Satellite imagery: Landsat 8 and its Band Combinations.

Satellite imagery: Landsat 8 and its Band Combinations.

Posted on 08 Dec 2016

By: Olga Makarova,
PR Manager, OpenWeather.

In the current version of the VANE Language, we use images from the Landsat 8 satellite, which captures the Earth’s entire surface every 16 days. The satellite makes hundreds of images, with a unique name for each one (such as “LC81410552016219LGN00”) and a pixel size of 30 metres. Each image consists of 11 bands; the size of an uncompressed image is 2 GB.

Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images consist of nine spectral bands with a spatial resolution of 30 metres for Bands 1 to 7 and 9. New Band 1 (ultra-blue) is useful for coastal and aerosol studies, and also new Band 9 is applicable for cirrus cloud detection. The resolution of Band 8 (panchromatic) is 15 metres. Thermal Bands 10 and 11 provide more accurate surface temperatures and are collected at 100 metres. The approximate scene size is 170 km north–south by 183 km east–west (106 by 114 miles).

By default, we get Bands 2, 3, 4, 5 and 7, but it is possible to download any other bands.

Updated! We have combined our satellite imagery into one simple and fast Satellite Imagery API. Satellite images (True and False colour, NDVI, EVI), historical data, etc. More information here!

Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) – launched 11 February 2013

Bands

Wavelength
(micrometres)

Resolution
(metres)

Band 1 – Coastal aerosol

0.43 – 0.45

30

Band 2 – Blue

0.45 – 0.51

30

Band 3 – Green

0.53 – 0.59

30

Band 4 – Red

0.64 – 0.67

30

Band 5 – Near Infrared (NIR)

0.85 – 0.88

30

Band 6 – SWIR 1

1.57 – 1.65

30

Band 7 – SWIR 2

2.11 – 2.29

30

Band 8 – Panchromatic

0.50 – 0.68

15

Band 9 – Cirrus

1.36 – 1.38

30

Band 10 – Thermal Infrared (TIRS) 1

10.60 – 11.19

100 * (30)

Band 11 – Thermal Infrared (TIRS) 2

11.50 – 12.51

100 * (30)


Let’s consider how these bands and their combinations can be used to display Landsat 8 images.

Bands 2, 3 and 4

The blue, green and red spectra combine together to create full-colour images.

One of the simplest operations is to generate an RGB map. Here an image consists of Bands 4-3-2, which correspond to the well-known RGB colour model.

Image #1: France, a spot near Toulouse.

http://owm.io/sql-viewer?lat=44.4949&lon=1.1175&zoom=13&select=b4,b3,b2&op=rgb&from=l8&tabActive=2

Image #2: The Sahara desert.

http://owm.io/sql-viewer?lat=21.11&lon=-11.39&zoom=9&where=day%3E2016-09-01,day%3C2016-09-10&select=b4,b3,b2&op=rgb&from=l8&tabActive=1

Band 5

Near Infrared (NIR) – this part of the spectrum is one of the most frequently used, as healthy plants reflect it the most: the water in their leaves scatters the wavelengths back into the sky. This information is useful for vegetation analysis. By matching this band with others, one can get indexes such as NDVI, which provide more precise measurement of plant condition compared with looking only at the visible greenness.

5, 4, 3 – Traditional Colour Infrared (CIR) image

Please note how the healthier vegetation appears more clearly in a brighter shade of red. This band combination is often used for remote sensing of agricultural land, forest and wetlands.

Let’s look at image #1 in the 5-4-3 band combination.

http://owm.io/sql-viewer?lat=44.4949&lon=1.1175&zoom=13&select=b5,b4,b3&op=rgb&from=l8&tabActive=2

Band 7The Shortwave Infrared (SWIR2)

Spectra Shortwave Infrared lets you clearly distinguish wet soil from dry soil, and also differentiates the Earth’s structure: rocks and soils that can look almost similar in other bands have a strong distinction in SWIR.   

We get the following picture if we take Image #2 and use infrared band 7 instead of red band 4:

http://owm.io/sql-viewer?lat=21.1767&lon=-11.5192&zoom=9&where=day%3E2016-09-01,day%3C2016-09-10&select=b7,b3,b2&op=rgb&from=l8&tabActive=2

5, 4, 3 – False colour image — "False colour" is a rendering using the NIR (near infrared) band that is more useful for showing land cover and differentiating it from urban and farmland areas. In these images, it is possible to pick out different types of vegetation. Also easily discernible is the boundary between land and water, which enables changes in shorelines to be tracked.

Compare the image below, made in the essential RGB colours, with the ones that follow it:

http://owm.io/sql-viewer?lat=60.9358&lon=59.3948&zoom=9&select=b4,b3,b2&op=rgb&from=l8&tabActive=2

And here is the 5-4-3 band combination:

https://owm.io/sql-viewer?lat=60.9398&lon=59.2108&zoom=9&op=falsecolor&from=l8&tabActive=2

7, 5, 2 – False colour image

This band combination is convenient for monitoring agricultural crops, which are displayed in bright green. Bare earth is shown in purple, while uncultivated vegetation appears in subtle green.  

http://owm.io/sql-viewer?lat=60.9358&lon=59.3948&zoom=9&select=b7,b5,b2&op=rgb&from=l8&tabActive=2

7, 5, 3 – False colour image 

This false colour image shows the land in orange and green colours, ice is depicted in beaming purple, and water appears in blue. This band combination is similar to the 7-5-2 one, but the former shows vegetation in brighter shades of green.   

http://owm.io/sql-viewer?lat=60.9358&lon=59.3948&zoom=9&select=b7,b5,b3&op=rgb&from=l8&tabActive=2


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