Get started with imagery

Get familiar with the Esri Landsat Viewer app

First, you'll open the Esri Landsat Viewer app and become familiar with the notion of spectral band combination.

  1. Open the Esri Landsat app.

    Default Landsat app


    To learn more about the Esri Landsat Viewer app, click About in the lower left corner of the app. You can also learn more about the Landsat program, jointly run by the United States Geological Survey (USGS) and NASA, on the program's home page.

    The app opens to the location of Esri headquarters in Redlands, California. You notice right away that the landscape does not appear in colors that look natural, the way they would appear to the human eye. The urban areas are light purple, while some of the vegetated areas are bright green. Why is that so?

    The Landsat satellite imagery captures different ranges of wavelengths on the electromagnetic spectrum, including some that are invisible to the human eye. Each range is stored separately in a spectral band and is particularly good at highlighting a type of landscape feature or property. The bands are described in the following table:

    BandNameWhat this band shows best



    Shallow water, fine dust particles



    Deep water, atmosphere






    Manufactured objects, soil, vegetation


    Near Infrared (NIR)

    Shorelines, vegetation


    Shortwave Infrared 1 (SWIR 1)

    Cloud penetration, soil and vegetation moisture


    Shortwave Infrared 2 (SWIR 2)

    Improved cloud penetration, soil and vegetation moisture



    Cirrus clouds

    You can then combine the bands into spectral band combinations.

  2. In the vertical toolbar on the left, hover over the currently selected Agriculture button.

    Agriculture button

    By default, the app uses the Agriculture band combination (bands 6, 5, and 2—or Shortwave Infrared 1, Near Infrared, and Blue). That combination highlights healthy agriculture vegetation in bright green and distinguishes it clearly from other land cover types like bare earth or urban. It is the option that is currently on. You'll now switch to the Natural Color band combination for comparison.

  3. In the toolbar, click Natural Color.

    Natural Color button

    With this new Natural Color band combination (bands 4, 3, and 2—or Red, Green, and Blue), you can see that the imagery is dominated by earth-colored tones. Together, the Red, Green, and Blue bands make up the spectrum of light visible to the human eye. Combining these three bands approximates how the landscape would look to a person.

    Redlands in Natural Color view

    The Natural Color band combination can be useful for some applications, but analysts often choose other band combinations based on the specific features they want to highlight. The toolbar on the left lists several common band combinations available in the app.

You'll continue to explore the power of spectral band combinations by navigating to the Sundarbans mangrove forest.

Monitor mangroves in the Sundarbans

Your next destination will be the Sundarbans mangrove forest on the border of India and Bangladesh. With Landsat's imagery capabilities, you'll monitor the health of the mangroves in an ecosystem highly susceptible to change.

  1. At the bottom of the toolbar, click the Bookmarks button.

    Bookmarks button

    A window opens, containing a list of bookmarks to interesting locations around the world.

  2. In the Bookmarks window, scroll down and click Sundarbans.

    Sundarbans bookmark

    The map extent changes from Redlands to the Sundarbans. The entire area you now see is part of the Sundarbans mangrove region.

  3. Close the Bookmarks window.
  4. In the upper left corner of the map viewer, click Zoom Out button a few times, until you see the label for the city of Kolkota in the northwest.

    Zoom in button


    You can also zoom in or out using the mouse's wheel button.

    Just from observing the area with the default Natural Color band combination, you can see a clear distinction between the heavily forested Sundarbans region and the highly urbanized city of Kolkata to the northwest. Much of the original mangrove forest was cut down, but what remains is protected by the Indian and Bangladeshi governments.

    The Sundarbans zoomed in


    Since satellites can't capture the entire world in one picture, they take multiple pictures that are then stitched together into a patchwork image called a mosaic. You may see the diagonal lines that divide different images. Also, because the images were taken at different dates and times, the color intensity may differ from one to the other.

    To distinguish the mangrove vegetation more clearly, you'll use the Color Infrared band combination, which combines the bands 5, 4, and 3 (or Near Infrared, Red, and Green). The Near Infrared (NIR) band distinguishes very clearly between vegetation (high value) and nonvegetation features (low value). As you can see on the spectral profile graph below, typical Forest, Urban, and Water features have very different NIR values.

