TimeScan, DLR

TimeScan is a GeoService developed by the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR). It provides a first impression of the main land cover characteristics and can support geospatial analysts and service providers to generate advanced land cover and land use classifications faster and with higher reliability.

Based on Landsat-8 data, TimeScan scans the time series of all available datasets within the selected analysis period. It calculates most significant spectral indices and calculates their statistics over time for each spot. It comes in two flavours: TimeScan Basic is a false color composite of the main indicators for built-up areas (red) water bodies (blue) and vegetation (green). TimeScan Professional provides a detailed statistical analysis for the selected spectral indices in addition.

TimeScan is available off the shelf for Africa and Germany 2013-2014, if you like to get TimeScan for other areas or other time periods, visit our GeoService TimeScan on Demand.

Recommended use 

With TimeScan basic everyone gets an impressive visualisation of the main landcover characteristics with a false color representation of the indicators for built-up areas or bare soil (mean of NDBI), for water bodies (mean NDWI) and vegetation (mean NDVI).

TimeScan professional supports value adders in remote sensing for a broad spectrum of use cases. For each spectral index users get statistical parameters over time. It is expected that with this intermediate product, final classifications can be generated quicker and with higher accuracy. Application areas are land use/land cover mapping, agriculture, forestry, risk management, as well as disaster monitoring, defense and security, and natural resource management.

Product description 

TimeScan is based on time series of Landsat data from the years 2013 and 2014, and partially from 2015 and 2016. Before indices and temporal statistics are calculated, cloud masking is performed to all scenes. The TimeScan output condenses the information contained in TeraBytes of pixels to a single output with a fraction of the original data volume. This is particularly relevant for achieving continuous environmental monitoring based on extensive time series of earth observation data.

TimeScan Basic 

TimeScan Basic is a false color composite of the main indicators for built-up areas (red), water bodies (blue) and vegetation (green). As main indicator the mean of NDBI, NDWI and NDVI is used.
Demo: Subset of TimeScan Basic as WMS (East 15 South 25)


Indicator: Built-up area
The Normalized Difference Built-Up Index (NDBI) highlights urban areas, which typically have a higher reflectance in the shortwave-infrared (SWIR) region, compared to the near-infrared (NIR) region. Applications include watershed runoff predictions and land-use planning.


The NDBI was originally developed for use with Landsat TM bands 5 and 4. However, it will work with any multispectral sensor with a SWIR band between 1.55-1.75 µm and a NIR band between 0.76-0.9 µm.1
All statistics on NDBI are saved in TimeScan Professional with the following band IDs:

  • Band__1: Max NDBI
  • Band__2: Min NDBI
  • Band__3: Mean NDBI
  • Band__4: SD NDBI
  • Band__5: MASD NDBI

Indicator: Water bodies
The Modified Normalized Difference Water Index (MNDWI) enhances open-water features while suppressing noise from built-up land, vegetation, and soil. Xu2 reported that the MNDWI produced better results than the Normalized Difference Water Index3 in enhancing and extracting water from a background that is dominated by built-up land areas.

MNDWI = (Green - SWIR) / (Green + SWIR)

Here are some guidelines for interpreting MNDWI results:

  • Open water has greater positive values than NDWI, as it absorbs more shortwave-infrared (SWIR) wavelengths than near-infrared (NIR) wavelengths.
  • Built-up features have negative values.
  • Soil and vegetation have negative values, as soil reflects more SWIR wavelengths than NIR wavelengths.

The MNDWI was originally developed for use with Landsat TM bands 2 and 5. However, it will work with any multispectral sensor with a green band between 0.5-0.6 µm and a SWIR band between 1.55-1.75 µm.
All statistics on MNDWI are saved in TimeScan Professional in the following band IDs:

  • Band__6: Max MNDWI
  • Band__7: Min MNDWI
  • Band__8: Mean MNDWI
  • Band__9: SD MNDWI
  • Band_10: MASD MNDWI

Indicator: Vegetation
The Normalized Difference Vegetation Index (NDVI) is a measure of healthy green vegetation. The combination of its normalized difference formulation and use of the highest absorption and reflectance regions of chlorophyll make it robust over a wide range of conditions. It can, however, saturate in dense vegetation conditions when the leaf area index (LAI) becomes high.

NDVI = (NIR - Red) / (NIR + Red)

The value of this index ranges from -1 to 1. The common range for green vegetation is 0.2 to 0.8.4
All statistics on NDVI are saved in TimeScan Professional in the following band IDs:

  • Band_11: Max NDVI
  • Band_12: Min NDVI
  • Band_13: Mean NDVI
  • Band_14: SD NDVI
  • Band_15: MASD NDVI

Spectral Index: ND57
The Normalized Difference Middle Infrared (ND57 or NDMIR)5 is the ratio of the Landsat-8 band 5 vs band 7.


All statistics on ND57 are saved in TimeScan Professional in the following band IDs:

  • Band_16: Max ND57
  • Band_17: Min ND57
  • Band_18: Mean ND57
  • Band_19: SD ND57
  • Band_20: MASD ND57

Spectral Index: ND42
The Normalized Difference Red Blue (ND42 or NDRB)6 is the ratio of the Landsat-8 band 4 vs band 2.

(NDRB) = (Red-Blue)/(Red+Blue)

All statistics on ND42 are saved in TimeScan Professional in the following band IDs:

  • Band_21: Max ND42
  • Band_22: Min ND42
  • Band_23: Mean ND42
  • Band_24: SD ND42
  • Band_25: MASD ND42

Spectral Index: ND32
The Normalized Difference Green Blue (ND32 or NDGB)6 is the ratio of the Landsat-8 band 3 vs band 2.

(NDGB) = (Green-Blue)/(Green+Blue)

All statistics on ND32 are saved in TimeScan Professional in following band IDs:

  • Band_26: Max ND32
  • Band_27: Min ND32
  • Band_28: Mean ND32
  • Band_29: SD ND32
  • Band_30: MASD ND32

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Off the shelf 

Africa 2013-2014, Germany 2013-2014


30 m

Access mode 

Filetransfer, Webservice



Delivery time 

A few hours



1) Zha, Y., J. Gao, and S. Ni. "Use of Normalized Difference Built-Up Index in Automatically Mapping Urban Areas from TM Imagery." International Journal of Remote Sensing 24, no. 3 (2003): 583-594.

2) Xu, H. "Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery." International Journal of Remote Sensing 27, No. 14 (2006): 3025-3033.

3) McFeeters, S. "The use of Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features." International Journal of Remote Sensing 17 (1996): 1425-1432.

4) Rouse, J., R. Haas, J. Schell, and D. Deering. Monitoring Vegetation Systems in the Great Plains with ERTS. Third ERTS Symposium, NASA (1973): 309-317.

5) D. Lu, P. Mausel, E. Brondizio and E. Moran. "Change detection techniques" International Journal of Remote Sensing, vol. 25, no. 12 (2003): 2365-2407.

6) Zhou, Weiqi & Qian, Yuguo & Li, Xiaoma & Li, Weifeng & Han, Lijian. (2014). Relationships between land cover and the surface urban heat island: Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures. Landscape Ecology. 29. . 10.1007/s10980-013-9950-5.

Source of spectral indices description: Harris Geospatial Solutions

Please note 

The product is developed within the project OPUS. Any feedback on the usability of this project will be greatly appreciated by the project team.
Please let us know if you encounter any problems at service@cloudeo-ag.com. We are happy to get your feedback.

Pricing / Licensing