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This final page concentrates on various floods that were well monitored by space sensors.


Mapping the Extent of Flooding

This kind of information was a factor in predicting the major flood in the northern Midwest, late in the Spring of 1997. Satellite imaging gave a critical look at the great floods on the Red River in North Dakota and Manitoba (Canada) that inundated Grand Forks, Fargo, and other towns along the state's border with Minnesota.

A color composite made from three NOAA AVHRR bands imaged the flood on April 27, with light gray representing the water and orange depicting clouds:

Colorized NOAA AVHHR image of a flood at Grand Forks, Fargo, April 27 1997.

Spring flooding is frequent in parts of the Mississippi River basin. A hundred-year flood, i.e., largest expected statistically in a 100-yr span resulted from snow melt and rain in late March of 1973. This Landsat-1 subimage (with an earlier pre-flood view) captured the extent of flooding on a cloud free day, showing St. Louis, Missouri (protected from downtown flooding), and the flood plains of the Mississippi, Missouri (joined at A), and Illinois (at B) rivers:

 Left view: Landsat-1 false color composite of St. Louis, MO, and the Mississippi, Missouri, and Illinois Rivers in normal flow; right view: same area experiencing a 100-year flood in March, 1973.

Twenty years later, the Midwest again flooded, worse than before. After several months of excessive rain that saturated the soil, because of a blocking high pressure system that kept the jet stream relatively stationary, in late July and August of 1993, water levels rose well above flood stage. Areas hardest hit were from Iowa to southern Illinois. Levees broke, inundating tens of thousands of acres. The '93 flood became the costliest in U.S. history (some estimates approach $15 billion). Satellite imaging played a key role in getting a number of good images of the flooded area. An indication of how experts in the Weather Service, the Corps of Engineers, etc. go about studying this flood and other floods is found at this Earthsat Web Flooding site.

Once again we examine the lowlands northwest of St. Louis. One image taken by Shuttle astronauts, using SIR-C, appears on the top. On the bottom is an image of merged JERS-1 radar and a SPOT 3-band composite, which offers considerable detail (notice how farmlands show through the water).

Color SIR-C radar image of a flood in the lowlands northwest of St. Louis, Missouri, August 1993.

Merged color JERS-1/SPOT-3 image of a flood in the lowlands northwest of St. Louis, Missouri, August 1993.

14-41: Which year does the Mississippi flood seem worse? Why isn't St. Louis flooded? ANSWER

Up river during the same 1997, the SAR radar on ERS-2 showed the flood (mostly black tones) near Dubuque, Iowa:

Flooded land in eastern Iowa, inundated in the 1997 flood, as imaged by the ERS-2 radar.

The next image is a Landsat-1 subscene (February 6, 1974) of the Barcoo River in Queensland/South Australia, flooded by Fall rains. The floodwaters have spread greater than 50 km (31 mi) wide in these low-lying plains, with low rolling hills.

Landsat-1 subscene image of a flood of the Barcoo River in Queensland, South Australia, February 6 1974.

The Yangtse River in China underwent a major flood in August of 1998. Millions were driven from their lowlands homes. In this unusual image, an ERS-1 radar image taken during June of 1993 is joined with an ERS-2 radar image taken on August 1, 1998, providing a multitemporal or change detection rendition. Both blue and red associate with flood waters.

A multitemporal radar image using a ERS-1 June, 1993 view of an area along the Yangtse River registered with a ERS-2 August 1, 1998 scene of the same area.

Finally, check this map showing areas with high soil moisture, a condition that bespeaks of water saturation from earlier heavy rainfall or from previous flooding. This soil wetness map shows much of Asia; maps of all the continents plotting this parameter are made by NOAA/NESDIS.

 A Soil Wetness Index map for June 2000 made from NOAA satellite observations over much of Asia.

This lengthy Section 14 purports to convey that the principal use of remote sensing remains surveillance of weather systems and oceans on local-to-global scales. We report this because of the widespread occurrence of water on the Earth's surface (even greater than the 70+% ocean surface area, stated on page 14-1, if we include the Antarctic ice [which stores more than 80% of the world's {frozen} fresh water] and Greenland.

At this point in the Tutorial, we have examined most of the specialized modes of remote sensing (defined by the electromagnetic spectral regions we can use), the spacecraft systems that mount the sensors, and the numerous applications to which these sensors have contributed. In the next Section (15), on Geographic Information Systems (GIS), we look at some systematic ways to integrate remote sensing data into organization, correlation, interpretation, and management of geographically-referenced information. Then, in Section 16, we look ahead to the next generation of remote sensing programs, in which individual satellites will simultaneously make meteorological, oceanographic, land surface, and biologic observations to present a unified picture of Earth as a System.

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