Impact of Climate Change and Land Use on the Southwestern United States

Impacts of climate change on life and ecosystems

Southwest U.S. Change Detection Images from the EROS Data Center

Reno and Lake Tahoe, Nevada

by Kristi Sayler, U.S. Geological Survey

A matched pair of satellite images from different years can be processed into a new change-detection image, which shows areas of increased or decreased brightness, greenness, or wetness. These images can be used to monitor landscape changes. These images of the Reno-Lake Tahoe area of Nevada, show some effects of natural processes on the landscape:

Burn area
Extensive changes resulting from forest fires can be observed in satellite images. Changes in greenness, displayed here as a dark blue color, show an area of vegetation which has become blackened from burning.
Conifer mortality
Scientists at Boston University have made ground measurements to quantify the decrease in the forest canopy as a result of drought. The sustained drought conditions weakened the trees and made them more susceptible to insect attacks. Satellite images can be used to estimate the geographic extent of the damaged area.
Forest clear-cutting
Droughts increase the geographic extent of exposed lakebeds, where new vegetation can be seen using satellite images. Changes in land use or timber harvesting activities can also be seen in this forested area.
Dry lake
These images were taken at the beginning and culmination of drought conditions in the western U.S. A broad shallow lake that was full of water in 1986 was empty, and the entire lake bed exposed, in 1992.
Reno/Lake Tahoe 8-5-1986Reno/Lake Tahoe 8-5-1992
Reno 8-5-1986 Reno 8-5-1992
Change from 1986 to 1992
Reno 1992 - 1986

How these images were produced

The change detection contained in the following pages is done using Landsat multispectral scanner (MSS) and thematic mapper (TM) data to identify and characterize landscape change. The change analysis procedure involves:
  1. co-registering multiple dates of MSS or TM data,
  2. transforming the imagery to scene-based measures of brightness, greenness, and wetness (TM data only),
  3. pairwise differencing of the brightness, greenness, and wetness measures to compute change vectors (magnitude and direction) for each image pixel,
  4. encoding the change vectors using hue, saturation, and value (HSV) for visualization, and
  5. formulating a signal-to-noise model by which to isolate areas of significant change.

color key

The color key, shown here, is the model used to encode the calculated change vectors produced for each pair of images. It can be used to interpret the change images contained within the following web pages. An increase in greenness is shown as green and a decrease in greenness is shown as magenta. A decrease in brightness is shown as various shades of blue and an increase in brightness is shown as orange/red tones. Any combination of brightness and greenness changes will be shown somewhere on the color key. Shades of grey imply no change or change that was not considered significant.

For a more detailed description of the techniques or algorithmns used consult the following conference proceedings article:

Dwyer, J., Sayler, K., and Zylstra, G. 1996. Landsat pathfinder data sets for landscape change analysis. Proceedings of International Geoscience and Remote Sensing Symposium. Lincoln, Nebraska, May 27-31, 1996.

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