Mapping our land more clearly and colourfully
for better analysis and visualisation

Acknowledging Landsat

NASA: Landsat

USGS: Landsat


Landsat-8 launch

Landsat-8 liftoff in February 2013

Earth Observation (EO) is the most effective way to monitor the environment of our changing home planet. The latest significant contributions by the U.S. and the European Union countries are the successful lunch and operation of Landsat-8 and Sentinel-2 satellites. Their high-quality and rich multispectral data covering very large acquisition areas are freely available and provide enormous opportunities for innovation and applications. They are "YOUR satellites" and highly complementary (even competitive for many applications) to high-resolution imaging.

We wish to help users quickly realise the full potential of the latest Landsat and Sentinel imagery. Our aim is to develop the highest-quality 10m-resolution Sentinel-2 and 15m-resolution Landsat-8 imagery composites (in natural and false colours). Quality matters!

To request the trial version of the software now: To request software download



Some generous user comments:

"Your software made my job easy." (Comment from a user)

"I like what I've seen of this software so far! I do a ton of image processing and analysis daily, and this makes stacking and sharpening much simpler than in arcgis, envi, or photoshop (best results so far, then I found yours)... Thanks for your time, and the software!" (Email from an industry veteran, March 2016)

"It is a very impressive piece of software and created very crisp and natural looking images." (Comment from an industry veteran)

"Thank you for an excellent product. I have used other pan-sharpeners and yours beats them all." (Email from an industry veteran, January 2016)

"I have found ST for Landsat-8 Imagery to be my most useful tool in working with the OLI images. Thanks for developing these tools!." (Email from a retired industry veteran, January 2016)"

"I am using your Spectral Transformer and all works perfectly. Many thanks to you for this great and accurate tool." (Comments from a user)

"I enjoy your GUI tool. It's like an App on PC and the first button click acts as simple as the 'voice' input in Google search." (Comment from an industry veteran)

I recently downloaded the Spectral Transformer for Landsat 8 software... thoroughly impressed with the ease of use, speed and quality of the results..." (Email from a senior image processing specialist, January 2016)





































Spectral Discovery for Landsat-8 Imagery



Advanced image stretching and pan-sharpening software to easily and rapidly make colourful and detail-rich (15m-resolution) Landsat-8 imagery composite, with 2 simple button clicks

  • Popular software for geospatial professionals and general users. It is productive and saves time!
  • Functions include band combinations, image stretching, image pan-sharpening, and exploratory image feature extraction. Perfect software tool to get the daily fresh Landsat-8 imagery into GIS and remote sensing software, and Google Earth Pro.
  • Version 2.0 released in 01/2016 (renamed from Spectral Transformer to Spectral Discovery in 08/2016)
    • 1 button click for automated NDVI calculation, with 3 types of outputs (demo)
    • 1 button click for automated extraction of surface water areas, with 3 types of outputs (demo)
    • batch processing
  • Updated 19/12//2016: Supporting the Landsat-8 data (in compressed GeoTIFF format) downloaded from AWS S3 Landsat-8 portal.
GUI software - Spectral Discovery for Landsat-8 Imagery

Landsat-8 Image Sources

The U.S. Geological Survey (USGS) distributes daily Landsat-8 data in three very accessible ways:

Recently, there are other avenues to rapidly download Landsat-8 imagery, e.g.

Libra (recommended for casual users, no registration required), EarthExplorer and GloVis provide Landsat-8 imagery data (all in uncompressed GeoTIFF format typically included in a single / bundled zip file), which can be directly analysed by Spectral Discovery software. For the Landsat-8 Level-1 standard data product, a pixel is most commonly represented by a Digital Number, not the true reflectance of land surface.

The Landsat-8 data from AWS S3 is in compressed GeoTIFF format. The software uses the conversion tool included in open GIS software QGIS to make format conversion.

The USGS Landsat portal provides comprehensive FAQs in relation to the new Landsat-8 imagery and its comparison with the previous Landsat series. It is important to read these before conducting proper image processing. Landsat-8 products are delivered as 16-bit images with the panchromatic band at 15m resolution and multispectral bands at 30m resolution, and band combinations are unique (e.g. bands 4/3/2 refer to red/green/blue, respectively, useful for making natural colour composite).

