Home » Remote Sensing » Spatial Resolution vs Spectral Resolution

Spatial Resolution vs Spectral Resolution

Spatial Resolution vs Spectral Resolution Feature

Spatial Resolution vs Spectral Resolution

What’s the difference between spatial resolution and spectral resolution?

Spatial resolution is a measurement of how detailed objects are in an image based on pixels.

Whereas spectral resolution is the amount of spectral detail in a band based on the number and width of spectral bands.

Let’s get into both concepts of image resolution with a bit more detail.

What is Spatial Resolution?

For spatial resolution, imagine gradually descending from a hot air balloon. As you descend, your eyes start recognizing features because everything is sharper. For any type of sensor, this means the spatial resolution is becoming finer.

Spatial resolution is the detail in pixels of an image. High spatial resolution means more detail and a smaller grid cell size. Whereas, lower spatial resolution means less detail and larger pixel size.

Spatial Resolution Comparison

Typically, drones capture images with one of the highest spatial resolutions. Even though satellites are highest in the atmosphere, they are still capable of 50 cm pixel size or greater like Worldview-3.

Overall, spatial resolution describes the quality of an image and how detailed objects are in an image. If the grid cells are smaller, this means the spatial resolution has more detail with more pixels.

What is Spectral Resolution?

Spectral resolution describes the amount of spectral detail in a band. High spectral resolution means its bands are more narrow. Whereas low spectral resolution has broader bands covering more of the spectrum.

For example, a multispectral image breaks light into 4 to 36 bands. Then, it assigns those bands names such as red, green, blue, and near-infrared. Each band may span 0.05 um in the electromagnetic spectrum.

Hyperspectral Example

Similarly, hyperspectral imaging captures a spectrum of light. But it divides the light into hundreds of narrow spectral bands. For hyperspectral images, spectral resolution is very high.

Spatial and Spectral Resolution Example

For example, Landsat-8 produces 11 images and each band consists of the following spectral resolution:

Band NumberDescriptionWavelengthResolution
Band 1Coastal / Aerosol0.433 to 0.453 µm30 meter
Band 2Visible blue0.450 to 0.515 µm30 meter
Band 3Visible green0.525 to 0.600 µm30 meter
Band 4Visible red0.630 to 0.680 µm30 meter
Band 5Near-infrared0.845 to 0.885 µm30 meter
Band 6Short wavelength infrared1.56 to 1.66 µm30 meter
Band 7Short wavelength infrared2.10 to 2.30 µm60 meter
Band 8Panchromatic0.50 to 0.68 µm15 meter
Band 9Cirrus1.36 to 1.39 µm30 meter
Band 10Long wavelength infrared10.3 to 11.3 µm100 meter
Band 11Long wavelength infrared11.5 to 12.5 µm100 meter

Each band has a spatial resolution of 30 meters except for bands 8, 10, and 11. While the panchromatic band has a spatial resolution of 15 meters, its thermal bands have a 100-meter pixel size.

Summary: Spatial Resolution vs Spectral Resolution

The difference between spatial resolution and spectral resolution is from pixel size and spectral detail.

Spectral resolution describes how much spectral detail is in each band such as hyperspectral or multispectral imaging.

Whereas spatial resolution represents the amount of detail of objects based on their pixel size.

Now that you’ve mastered these two concepts, learn more about remote sensing and image classification with some of our helpful articles below.

Subscribe to our newsletter:

2 Comments

Leave a Reply

Your email address will not be published. Required fields are marked *