GEOB 373 Spatial Resolution of remotely sensed data

Spatial Resolution

Of the four 'resolutions' that describe remotely sensed imagery, spatial resolution is the one that receives the greatest attention, not surprisingly since it is the one characteristic that is most apparent to most people (e.g., zooming into a Google map). Furthermore, spatial resolution interacts with a number of other image characteristics (e.g., the interaction between the pixel resolution and the object's pattern). As such, developing an understanding of how spatial resolution is defined, how it interacts with the other resolutions and object characteristics, and what spatial resolution is required for a particular application, is important.

Satellite Sensors, Application Scale and Urban Objects

(m)	Resolution	Application Scale	Urban Object	RS Sensors
0,1 – 0,5	extremely high resolution	1:500–1:5.000	individual person, roof structure, manhole duct cover	airborne sensors: ADS, DMC, Ultracam
0,5 – 1,0	very high resolution	1:5.000–1:10.000	street lines, car, garage, small building, bush	satellite sensors: Worldview pan, GeoEye pan
1 – 4	high resolution	1:10.000–1:15.000	tree, building, truck, bus	satellite sensors: Quickbird ms, GeoEye ms
4 – 12	medium resolution	1:15.000–1:25.000	complex, large building, industry, commercial	satellite sensors: RapidEye, IRS pan, SPOT 5
12 – 50	moderate resolution	1:25.000–1:100.000	vegetation cover, settlement types & pattern, urban structure	satellite sensors: Landsat TM, ETM+, ASTER
50 - 250	very low resolution	1:100.000–1:500.000	urbanized areas regional level	satellite sensor: Landsat MSS, MODIS
> 250	extremely low resolution	< 1:500.000	urban national level	satellite sensors: MODIS NOAA AVHRR, Meteosat

(A copy of Table 1 from Mapping metropolitan growth from space by Matthias S. Moeller.)

Some useful links:

Characterization of satellite imagery, as presented by the US Satellite Imagery Corporation -- they provide some clear examples of spatial and temporal resolution issues, as well as an explanation of nadir and othorectification of satellite imagery. A demo of the GeoEye satellite 'in action'.
The Canada Centre for Remote Sensing's tutorial on spatial resolution (includes a good discussion on IFOV).
Mapping metropolitan growth from space, wherein a good discussion of spatial and the need for higher radiometric resolution is presented.
An interactive comparison of spatial resolution from MODIS (500 m), Landsat (30 m) and Ikonos (4 m).
An interactive demonstration of what a sensor sees (aka mixed pixels).
Satellite sensors in science education: an interactive examination of the pixel 'footprint', and of spatial resolution. (Click through to see other related demonstrations.)
Satellite swaths (a movie), and satellite orbits (a movie)
Notes on aliasing in remotely sensed images (a description of aliasing; an interactive demonstration of aliasing)
An explanation of RGB to HSI conversion used to pan sharpen an image. (An example of how one software vendor describes the process.)

Text: Chapter 2.5.1: Sensing properties

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