Spatial and spectral resolution in remote sensing are both critical for specific applications. Both are advanced geospatial technologies with critical uses in geoimaging and other applications. However, spatial and spectral resolution are not the same. Learn more about how these two resolution methods work and which one is optimized for your applications.
Spatial vs. Spectral Resolution
Spatial resolution measures the number of pixels in a given area. Smaller pixels in a raster will look more detailed, while larger pixels will look more coarse. Consequently, higher spatial resolutions will provide clearer and more detailed images than lower resolutions.
Spectral resolution, on the other hand, is the ability of a sensor to identify fine wavelength intervals. It measures each band in a dataset within the electromagnetic spectrum. While some sensors will collect information within bands of uniform width, others will only take overall measurements.
Applications and Capabilities of Spatial Resolution
By measuring how detailed an object can appear in an image, spatial resolution can help identify imaging quality and accuracy. Effective spatial resolution will depend on how the displayed object interacts with the compression system.
In general, spatial resolution:
- Uses spatial combination features to create enhanced structural information
- Characterizes complex environments
- Identifies less reflective elements and registers strongly reflective elements as smaller than the image resolution