An overview of some common band combinations for better discrimination of various ground features is provided here, there, but one should not be limited by given prescriptions.

Landsat-8 band combinations

New Image Analysis Software Tools

While the imagery source is magnificent, more work needs to be progressed on how to use the imagery in a straightforward way.

There are many remote sensing and image processing software tools on the market, but it is fair to say that very few can efficiently make beautiful, detail-rich imagery composites with adaptive image histogram stretching and advanced image pan-sharpening. One may spend hours to produce something that is of high quality.

For many GIS users, it is often hard to find right capable tools (i.e. band combination, image stretching and image pan-sharpening) in GIS software packages.

And for casual users and the general public, dedicated tools to process the vast Landsat imagery archive are lacking.


Spectral Discovery for Landsat-8 Imagery fill in this gap.

Standalone tool set performs a few critical steps of analyses:

  • Step 1 - Band combination (to make three-band imagery composite)
  • Step 2 - Image histogram stretching (to make colourful composite)
  • Step 3 - Image pan-sharpening (to make colourful and spatially sharper composite)
  • Step 4 - Exploratory image feature extraction with image feature indices (e.g. NDVI and NDWI) and band ratios

We believe these tools are very useful for a wide range of users who are interested in analysing the latest Landsat-8 imagery. These powerful and easy-to-use tools specifically target Landsat-8 imagery in GeoTIFF format directly downloaded from the USGS Landsat-8 distribution portals (e.g. USGS EarthExplorer or USGS GloVis) and Libra.

Step 1: Simple and convenient band combination to make three-band imagery composite

<red_band_in> <green_band_in> <blue_band_in> <RGB_out.tif>

e.g. Landsat8_RGB.exe b4.tif b3.tif b2.tif RGB_b432.tif
(for true colour)

e.g. Landsat8_RGB.exe b5.tif b4.tif b3.tif CIR_b543.tif
(for colour infrared)
e.g. Landsat8_RGB.exe b7.tif b5.tif b3.tif FC_b753.tif
(for false colour)


Step 2: Adaptive linear and non-linear image histogram stretching over the three-band imagery composite

<red_band_order> <green_band_order> <blue_band_order> -s
<image_stretch_band1_left_cut> <image_stretch_band1_right_cut> <image_stretch_band2_left_cut> <image_stretch_band2_right_cut> <image_stretch_band3_left_cut> <image_stretch_band3_right_cut> <nonlinear_stretch_band1>
<RGB_in.tif> <RGB_stretched_out.tif>

e.g. Landsat8_Stretch.exe 1 2 3 -s 2 0.2 2 0.2 2 0.2 2 2 2
RGB_b432.tif RGB_b432_stretched_res30m.tif
e.g. Landsat8_Stretch.exe 1 2 3 -s 2 0.2 2 0.2 2 0.2 0 0 0
RGB_b432.tif RGB_b432_stretched_res30m.tif

e.g. Landsat8_Stretch.exe 1 2 3 -s 0 0 0 0 0 0 0 0 0
RGB_b432.tif RGB_b432_stretched_res30m.tif


Step 3: Advanced and fast image pan-sharpening

<pan-sharpening_method> -s
<image_stretch_band1_left_cut> <image_stretch_band1_right_cut> <image_stretch_band2_left_cut> <image_stretch_band2_right_cut> <image_stretch_band3_left_cut> <image_stretch_band3_right_cut> <nonlinear_stretch_band1>

<pan_band_in.tif> <ms_in.tif> <fused_out.tif>

e.g. Landsat8_Fuse.exe 1 -s 2 0.2 2 0.2 2 0.2 2 2 2
b8.tif RGB_b432.tif RGB_b432_fused_res15m.tif


Step 4: Calculating image feature indices and band ratios

<calculation_method> <input_band1.tif> <input_band2.tif> <threshold>

e.g. Landsat8_Feature.exe 1 b3.tif b6.tif 0.1


Details about the options of the tools can be found in the software User Guide (PDF):



