URBAN AND LAND USE APPLICATIONS:


Remote sensing tends to orient towards any applications that are of direct and immediate benefit to people and society. Map types that are designed to show both natural and manmade features on which data pertinent to those aims is recorded and from which up-to-date information is easily extracted are referred to as land cover and land use maps. A commonly used land cover classification is presented and an example of a classified remote sensing subimage that displays cover classes is given. Much of this section will concentrate on the appearance of cities and urban areas in space imagery; these images are good starting points for making land use/cover maps. Several urban areas in the U.S. Southwest are examined on this page.


URBAN AND LAND USE APPLICATIONS:

Some Basic Principles and Examples

As strongly hinted at in the first three Sections, space imagery (and aerial photography as well) is a powerful medium for mapping what’s at the Earth’s surface. We can identify and categorize the various natural and man-developed features in terms of land cover. The term land use is almost a synonym, but refers specifically to how the land is used for human activities. Land cover and use maps are an essential input to Geographic Information Systems, described in detail in Section 15. Most of these maps follow some classification system. One in common use is that developed by James Anderson and his colleagues at the U.S. Geological Survey. This hierarchical system has four levels. The two higher ones (Levels I and II) are categories that we can usually identify and hence, map, using space images, whereas, aerial photos (for higher resolution) are needed for Levels III and IV. This classification in Levels I and II is shown here:

Level I and Level II Classifications, US Geological Survey.

To illustrate the subdivisions at Level III, we pick Level I = Urban - and Level II = Residential, then the subdivisions under Level III are: units = Single-Family; Multi-Family; Mobile Homes; Hotels/Motels; and Other. Generally, the finer the breakdown, the more on-site, ground truth information we need. Maps for Levels I and II can be colorized, and we can add numerical symbols (e.g., 115 = Residential Hotels) for individual features on maps with a large enough scale to fit them.

An example of a typical land cover and use map is this U.S. Geological Survey Map of the now-familiar Harrisburg, PA scene. Although the legend lettering is too small for legibility in this Tutorial, suffice to say that a number of Level II categories are mapped. This is a typical example of such ground-based land features mapping (you will see another example in the Final Exam, Section 21).

U.S.G.S. Land Use/Cover Map of Harrisburg, PA and vicinity.

For comparison, here is a multi-theme classification of land use/cover derived from Landsat imagery that maps an area in and surrounding Harrisburg, PA. The city is located next to the prominent yellow pattern assigned to urban. Smaller yellow blotches to the east and west are indications of downtowns, such as Carlisle, Hershey, and Lebanon. This metropolitan area, with a population exceeding 300,000, is generally spread out beyond the Harrisburg city limits. The legend category called “deforestation” describes the same Gypsy Moth defoliation touched upon on page 3-6. Land use/cover mapping with space images such as Landsat, SPOT, JERS, IRS is capable of displaying with good (not excellent) accuracy some of the Level II categories. IKONOS and similar high resolution satellite imagery can pick up many of the Level III units.

Example of a typical land cover classification (map) for an area around Harrisburg, PA.

Students at the University of Arizona have produced an excellent Web site illustrating in a series of well-documented steps the approach they took to classifying land use in a rural part of Cochise County, AZ. They compared Landsat subscenes for two dates, in 1973 and 1992, working towards a change detection map that picks out new features or different uses for some earlier features. Very informative; access it at this site:

For the next three pages, we will concentrate on urban land use by looking at space imagery of a group of U.S. and foreign cities:

` <>`__4-1: As a warm-up and refresher, briefly review how a metropolitan area appears in a standard false color composite. It is sometimes hard to delineate the outskirts of a suburban land use class; suggest one way to roughly decide on its boundary. ** **ANSWER**

Los Angeles, San Diego, Tucson, Las Vegas, San Jose, and Honolulu

Because much of the U.S. and world populations are concentrated in and near metropolitan centers, we concentrate in this Section on urban land uses. After you have run through the first three pages, if your home town or the city nearest you was not covered, search through Other U.S. Cities.

