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Section 1 is the key or pivotal "chapter" in this Tutorial, in that you will be introduced to two prime approaches in the use of remote sensing: 1) standard photo-interpretation of scene content, and 2) use of digital image processing and classification techniques that are generally the mainstay of practical applications of information extracted from sensor data sets. To accomplish this, we will utilize just one Landsat TM subscene that covers the Morro Bay (MB) area on the south-central coast of California. On this first page, a full Landsat TM image and one TM band (3) subscene image, both showing Morro Bay, are displayed. The concept of plotting its gray scale values or digital numbers (DN) is exemplified, and a brief description of the geographic setting of MB is given.



Assuming that you have read the preceding Introduction to remote sensing, you should be ready to work with the basics that image interpreters apply to examining and analyzing an image . In this section we concentrate on analyzing a single Landsat image - a subscene of Morro Bay, California. Because this is a major learning experience for most readers, we scrutinize this image and its derivatives more intensely than most of the others in later Sections. We demonstrate and evaluate several of the routine analysis techniques used in computer processing of satellite remote sensing data (see end of page 1-20 for a brief list of books on the principles of image processing). For this subscene, Idrisi is the processing software used to generate all image products. However, you will get a chance to do your own processing of the Morro Bay TM images by using the PIT program, explained in Appendix B, and with a supplement that will "walk" you through its use on the Morro Bay image set.

At the outset, we want to give you an option, namely to run through a Website that is brief but comprehensive in its treatment of the basics of image processing of remotely sensed data. This preview may help you as we apply these ideas to the Morro Bay image. To choose this path, just click on this Canadian Soonet link.

Morro Bay in Context

The chosen subscene lies along the central California coast about half way between San Francisco and Los Angeles, in the county of San Luis Obispo. Before looking at the subscene, it is appropriate to locate it in a full Landsat scene. Below is a "true color" Landsat image acquired on December 8, 1982 that shows the California Coast, the Coast Ranges, and a small segment of the San Joaquin Valley. At the top left is part of Monterrey Bay. At the very bottom, on the coast, is Morro Bay itself. As seen here, almost the entire area included in the subscene (from a different date) is present but appears so tiny in this small scale full scene that it may prove hard for you to make it out.

November 1982 Full Landsat TM of south-central California coast, with Morro Bay at bottom center.

TM Natural Color Image of Morro Bay, California

We extracted this subscene acquired on November 19, 1984 from Landsat 5 Thematic Mapper scene 5026-31810 (Path 043; Row 035: these are the locational coordinates used in the Worldwide Reference System [WRS], which for Landsats 1, 2, and 3 [18 day repeat cycle] divides the orbital paths into 251 adjacent paths each pair 160 km apart; rows are numbered from 0 [poles] to 60 [equator]) . The actual data set is part of the Education sampler offered to users by the Space Imaging Corp. (the company has merged with another called Eosat that is located in Lanham, MD; Eosat, which produced a collection of TM imagery for educational uses, including the Morro Bay subscene, no longer supplies this set). To acquaint yourself with this subscene, look at the black and white TM Band 3 image which has been enlarged to a convenient size to allow you to look for details and specific features singled out later in the Section.

TM Band 3 image of Morro Bay, California

TM Band 3

1-1: After finding this subscene in the full image above, locate Morro Bay on the California map in a U.S. Atlas. Familiarize yourself with the area that includes the subscene and with the surrounding region (up to about 162 km [100 miles]). ANSWER

The subscene consists of a 512 x 512 pixel array (because each pixel represents 30 m [98ft] each side of the image is just over 16 kilometers [10 miles] long). Below is a histogram giving a frequency distribution of the brightness values in Band 3. The abscissa plots the spread of brightness values, specified by their Digital Numbers (see page 1-12) or DNs that, in a black and white Landsat TM image, ranges from 0 (black) to 255 (white) with numbers from 1 to 254 representing gray levels in progressively increasing lightness.

1-2: Analyze this histogram. What do its peaks represent? If the DNs shown along the abscissa were the ones used to produce a black and white image, what would it look like? ANSWER


Histogram of the TM Band 3 image shown above.

  The largest town in the image is Morro Bay, a resort community of about 10,000 permanent residents, some of whom are still actively involved in commercial fishing. The town is located about 21 km (13 miles) NW of the city of San Luis Obispo, along the conspicuous road evident in the scene (the famed coastal Highway 1 which wanders along much of the California coastline but in this scene extends inland to the east). The second major road, California Highway 41, is visible as it passes through a valley between hills enroute to Atascadero 27.5 km (17 miles) to the NE of Morro Bay. Cayucos is a small residential town along the coast just north of Morro Bay. Near the bottom of the image is another large settlement, the town of Los Osos (and its northern neighbor, Baywood Park), which is popular now as a retirement community, especially the areas along hillsides with commanding views of the ocean.

Assuming you didn't locate Morro Bay on the California State Map (first question above), this map version extracts the immediate area and should help to get your bearings relative to the above description.

Map of Morro Bay and its surroundings.

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Primary Author: Nicholas M. Short, Sr. email:

Collaborators: Code 935 NASA GSFC, GST, USAF Academy
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