    Color Infrared band combination

    Healthy vegetation appears bright red in the Color Infrared band combination.

  5. In the toolbar, click Color Infrared.

    Color Infrared button

    The imagery updates.

    Sundarbans with Color Infrared band combination

    The mangrove forest now appears bright red, signifying dense, overall healthy vegetation. The water bodies going through the mangrove—devoid of vegetation but high in sediments—appear turquoise blue. Built-up areas, such as the city of Kolkata, appear grayish or beige. Areas with agriculture appear as a lighter shade of red, signifying some vegetation presence, but less dense than in the mangrove.

  6. Zoom in to the heart of the mangrove forest.

    Mangrove forest zoomed in


    Since Landsat imagery is refreshed on a regular basis with more recent images (every two weeks on average), it could be that the most current image for an area of the Sundarbans happens to be a bit cloudy or hazy. If so, pan with the mouse to another area of the mangrove forest that appears clearer.

    Now you can see the mangrove forest in more detail. Over the broad delta region, the forest is broken up by several rivers and complex tidal waterways. Many of its small islands are accessible only by boat, which hinders on-the-ground observation and intensifies the need for satellite imagery to monitor the forest.

    Healthier vegetation appears brighter red, but some areas appear in a lighter shade of red or beige. As an analyst, you could identify these areas as containing potentially less healthy vegetation and needing further investigation.

  7. Zoom in and out and pan to explore various areas of the mangrove.
  8. Go to the east side of the mangrove, where the color changes dramatically from mostly red to mostly beige.

    Forested and deforested areas

    You can see a sharp contrast where the protected mangrove area ends: the land in the nonprotected area was formerly covered with mangrove forest but has now been entirely deforested. It shows as mostly beige or light pink, signifying an absence of vegetation. As an analyst, you could use these differences in color to detect illegal tree logging activity in the protected areas.

    Mangrove forests are highly susceptible to changes in sea level and water salinity, as well as pollution, illegal logging, and other factors. Loss of mangroves would not only compromise the habitat of the diverse species of flora and fauna that live there (including many endangered species, such as the Bengal tiger), but also remove an important shield against monsoons for the neighboring localities. It is important to maintain the health of the forest, and imagery can help do that.


    What is the difference between the Color Infrared band combination and the Agriculture band combination that you used earlier in the tutorial? Both are good at highlighting healthy vegetation (in bright red for Color Infrared and bright green for Agriculture). Color Infrared is a more common band combination that is available for many types of satellite and aerial imagery, as it only requires a Near Infrared (NIR) band, besides the green and red visible light bands. The Agriculture band combination is less common, because it requires not only a NIR band but also a Shortwave Infrared (SWIR) one. The presence of the SWIR band makes it better at capturing the soil and vegetation moisture level, and it is also better at penetrating clouds.

Find an oasis in the Takla Makan Desert

Vegetation is not the only thing imagery can monitor. Next, you'll travel to China's Takla Makan Desert and observe moisture levels in the arid locale.

  1. In the toolbar, click Bookmarks. In the Bookmarks window, scroll down to and click the Takla Makan Desert bookmark.

    The map extent changes.

  2. Close the Bookmarks window.

    Takla Makan Desert, China

    The boundaries of the oval-shaped desert are fairly clear, even when displayed in Natural Color. Since the Takla Makan Desert is primarily made up of sand dunes, its surface appears smooth and uniform from above, with few mountains or geological features. While the desert appears dry, you'll determine whether there are areas of moisture using the moisture index.


    With Landsat imagery being updated on regular intervals, your images may appear different from the example images, due to cloud cover or seasonal weather patterns.

    Bright white areas represent clouds, and there might be more or less of them in the current scene you are observing.

  3. In the toolbar, click Moisture Index.

    Takla Makan Desert displayed with Moisture Index.

    Unlike Color Infrared, which was only a combination of three different spectral bands, the Moisture Index is a more sophisticated use of spectral bands. It is an index, which is a calculation that computes a ratio between different bands. In the case of Moisture Index, the bands involved are 5 (NIR) and 6 (SWIR 1), and the formula is as follows:


    If the NIR band value is higher than the SWIR 1 band value, the result of the formula will be a higher (positive) value, denoting a high moisture level. Otherwise, it will be a lower (negative) value, denoting a low moisture level. As you can see on the graph below, Lush Grass and Water features will typically result in a positive value, and Desert features in a negative value.