Major metropolitan areas are sprawling, often occupying a significant fraction of a full Landsat scene (although on a world scale,these areas comprise less than 10% of the land surface). This is certainly the case in one of the largest (areawise) urban regions in the world - the Los Angeles megalopolis as seen in a resampled (lowered resolution) MSS image that covers most southern California.

Landsat MSS full scene of the Los Angeles metropolitan area, with the Tranverse Ranges and Mojave Desert to the north.

Major geographic features in this image include the western Mohave Desert (containing Edwards Air Force Base), the southern tip of the Great (San Joaquin) Valley, the Tehachapi mountains on the north (extending from the southern tip of the Sierra Nevada), and the Transverse Ranges north of L.A. (bounded sharply on the north by the infamous San Andreas fault and on the south by the Santa Monica and San Gabriel Mountains). Los Angeles (lower right) lies within a structural basin, forming a lowlands that restricts air circulation and is a natural trap for pollutants (the famed L.A. smog).

` <>`__4-2: Consult an atlas; find the above features and others that you may know about from living in, having visited, or having heard about Southern California. For example, find Hollywood. **ANSWER**

A more detailed look is given in this Landsat-7 subset:

Subscene of much of greater Los Angeles, imaged by Landsat 7.

The IKONOS satellite succeeded quite well in finding Hollywood. In fact, it imaged the famous large white letters that spell out this name against the backdrop of a steep slope on the south side of the Santa Monica Mountains near this most recognized city in the Los Angeles area:

The famed Hollywood sign (near top) as imaged by IKONOS.

The urban signatures in a false color composite are clearly evident in the segment of the MSS image containing a part of the numerous cities and suburbs that makes up the greater Los Angeles regional sphere of influence. The areas of higher population density show two dominant color themes: thin, usually blue to almost black, linear criss-crossing patterns representing streets and roadways; and areas in between that are also usually some shade of blue. The latter are the spectral expression of buildings, which tend to reflect brightest in the blue and green bands. Interspersed within these areas are patches of red, which correspond to city and town parks, cemeteries, golf courses, and pockets of intra-urban agricultural fields. Residential areas often have color signatures ranging from brown to pink to mild red, stemming from the mix of lawns and trees with houses and streets. In the Los Angeles hills and neighboring mountains, signs of homes and neighborhood centers are hard to recognize because the trees and brush swamp those areas with reds. The Palos Verdes Estates section on the ocean is a good example. However, bands and patches of blue in the valleys, such as in the Santa Clara valley east of Ventura, indicate commercial concentrations along highway strips.

The Transverse Range is quite an impressive backdrop for the citizens of the Greater Los Angeles area to look at from various spots in the basin. This next image is a perspective view of these mountains and most of the Los Angeles basin with its many metropolitan areas made by combining data from NASA JPL’s SRTM radar mission (see Section 11) with an enhanced image acquired by Landsat-5.

A perspective 3-D view of the Transverse Ranges and part of the Los Angeles Basin, made by combining Landsat-5 with SRTM radar data.

Urban areas are quite distinctive in radar imagery, as is clearly evidenced in this 1978 Seasat image (see Section 8 for a description of this satellite and a review of radar interpretive principles) that covers the west side of the Los Angeles metropolitan area. To aid in recognizing landmarks within the image, we include a segment of the 1989 Rand McNally atlas map that locates roadways, towns, and other features in the urban infrastructure.

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Seasat radar image of the western Los Angeles metropolitan area, 1978.

Rand McNally map of the western Los Angeles metropolitan area, 1989.


It also helps to show a ground photo of some part of a city or metropolitan area to tie in with the space imagery. We will do this for many of the cities (especially in the U.S.) in this Section. Here is a view of downtown Los Angeles:

Panorama of downtown Los Angeles.

