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Posted on December 25, 2022 (Updated on July 22, 2025)

Calculating LST from Landsat 8 image collection in Google Earth Engine?

Hiking & Activities

Decoding Earth’s Skin: Calculating Land Surface Temperature with Landsat 8 and Google Earth Engine

Ever wondered how hot the Earth’s surface really is? I mean, really is, not just what the weather app tells you about the air temperature. Land Surface Temperature (LST) gives us that granular view. It’s like taking the Earth’s temperature directly on its “skin,” and it’s a game-changer for understanding everything from climate change to city planning.

Why should you care? Well, LST is a key player in how our planet manages energy. It helps us track climate change impacts, understand those sweltering urban heat islands, and even figure out when plants are stressed out from lack of water. And thanks to Google Earth Engine (GEE), crunching the numbers on satellite images to get this data has become surprisingly accessible.

Let’s talk about Landsat 8. This satellite, launched back in 2013, is a workhorse for Earth observation. It’s got two main eyes: the Operational Land Imager (OLI) for visible and infrared light, and the Thermal Infrared Sensor (TIRS) specifically for measuring temperature.

TIRS is the cool part (pun intended!). It uses two thermal bands to sense the heat radiating off the Earth:

  • Band 10: Peeking at wavelengths around 10.8 µm
  • Band 11: Checking out wavelengths around 12.0 µm

What’s neat is that Landsat 8 has two thermal bands, unlike older Landsats with just one. This gives us more accurate temperature readings. The data comes in at a 100-meter resolution, but it’s often tweaked to match the 30-meter resolution of the other bands for easier analysis.

Now, how do we actually get the LST data using Google Earth Engine? It’s easier than you might think.

First, you’ll need a GEE account. Once you’re in:

  • Define the area you’re interested in – your Area of Interest (AOI).
  • Pull in the Landsat 8 data collection, specifying the date range you want to analyze.
  • GEE lets you filter the data by date, location, and even cloud cover. Trust me, you want to filter out those cloudy images!

    Okay, time for the math. Don’t worry, GEE does most of the heavy lifting. Here’s the general idea:

  • From Numbers to Radiance: The satellite records data as Digital Numbers (DN). We need to convert these to Top-of-Atmosphere (TOA) Radiance using calibration data that comes with the images.
  • Radiance to Temperature: Next, we convert that radiance into Brightness Temperature, which is essentially the temperature a perfect black object would need to be to emit that much energy. We use something called the Planck function for this. To get the temperature in Celsius, just subtract 273.15 from the Kelvin value.
  • Emissivity Correction: This is where it gets a bit tricky. Different surfaces emit heat differently. We need to account for this using Land Surface Emissivity (LSE). A common way to estimate LSE is using the Normalized Difference Vegetation Index (NDVI), which tells us how much vegetation is in an area.
    • Calculate NDVI using the red and near-infrared bands.
    • Figure out the Proportion of Vegetation (PV) from those NDVI values.
    • Estimate LSE using a formula like: LSE = 0.004 * PV + 0.986.
  • Final LST Calculation: Finally, we combine the brightness temperature and LSE to get the Land Surface Temperature. There are different algorithms you can use here, like the mono-window algorithm.
  • So, what can you do with LST data once you have it? Plenty!

    • Urban Heat Islands: Spotting those pockets of intense heat in cities.
    • Climate Change: Tracking temperature trends over time.
    • Agriculture: Checking if crops are thirsty or stressed.
    • Environmental Studies: Understanding how water evaporates and how energy flows on the Earth’s surface.

    In a nutshell, calculating LST from Landsat 8 in Google Earth Engine opens up a world of possibilities for understanding our planet. It’s a powerful tool, and with GEE, it’s more accessible than ever. So dive in, explore the data, and see what you can discover about the Earth’s ever-changing temperature!

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