  • For a scene with little cloud cover or fewer white objects, these image stretching options (-s 2 0.2 2 0.2 2 0.2 5 5 5) would suffice. If a scene contains a large proportion of white objects (e.g. cloud and snow), try to increase the right-end cut-off values in image histogram stretching for their exclusion.
  • To improve the brightness of the imagery composite, one may increase non-linear stretching values to 10, 20, 30 and so on.
  • The first pan-sharpening method (1) would perform better for the majority of cases. This choice may be subject to the size of image objects in the scene (i.e. ground features).
  • Output files from image stretching and pan-sharpening, if exist, will be over-written automatically.
  • The same procedure equally works for any three-band combinations. Through iterations, any number of multispectral bands can be fused and pan-sharpened.
  • To avoid typing long file names in DOS console, one can simply drag files to the console.
  • One may prepare DOS batch files to efficiently run tools with various image stretching and pan-sharpening options.
  • The band combinations and image stretching tools may be used to process the generic 8- or 16-bit remote sensing imagery.


Run time:

Spectral Discovery for Landsat-8 Imagery is very productive. The time to process a full Landsat-8 scene on an average office computer is only about 1 minute (with minimal memory usage). Detailed estimates are as follows:
  • Step 1 (band combination): 1-5 seconds
  • Step 2 (image stretching): 5-20 seconds
  • Step 3 (image pan-sharpening): 15-90 seconds


It is with great privilege that we all have access to such a superior imagery source. We are motivated and have tried our best to develop the tools that can preserve that high quality as much as possible.

We are confident that anyone even with little image processing experience can perform the above analysis. It is our hope that more people can take advantage of and benefit from the excellent Landsat-8 imagery. Thank you, NASA and the USGS!

Rapid Processing for Innovative Applications

This unique software can be used for for a wide range of environmental studies, including:

  • Monitoring land cover changes (e.g. deforestation and urban expansion)
  • Mining exploration and mineral detection with SWIR bands
  • Precision agriculture and vegetation mapping (e.g. NDVI)
  • Natural hazards (e.g. fire scar mapping, flooding, volcanic eruption)
  • Updating GIS basemaps with the latest fresh imagery

Two more button clicks: To rapidly make 120 or 336 band combinations using Landsat-8's full spectral bands in a batch mode:

  • 120 = 6x5x4, using 6 multispectral bands - Bands 2, 3, 4, 5, 6, 7 (~20GB disk space required for each scene)
  • 336 = 8x7x6, using 8 multispectral bands - Bands 1, 2, 3, 4, 5, 6, 7, 9 (~60GB disk space required for each scene)

A simple yet extremely powerful way of image (visual) analysis: Through rapid, various band combinations, important features/phenomena of interest on Earth land surface can be better highlighted and revealed.

Example 1: Mapping fire scars (burnt areas) with numerous band combinations in an automated procedure. Left: The extent of fire scars being clearly revealed by Bands 7/5/3; Right: Natural-colour image with Bands 5/4/3. Location: Point Mugu State Park, California; Image source: Landsat-8 (scene DATE_ACQUIRED = 2013-05-13).


Example 2: Animated view of 336 band combinations (=8x7x6) of a full Landsat-8 scene (using 8 bands)


See the Detail: Advanced Image Fusion and Pan-sharpening

Example 3: Pan-sharpening of Landsat-8 imagery from coarse 30m-resolution (Left) to very sharp 15m-resolution (Right). Location: San Francisco; Image source: Landsat-8 (scene DATE_ACQUIRED = 2013-04-16).


See the Invisible: Exploring Unique Short-wave Infrared Bands

Landsat-8 short-wave infrared (SWIR) bands are capable of detecting wildfire hot spots and lava flows/heat through smoke.

Example 4: Holuhraun Lava Field, Iceland (DATE_ACQUIRED = 2014-09-06). Left: Natural-colour composite (showing full smoke); Right: false-colour composite (containing SWIR bands)


See Features of Interest (FOI): From Pixels to Information

Exploratory image feature extraction with image indices (e.g. Normalised Difference Vegetation Index - NDVI, Normalised Difference Water Index - NDWI, Normalised Difference Urban Index, Normalised Difference Snow Index, Burned Area Index) and various band ratios, for a wide range of environmental studies.

Example 5: Classifying and estimating water surface areas in an automated procedure. Left: Extracted water surface shown in light blue; Right: Natural-colour image with RGB bands. Location: Sundarban, Bangladesh; Image source: Landsat-8 (scene DATE_ACQUIRED = 2015-11-12).