    NIR and SWIR 1 bands for Desert, Lush Grass and Water features

    On the map, the Moisture Index shows moisture-rich areas in blue tones, and low moisture areas in orange tones. As expected, most of the Takla Makan Desert appears low moisture. However, the Moisture Index reveals several places that aren't as dry as they seemed with Natural Color. You'll ignore the darkest navy blue patches at the periphery, because they correspond to clouds (these are the clouds that were previously showing in white in the Natural Color view). Instead, you'll take a closer look at some of the medium blue patches, which signal actual ground-level moisture.

  4. Zoom to the area of moisture on the west side of the desert, outlined in the image below.

    Moisture-rich area in the Takla Makan Desert


    To zoom to a specific extent, press the Shift key while you draw a box around the area you want to zoom to.

    You zoom to a place labeled on the map as Shache.

    Shache area close up

    Shache is an oasis settlement fed by a river that runs down the nearby mountains. The Moisture Index shows that this area has a fair amount of moisture overall (although the exact amount might vary depending on the season). The Moisture Index is a great tool for monitoring drought levels and measuring desertification trends.


    As you zoomed in, the Shache area may have gone from medium blue to dark blue. The reason is that the colors are chosen based on the features that currently show on the map. When there was a high cloud presence, they were the highest moisture features and were showing in the darkest blue tones. Now that most of the clouds are outside the map extent, the Shache oasis becomes the highest moisture feature and is therefore colored in dark blue. This type of rendering is called Dynamic Range Adjustment or DRA.

    To reveal what the moisture in the Shache area is being used for, you'll use the Agriculture band combination.

  5. In the toolbar, click Agriculture. Zoom in once or twice, until your view is similar to the one in the image below.

    Shache area with Agriculture band combination

    As seen in earlier sections, the Agriculture band combination (bands 6, 5, and 2, or SWIR 1, NIR, and Blue) highlights agriculture in bright green. Most of the moisture-rich area you saw when using the Moisture Index coincides with the agriculture presence that you now see in bright green. However, you can now also see the location of the river and tributary streams that irrigate this valley, clearly distinguished from the vegetated areas by their dark blue color.

    Using different band combinations and indexes allows you to uncover different types of information in the imagery.


    It's important to be judicious when making visual analysis of satellite imagery. For instance, the Moisture Index indicated some areas as moisture rich, simply due to the presence of clouds. Additionally, the Moisture Index could have missed areas with plentiful underground water that has not yet been tapped for agriculture. When done properly, interpretation of satellite imagery can uncover truths about the world, but it is important to understand its limitations as well.

See submerged islands in the Maldives

Landsat imagery can see underwater to a limited degree, creating images of shallow seafloor. To explore this capability, you'll travel to the Maldives, a small island nation off the coast of India. The Maldives is made up of over 1,000 small, low-lying islands. So low, in fact, that the entire nation is in danger of disappearing beneath the ocean if sea levels continue to rise. With the bathymetric imagery capabilities of Landsat, you'll see the submerged islands—and the ones in danger of being submerged.

  1. In the toolbar, click Bookmarks. In the Bookmarks window, scroll down to and click the Maldives bookmark.
  2. Close the Bookmarks window.

    The Maldives

    The imagery shows many small islands. The islands are formed out of coral and grouped into ring-shaped clusters called atolls. The Maldives bookmark has automatically made the Bathymetric band combination active. The Bathymetric band combination (bands 4, 3, and 1, or Red, Green, and Coastal) replaces Blue with the Coastal band, which emphasizes shallow underwater features. At the default extent, however, it's hard to tell what's underwater and what isn't.

  3. Zoom to the area labeled on the map as Malé, outlined in the following image.

    Malé (Maale)

    Malé (alternatively spelled Maale) is the capital and main city of the Maldives. After you zoom, you may be able to see built-up urban environments on some of the islands. If not, you can zoom in further.

    Built-up islands around Malé

  4. Pan and zoom to the Thilafushi island west of Malé.

    Thilafushi island.

