Geog 258: Maps and GIS

Remote Sensing

Principles

January 18 (Wed)

Reading: Text Chapter 9

Complementary readings: Bolstad 2005 and NASA online tutorial

Remote Sensing and Maps

Seen from mapness continuum: less abstraction (cf. topographic map) see I.3 (p. 6)

Seen from map-making process: indirect experience (cf. ground survey)

Maps can lie along different mapness continuum based on varying elements of three defining characteristics of map (map scale, map projection, and map abstraction); image of the earth is the important source of maps

Maps can be made through either direct experience or indirect experience, and actually through both; map-making requires ground survey (determining the location of the earth; which again requires the full knowledge of the earth – how it looks and how the location in the earth can be measured, which is the subject of next week or so; see chapter 1, 3, 4, 5). With the invention of aircraft and spacecraft, it became possible to observe the earth remotely with a large geographic coverage.

Map-making through direct experience (Ground survey)

Map-making through indirect experience (Remote sensing)

Principles of Remote Sensing

Why is the tree green?

To see something, we need three elements: object (e.g. tree), energy source (e.g. sun light), and sensor (e.g. human eye). When light strikes object, energy from the light is either reflected or absorbed by the object (Figure 9.2). The amount of reflected energy is the color perceived by your eye for example.

What you see is in essence electromagnetic energy reflected by object where the energy travels in the form of different wavelengths (→ electromagnetic spectrum). If the energy in green spectrum is more reflected by the object than energy in other spectrum, it appears green. See Figure 9.1

Electromagnetic spectrum can be divided into spectral bands. Humans can only see visible light between 0.4 and 0.7 micrometer (millionth of 1 meter) in terms of wavelengths.

In remote sensing, sensor is camera in aircraft or electronic recording instrument built in artificial satellite, producing aerial photo and satellite imagery, respectively.

Pixel values in the image represent the amount of electromagnetic energy reflected by the object given spectral bands. The amount of electromagnetic energy reflected by the object differs across electromagnetic spectrum (→ spectral signatures) See Figure 9.3

Spectral bands determine how geographic features look; the amount of electromagnetic energy reflected by the object varies as a function of varying wavelengths (i.e. spectral signature).

Combination of any 3 of the 7 bands on TM (Thematic Mapper: main sensor on Landsats 4 through 7) can be assigned to one of the three primary colors: blue, green, red to yield a color composite. If RGB is assigned to corresponding wavelengths respectively, a color composite yields true-color image. Otherwise, it yields false-color image.

True-color image

See Plate 9.6

Why does vegetation appear red?

Because infra-red band (band 7) is assigned to Red layer, and healthy vegetation exhibits high intensity of reflected energy (shown in Figure 9.3). High intensity is translated into very red color.

Not all of reflected energy reaches the sensor. Certain wavelengths couldn’t penetrate water vapor (clouds), carbon dioxide, ozone, and solid particles (dust for example). Infrared and microwave provides transparent atmospheric window (see Figure 9.4), opening the potential for developments in active sensor system such as Radar imaging (RADAR uses microwave).

Three Key Aspects of Resolutions of Remotely Sensed Imagery

Look at description of satellite image or aerial photo in EROS Data Center

· Spatial: pixel size (digital) or grain size (film)

· Temporal: how often (time interval) the image is updated

· Spectral: which spectral bands, how many spectral bands

These three resolutions are important considerations for determining the fitness of use of data