ABCs of DEW Software chapter 7:

Temporal Analysis
of Satellite Images

 Las Vegas in 1986
 Las Vegas in 1992

The word temporal means “of or relating to time.” The images of Dallas at the end of the previous chapter show how satellite images captured at different times can reveal very important things to us.

These images show the rapid growth of Las Vegas, Nevada. This is by far the fastest-growing metropolis in the United States. The population grew in the last century as follows:

1964: 127,000 1986: 608,000

1972: 273,000 1992: 863,000

1997: 1,124,000

These are the same kind of standard false-color images that appear throughout Earthshots (http://edcwww.cr.usgs.gov/earthshots), simulating color-infrared aerial photographs. Remember “R-G-B = IR-R-G”: red, green, and blue in the image represent how much infrared, red, and green solar energy the ground reflects.

As the city expands you can see a sort of landcover succession through human construction.

  • Pre-construction land appears medium gray-green indicating sparse desert vegetation, reddish soils, and stone.
  • Construction land appears brighter. Bulldozed soil, bare of vegetation, is very reflective.
  • A young neighborhood appears medium green (medium green) again, perhaps a bit brighter from all the reflective pavement and roofs. The trees are small, and some developments now conserve water by landscaping with rock and desert plants rather than grass.
  • An old neighborhood appears dark, brownish red, from the mature trees and more grass.
  • Golf courses appear bright red because they are the most intense vegetation.
  • Water appears almost black because at this angle it scatters little light back to the Landsat sensor.

Satellite images

The 1972, 1986 and 1994 scenes are from the NALC dataset.

LM1042035007225790 (Landsat 1 MSS, 13 September 1972)

LM5039035008625390 (Landsat 5 MSS, 10 September 1986)

LM5039035009225490 (Landsat 5 MSS, 10 September 1992)

 Chernobyl, Ukraine, 1986
 Chernobyl, Ukraine, 1992

A devastating nuclear accident happened at Chernobyl, Ukraine, on 26 April 1986. These images show the area around the nuclear power plant approximately one month after the accident, and six years after the accident. This area is near the common borders of Ukraine, Belarus, and Russia.

The images clearly show farm abandonment. Agriculture appears as a collage of bright red (growing crops) and white (highly reflective bare ground). Many of these areas appear a flat tan-green in 1992, indicating natural vegetation which has taken over the abandoned fields. While the reactor was still on fire, all settlements within 30 km were evacuated, including Pripyat (1986 population 45,000), Chernobyl (1986 population 12,000), and 94 other villages (estimated total population 40,000). As of 1992, this area remained almost completely abandoned.

The radiation also affected wild plants and animals around Chernobyl. Pine forests soon died, cattails grew three heads, and wild animals declined in number. But in the coming years, as the short-lived radionuclides decayed and the longer-lived contaminants settled deep into the soil, the wildlife rebounded. Human abandonment also made habitat available for birds, deer, rodents, wolves, boar and other animals. These populations appear to be increasing despite the extraordinarily high mutation rates caused by contamination in the food chain and by one of the highest background radiation levels in the world.

Satellite images

LT5182024008615110 (Landsat 5 TM, 31 May 1986)

LT4182024009220810 (Landsat 4 TM, 26 July 1992)



NDVI: A Measure of Vegetation

One way to identify different surface covers has been to compare the intensity of the infrared to the visible light being reflected from the Earth’s surface. An early technique was to subtract the visible red from the infrared intensity. Since vegetation reflects more IR than visible light, the difference between IR and red is an indication of vegetation cover—a sort of “Difference Vegetation Index.” This works well for ground without steep slopes, but for steep surfaces, there is a shadow effect: some areas reflect different intensities of light just because of their slope. But the percent of light reflected is the same, regardless of the intensity of light, so one way to eliminate the shadow/slope problem is express the Difference Vegetation Index as percent by dividing the difference between IR and red intensities by the total light being reflected. This technique is called normalization, and the scheme, which is commonly used to identify the amount of vegetation cover, is called the “Normalized Difference Vegetation Index” or NDVI.


Normalized Difference Vegetation Index formula
 Investigation
Use VegetationAnalysis software to observe and measure changes in Mt. St. Helens before and after the great eruption of 1980.


 For new material relating to this chapter, please see the GSS website “Staying Up To Date” page:
http://www.globalsystemsscience.org/uptodate/dew/ch7


Subpages (1): 7-1. Mt. St. Helens
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