    You can see that the east side of Thilafushi, in beige and brown tones, is above water and inhabited, while the west side of the island in light bluish tones is an uninhabited and mostly submerged reef. Next, you'll explore islands that are completely submerged.

  5. Pan north from Malé to see a large number of completely or almost completely submerged islands.

    Submerged islands

    The Bathymetric band combination increases the difference between submerged features (blue or turquoise blue) and emerged features (white, beige, or brown).

With Landsat imagery, you can monitor how sea level rise affects these low-lying islands. Although mathematical measurements of sea level rise would be a more exact indicator, satellite imagery can paint a persuasive and compelling picture of the real situation on the ground (or in the water). Islands are sinking worldwide due to the sea level rise caused by climate change. By mid-21st century, many low-lying atoll islands might become uninhabitable.

Track development on the Suez Canal

Until now, you've explored imagery that is a snapshot of a single instant, looking at the most recent Landsat images available. But what if you wanted to track trends over time? What if you wanted to compare mangrove health today and 10 years ago, or see if some of the submerged islands in the Maldives were above water in the past? The first Landsat satellite was launched in 1972, meaning that more than 40 years of Landsat imagery is available for comparison. While older satellites were not equipped with all of the capabilities of more recent satellites, including the ability to see certain spectral bands, their imagery can still be important for seeing how the world has changed. To illustrate that, you'll visualize the construction of an expansion to the Suez Canal in Egypt to increase its traffic capacity.

  1. In the toolbar, click Bookmarks. In the Bookmarks window, click the first bookmark, Suez Canal.
  2. Close the Bookmarks window.

    Suez Canal, Egypt

    The map shows a portion of the Suez Canal in the Agriculture band combination. Vegetation is shown in green, and water in black or dark blue. That segment of the canal was extended in 2014, and there are now two canals that run parallel to each other. The canal on the left is the original Suez Canal, opened in 1869. The canal on the right is the addition.

  3. In the toolbar, click the Time button.

    Time button

    The Time Line slider appears. The Time Line slider shows all available imagery from as far back in time as Landsat satellites captured imagery of this area, and it allows you to filter the imagery based on cloud cover or seasonality. The oldest image of this area, on the left of the timeline, is from September 19, 1984. Since Landsat imagery is updated periodically, the most recent image on the right may be different from the example image.

    Oldest and most recent image available


    You can drag the Time Line window to move it anywhere in the app to ensure it doesn't obstruct interesting features.

  4. For Cloud Filter, keep 10% Cloud.

    The Cloud Filter parameter allows you to choose how much cloud cover is acceptable when searching for imagery. In this case, any imagery with more than 10 percent cloud cover will be excluded.

  5. For Season Filter, keep All.

    The Season Filter parameter allows you to choose a specific season, such as spring or summer. For instance, when monitoring the evolution of a forested area over time, it can be useful to look at it only at summer dates, when the tree leaves are on.

  6. Click the left side of the Time Line window, just above the date, to view the oldest imagery from 1984.

    Suez Canal in 1984

    In the year 1984, no trace of the second canal existed. You'll scroll through the timeline to watch the second canal's development as it occurred.

  7. On the right side of Time Line, click the Plus button to move to the next image of the area chronologically.

    Plus button

    The next date with canal imagery is November 10, 2000, still long before the second canal's construction. One change to note is that agricultural activity (in green) has considerably increased in several locations.

  8. Continue clicking the Plus button until you reach November 10, 2014. Alternatively, you can also drag the time slider button with the pointer to move more quickly through time.

    Suez Canal in 2014

    Although faint, you can see the foundation of the second canal to the right of the first one.

  9. Continue clicking the Plus button to observe the canal's development over time.

    You can also notice further development in agricultural activities.

    When does the canal appear to be completed? How long did its construction take? Can you notice some changes in the agricultural methods used? By accessing the deep compendium of Landsat imagery, you can answer these questions, as well as other change-related questions across the world. Landsat imagery can track sea ice extent, lake water-level fluctuation, and urban development. It can also monitor seasonal changes, such as crop cycles and vegetation bloom. When combined with spectral band combinations, it increases the potential for imagery analysis even further.

  10. When you are finished exploring, close the Time Line window.

Create your own spectral view

You're not limited to using the preconfigured spectral band combinations and indexes. You can also build your own band combination to look at a place of interest in a new light.

