically, this ranges from 8 to 14 bits, corresponding to 256 levels of the gray scale and up to 16,384 intensities or "shades" of colour, in each band. It also depends on the instrument noise.

Temporal resolution
The frequency of flyovers by the satellite or plane, and is only relevant in time-series studies or those requiring an averaged or mosaic image as in deforesting monitoring. This was first used by the intelligence community where repeated coverage revealed changes in infrastructure, the deployment of units or the modification/introduction of equipment. Cloud cover over a given area or object makes it necessary to repeat the collection of said location.

LiDAR

What it is: LiDAR (Light Detection And Ranging) is an exciting and rich data source for analyzing surface features. This data is created with laser light which creates dense samples and highly detailed surface elevation values. The data collection process can return multiple layers for a single point, representing, for example, a tree top and the bare earth below. Applications of this type of data include measuring heights between points, developing flood plain models, generating DEMs and DSMs, estimating forest density and height, and many more.

Data format: LiDAR point cloud data can be represented as a series of rasters or TINs, a LAS dataset, a mosaic dataset, or a terrain dataset. For an introduction to using LiDAR data in ArcGIS, see ESRI's Fundamentals about LiDAR page.

Things to consider: LiDAR data files are often exceptionally large. Before attempting to access this type of data, you should consider the resources needed to work with it, both in terms of available memory and system processing speed. Often when a GIS project involves terrain analysis, a DEM (Digital Elevation Model) or similar type of file (which are comonly derived from LiDAR data) may be sufficient and put a great deal less strain on your resources.

Data Sources:

• LiDAR data is available from the AGS Library for a limited number of counties in Wisconsin. (Be aware that special arrangements may be required to transfer large data sets.)
• Increasingly, LiDAR data is available from online sources. The United States Interagency Elevation Inventory is a resource for finding agencies which host this type of data and is searchable by geography. (Note: This site does not appear to receive regular maintenance, so some links may no longer be active.)

The Contents of Finding and Using GIS Data may be reused with attribution for Non-Commercial purposes.

Finding and Using GIS Data by Board of Regents of the University of Wisconsin System is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License.