The challenge to monitor changing temperatures in urban and rural areas has never been more real or important. Most commonly, temperature readings are taken by measuring the temperature of the air. However, this has a major drawback in that it cannot account for variation of temperature on different surfaces and materials. To do so, Land Surface Temperature (LST) is required. LST readings are generally obtained through remote sensing observations from satellites, which offer the benefit of monitoring cities, regions and nations at scale and at regular intervals. What differentiates D-CAT’s LST product is the unparalleled spatial resolution of 15m enabling more precise spatial insights.

There are two main sources of satellite LST data: ESA's Sentinel-3 and NASA's Landsat 8. Sentinel-3 offers a resolution of 1km and LST is available directly from the satellite. This resolution is considered too low for monitoring LST in cities, for example, or other common applications such as agriculture. Landsat 8 offers a resolution of 100m, but the temperature data is not available directly from the satellite without radiometric processing as well as atmospheric correction being applied.

We offer such processed Landsat 8 LST images which are ready to use, with the added benefit of significantly improved spatial resolution. Using state-of-the-art image processing techniques, we have created an algorithm which produces LST images with a resolution of 15m instead of the standard 100m resolution that Landsat 8 provides. This allows the user to gain more insight from their area of interest, and to monitor areas with more spatial precision than other LST products whilst maintaining very high accuracy in temperature measurement.

Below are two animations demonstrating our proprietary algorithm being applied to images taken over Prague and Singapore during 2019. The algorithm not only gives temporal LST readings of the regions of interest, but also removes clouds and shadows from the images which would otherwise give invalid LST readings if not removed.



The graphs below show the average LST readings of Prague and Singapore during 2019.

The full set of this example data is available for free on AWS Data Exchange (ADX)D-CAT offers a service, fulfilled through ADX that can supply this data for any area or region.


By using this service clients:

Example Applications


Monitoring when crops are exposed to extreme temperatures gives farmers insight as to when to take action to minimise the amount of stress or damage done to the plants. This can range from very high temperatures which cause the plants to lose moisture and dry up, to very low temperatures which cause frost damage.

Weather and Climate Change

LST is particularly useful in monitoring weather and climate change. It allows features such as glaciers to be monitored which would otherwise be very difficult to monitor using conventional methods.

Smart Cities

Providing a reliable LST reading every 15m provides valuable insights to city planners, developers and architects. This innovative approach to recording localised ground temperature across a whole city and urban area means the city can detect, identify and monitor urban heat islands with greater precision whilst avoiding the overhead of creating a larger network of meteorological stations or IoT sensor costs to capture this data.

For more details about our products and services please get in touch.



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