  1. Use the Find a place search bar at the upper left of the map viewer to navigate to a location of interest to you.

    Find a place search capability


    When using the search bar, type the desired location using the following format: City, State or Region, Country.

    While you are encouraged to use any location in the world, the example images in these next few steps will use the default extent of Redlands, California. You can go there by clicking the Default Extent button below the Zoom Out button.

    Default Extent button

  2. In the toolbar, click the Build button.

    Build button

    The Build Your Own window appears. To create a band combination, you'll input the three bands to be combined. You can also adjust the stretch and gamma, which changes the contrast and brightness in the image. As a reminder, here is the list of the spectral bands available.

    Number Name What this band shows best



    Shallow water, fine dust particles



    Deep water, atmosphere






    Manmade objects, soil, vegetation


    Near Infrared (NIR)

    Shorelines, vegetation


    Shortwave Infrared (SWIR) 1

    Cloud penetration, soil and vegetation moisture


    Shortwave Infrared (SWIR) 2

    Improved cloud penetration, soil and vegetation moisture



    Cirrus clouds

    What bands should your combination use? It depends on what you want to see. For instance, if you want to emphasize vegetation, you can use the Near Infrared, Red, and Green bands—which happen to be the bands that make up the Color Infrared combination you used in the Sundarbans.

  3. Set the first band to NIR(5), the second band to Red(4), and the third band to Green(3). Click Apply.

    Build the Color Infrared band combination

    The imagery highlights vegetation as red, just as in the ready-made Color Infrared band combination. The order of the bands is also important, however. Because the human eye can only see the red, green, and blue ranges, those three bands (or channels) are the only ones that can be used to represent any spectral band combination. So, as you choose any three Landsat bands for your new combination, the first one will always be displayed through the Red channel, the second one through the Green channel, and the third one through the Blue channel. Together, they form a single composite image, as illustrated in the diagram below.

    How a composite image is created
    Composite image: A - Choose three Landsat bands to display; B - Assign them to the Red, Green, or Blue channel; C - Obtain a composite image.

    You'll now try the same bands in a different order.

  4. Set the first band to Green(3), the second band to Red(4), and the third band to NIR(5). Click Apply.

    Switched band order

    The same vegetation features are emphasized, but they are emphasized in blue instead of red. In general, the bands that are used determine what kinds of features are highlighted, while the order of the bands determines the color. Next, you'll try a new set of bands.

  5. Using the table above as a guide, put in your own combination of bands and click Apply.

    To help you choose the bands, you can also use the Identify function to examine the spectral profile of the features that interest you.

    What features are emphasized in the image? Are these the same features you would expect to see emphasized based on the bands you chose? If you reorder the bands, how does the color change?

  6. Try as many band combinations as you like. Adjust the stretch and gamma to see how the image contrast and brightness change.

    With the ability to make all sorts of band combinations, look at any location in the world, and tap into images extending back many years, the possibilities of Landsat imagery seem infinite.

  7. Close the Build Your Own window.

Explore more locations

The Landsat app includes several more bookmarked locations from around the world. These locations display dramatic or unique landscapes viewed through particular band combinations that highlight each location's most intriguing features. The remaining bookmarks include the following:

  • Cambridge Gulf, Australia
  • Eye of the Sahara, Mauritania
  • Gosses Bluff, Australia
  • Exumas, the Bahamas
  • Beijing, China
  • Mexico City, Mexico
  • Central Saudi Arabia
  • Bahr al Milh, Iraq
  • Bay of Gibraltar, the United Kingdom
  • Lake Chilwa, Malawi
  • Cuesta del Viento Reservoir, Argentina
  • Andasol Solar Power Station, Spain
  • Cubbie Station, Australia
  • New Islands in Dubai
  • Volcanoes in Chile

This tutorial won't take you through each bookmark, but you can discover them on your own or navigate to other areas around the world that you want to explore with spectral imagery.

In this tutorial, you discovered the capabilities of imagery, traveling around the world through the Esri Landsat Viewer app. You learned how different band combinations and indices allow you to monitor conditions and detect change anywhere on earth. You now have a better understanding of the vast applications of imagery and are ready to explore the world on your own.

You can find more tutorials like this on the Introduction to Imagery & Remote Sensing page.