Remote Sensing  » Spatial Analysis

Resolution
The resolution of an image refers to the potential detail provided by the imagery. In remote sensing we refer to three types of resolution: spatial, spectral and temporal.
Spatial Resolution refers to the size of the smallest feature that can be detected by a satellite sensor or displayed in a satellite image. It is usually presented as a single value representing the length of one side of a square. For example, a spatial resolution of 250m means that one pixel represents an area 250 by 250 meters on the ground.
Spectral Resolution refers to the ability of a satellite sensor to measure specific wavlengths of the electromagnetic spectrum. The finer the spectral resolution, the narrower the wavelength range for a particular channel or band.
Temporal resolution refers to the time between images. The capability for satellites to provide images of the same geographical area more frequently has increased dramatically since the dawn of the space age.

Contouring
Meteorologists, oceanographers and geologist all use contour analysis to visually explain the information that images and data is providing. Contouring data is an elementary step in spatial analysis. The ability to correctly and confidently analyze data is critical to interpreting conditions.  Contouring is vital for finding the location of atmospheric and oceanic fronts, locating potential regions of severe thunderstorms, tracking hurricanes, tracking the movement of pollutants and tracing water movement in the oceans.

Color-Coding and Color Enhancements
Another way to delineate data on maps and images is to color code salient features such as different rock types, a range of temperatures, or any type of information where it would be useful to convey visually by adding colors.
The image to the right clearly shows the warm gulf stream waters in orange and red and numerous eddies mixing with cooler ocean waters as the entire current moves up the east coast of the United States before veering off towards Europe.

gulf stream
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Overlaying Data
It is common to add information to images and maps by overlaying related fields of data. The information can be lines of equal pressure (isobars) or equal temperature (isotherm), surface weather observations, wind fields, or geographical data. A topographic map is a common example, when topography lines are closer together you can expect to be walking on steeper terrain. Overlaying related information on maps or imagery allows for spatial analysis on multiple levels with convenient visual displays.

Spatial Analysis and Geographic Information Systems (GIS)
The term Geographic Information System (GIS) is applied to software programs that perform computational analysis of data and phenomena by georeferencing data to the Earth’s surface. GIS software supports spatial visualization of variables with graphs and maps in order to identify patterns of spatial dependency in the phenomenon under study.