See the Big Picture: Using Global Imagery Mosaics

Need a global satellite imagery mosaic? Please take a look at the high-quality global satellite imagery mosaics (30m-resolution, multiple styles) in ELS2000 series.

Automated, exploratory land cover classifications at 30m and 15m resolutions, at the global scale (ongoing)

Land cover changes

Near real-time / daily monitoring



Others: Processed Samples

Truly natural-colour, full-scene examples for the "Vivid Earth" series - To view our land more clearly and colourfully!


Full scene overview

Full-scene raw imagery data courtesy of the USGS. All in GeoTIFF format downloaded from the USGS GloVis





Comparison and evaluation

Please evaluate the quality of the processed imagery (stretched and pan-sharpened) in terms of:

- spectral consistency
- colour saturation
- colour contrast

- spatial precision

- object detail
- spatial sharpness

- spatial texture

Be the judge on the performance of the tools. Quality Matters!

Full-scene, pan-sharpened result at 15m resolution in GeoTIFF, ready to be used in all GIS and mapping software (e.g. QGIS, ArcGIS, MapInfo), popular image-editing software (e.g. PhotoShop), and Google Earth Pro.

For demonstration, three GIS-ready, compressed formats are included in the zip file:

- JPG (plus *.wld file)
- JPEG2000
- KMZ (Google Earth)

San Francisco
Zip file 

LANDSAT_SCENE_ID = "LC80440342013106LGN00"


stretching option:
-s 2 0.2 2 0.2 2 0.2 5 5 5

Los Angeles
Zip file 

LANDSAT_SCENE_ID = "LC80410362013133LGN01"

DATE_ACQUIRED = 2013-05-13

stretching option:
-s 2 0.2 2 0.2 2 0.2 5 5 5
New York
Zip file  

LANDSAT_SCENE_ID = "LC80140322013152LGN00"

DATE_ACQUIRED = 2013-06-01

stretching option:
-s 2 0.2 2 0.2 2 0.2 20 20 20

Washington D.C.
Zip file  

LANDSAT_SCENE_ID = "LC80150332013111LGN01"

DATE_ACQUIRED = 2013-04-21

stretching option:
-s 2 0.2 2 0.2 2 0.2 10 10 10

The Alps, Europe
Zip file  

LANDSAT_SCENE_ID = "LC81960282013115LGN01"

DATE_ACQUIRED = 2013-04-25

stretching option:
-s 2 2 2 2 2 2 20 20 20

Shanghai, China
Zip file  

LANDSAT_SCENE_ID = "LC81180382013145LGN00"

DATE_ACQUIRED = 2013-05-25

stretching option:
-s 2 5 2 5 2 5 5 5 5

Sydney, Australia

Newcastle, Australia
(beautiful beach waves + scary river plumes in "3D")

Zip file 

LANDSAT_SCENE_ID = "LC80890832013117LGN01"

DATE_ACQUIRED = 2013-04-27

stretching option:
-s 2 0.2 2 0.2 2 0.2 2 2 2

Download all above comparison images Zip file

The size of each processed full scene in a compressed form is only about 5% of that of the raw data in GeoTIFF format.

bands 5/4/3

Equally works for all other band combinations

bands 7/5/3

Download all comparison images Zip file


Two formats included in the following zip files:

- JPG (plus *.wld file)
- KMZ (Google Earth)

Hong Kong and the Pearl River Delta, China

Zip file  

LANDSAT_SCENE_ID = "LC81220442013333LGN00"

DATE_ACQUIRED = 2013-11-29

Auto parameterisation

Seoul, South Korea

Zip file  

LANDSAT_SCENE_ID = "LC81160342013259LGN00"

DATE_ACQUIRED = 2013-09-16

Auto parameterisation


It only takes about 1 minute to process each full scene on an ordinary computer. All daily scenes can be processed as above and efficiently delivered as soon as they are available in the following formats (for professionals in remote sensing and GIS fields, as well as the general public):

  • Conventional GeoTIFF
  • JPEG2000
  • KMZ (Google Earth)
  • Various web mapping tilesets, e.g. Google Map Tiles, Bing Maps Tiles, OSM Tiles, TMS Tiles

the potential for the broadest use of the new Landsat-8 imagery is great.


"An enormous amount of spatial data sets has been produced and explored already, but the future for a bright, sustained geospatial industry and location intelligence business critically depends on the quality of spatial data."

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