Many of the dark linear features in this radar image correspond to interstate highways and other major roadways. The two dark, narrow, east-west strips just on shore at Santa Monica Bay are runways at Los Angeles International Airport. These dark patterns come from specular (smooth) reflecting surfaces that deflect most of the radar beam away from the receiving platform. Generally, buildings return much of the radar signal, giving rise to an intermediate gray tonal signature (uniform here because most individual buildings are not resolved). Very light patterns are associated with high levels of backscatter caused, in some instances, by stands of vegetation. The light pattern along the west coast of the Palos Verdes peninsula, a luxuriant residential area may come from dense vegetation. However, the very bright, squarish pattern at the east end of the Santa Monica Mountains that extends into the San Fernando Valley around Burbank-Glendale is rather mysterious. It approximately coincides on the map with Griffith Park, north of Hollywood, but its position relative to roadways that are discernible in the radar image, indicates an inexact fit (possibly an effect of non-rectification).

` <>`__4-3:Again, use an atlas and turn to the pages that show the Greater Los Angeles region (as does Rand-McNally). Try to locate the various Interstates and Freeways. Find such places as the Santa Monica Mountains, Glendale, central Los Angeles, Torrance, Long Beach. You will probably note that the road patterns in the radar image don’t fit too well with the map - some main roads are not clearly singled in the image. Care to guess why this is so? What are the bright patterns protruding into the ocean at Long Beach? `ANSWER <Sect4_answers.html#4-3>`__

Even the lower resolution subscenes created from MSS images are effective ways of manifesting the major features of urban areas, such as street patterns, large buildings, airports, recreational parks, and some industrial facilities. This effect is certainly evident in this March 30, 1975, MSS view of the central parts of San Diego in southernmost California. It shows the Bay harbors, military and civilian airports, the downtown, Balboa Park, Mission Bay, and Cabrillo Point.

Downtown San Diego, a Landsat-2 subscene

But, the value of much higher resolution to discerning metropolitan features down to the individual building scale is convincingly revealed by this November 22, 1988, SPOT image of inner San Diego, in which the three multispectral HRV band images, at 20 m (66 ft) resolution, are combined and registered with the 10 m (33 ft) panchromatic image taken simultaneously. The details in this image are persuasive proof that civilian space imagery can match, at least, the smaller scale aerial photos in clarity and information content.

SPOT subscene of approximately the same part of downtown San Diego as shown above.

Many who live or visit San Diego consider it the ideal metropolitan area in the United States in which to live. Its climate is famed for its moderate temperatures and high frequency of sunny days. Its downtown waterfront skyline, shown below, defines its modern fast growth.

Looking east across the harbor at downtown San Diego.

` <>`__4-4: First, with the help of your atlas, locate the San Diego landmarks mentioned above. Then, look at the U.S. Naval Air Station at the broad North Island at the end of the sea spit that makes up the Coronado area west of San Diego Bay. Using both the MSS and SPOT renditions, note any changes you can detect on this Island. Look for another change to the north. **ANSWER**

We now look at another major western, urban area in a somewhat different setting, Tucson, Arizona, nestled between mountains on three sides:

Central Tucson with the Tucson Mountains in the background

Much of the city displayed here in a Landsat TM False Color Composite subscene extending about 58 km (36 mi) east-to-west, sits on nearly flat terrain, wedged in by several large alluvial fans from the southeast and north. The latter fan actually is becoming a major residential suburb, noted for fine homes amidst dissected canyons. The entire city area was built up from stream deposits coming off the surrounding mountains.

Landsat TM false color composite showing a broad valley framed by the Santa Catalina Mountains to the north of Tucson, AZ (checkered area).

Many prominent, wide streets criss-cross the town, being laid out on the surveyor’s section (one square mile) lines in the Township System. From the east, the Rio Rillito joins the Santa Cruz river (north-south) just north of the city’s center. Tucson’s International Airport sits to the south, about five miles from Davis-Monthan Air Force Base to its northeast. North of the city are the Santa Catalina Mountains, rising to 2800 m (9184 ft) at Mt. Lemmon, where citizens of this desert town in a basin around 825 m (2706 ft) can ski in the winter. The tip of the Rincon Mountains touches the eastern edge of the city, and the scattered hills of the Tucson Mountains extend to the west. Copper mining is a major regional industry, as evidenced by the dark fan-shaped lake and the bluish-white open-extraction pits of the Pima Mission Mines to the south.

` <>`__4-5: Much of the greater Tucson area has a brownish tone. Why? **ANSWER**

An even more dramatic example of building a city from “scratch” is found near the southern tip of the next state to the northwest of Arizona. Here in the midst of a flat desert basin surrounded by mountains lies the gambling heart of North America, Las Vegas, Nevada. This rapidly growing urban area now exceeds a million in population. Water to nourish this “oasis” is drawn from Lake Mead, behind the Hoover Dam.

Landsat subscene showing the dry desert area within which Las Vegas, NV is now expanding; Spring Mountains to the west (left).

Las Vegas is built around a long avenue known as the “Strip”, seen here during its prime time at night. You should be able to pick out that narrow area in the Landsat image.

The Las Vegas Strip at night.

To see a very large but detailed image (Terra’s ASTER) of Las Vegas, press here (this avoids an initial download that would have lengthened the time to complete this page; if you access the image, press BACK to return to this page).

In the 1960s the writer visited the Strip many times enroute to the Nevada Test Site, some 80 miles to the north, where he conducted his examination of the effects of underground nuclear explosions while working at the Lawrence Livermore Laboratory. Here is an IKONOS image of part of the Strip (near top of image); McCarron Field is in the lower left.

IKONOS image of part of the Las Vegas Strip.

IKONOS can produce images with even higher resolution. But the one available online is made by Digital Globe’s Quickbird-2, achieving a resolution of 0.68 m. Shown here is the 28-story twin towers of the Exalibur Hotel, on the Strip, and opened in June of 1990.

Quickbird 2-ft resolution image of the Excalibur Hotel on the Las Vegas Strip.

In 1972, Las Vegas had about 270,000 residents; by 1992 the city had grown to more than 900,000. Growth of the city is evident in comparing a 1972 Landsat subscene to one acquired in 1992.

Las Vegas, 1972 Las Vegas, 1992

The writer (NMS) would be remiss if he did not include a (Landsat) image of El Paso, TX. This is where he spent a fascinating 18 months right after World War II in an anti-aircraft battalion at Fort Bliss (4th Army). El Paso is the dark bluish-gray area near the bottom left in the upper right quadrant of the image. Across from it is the Mexican town of Juarez (very popular nightlife for the soldiers). The Rio Grande, dividing New Mexico-Texas from our southern neighbor, is marked by the patchwork of farms using irrigation from that river. Volcanic flows are evident in the almost uninhabited desert to the west. The blue patches are normally dry (playa) lakes temporarily covered with a few inches of monsoon rain water. El Paso is sited at the bottom end of the Franklin Mountains; next up to the north is the Organ Mountains, near which was the firing range for the 90 mm AA guns his unit was responsible for. The area covered by El Paso-Juarez has grown by at least 50% since 1947:

Landsat image containing El Paso, TX, the Rio Grande, and surrounding desert.

Thus, America’s Southwest and West Coast are among the fastest growing in population within this country. This is brought home by the next image, a change detection depiction of part of San Jose, California, a city that has more than doubled in size since 1973.

Population change in San Jose, California

This next image, made by the Landsat 7 ETM+, was added on December 7, 2001, the 60th anniversary of the Pearl Harbor attack. This is the southern part of the island of Oahu (see page 17-3 for image of Hawaiian Islands). What surprised the writer (NMS), who has never been to this State, is the relatively small size of Honolulu.

The southern part of the Island of Oahu.


Primary Author: Nicholas M. Short, Sr. email: nmshort@nationi.net
Collaborators: Code 935 NASA GSFC, GST, USAF Academy