In remote sensing, resolution refers to the size of the smallest feature that can be detected in an image. Resolution is an important consideration when choosing a remote sensing platform or sensor, as it determines the level of detail that can be observed in an image. Higher-resolution images contain more detailed information and can distinguish smaller features, while lower-resolution images may not have enough detail to distinguish smaller features.
There are four types of resolution in remote sensing: spatial resolution, spectral resolution, temporal resolution, and radiometric resolution
- Spatial Resolution: It refers to the size of the smallest feature that can be distinguished in an image, and is typically measured in units of distance, such as meters or feet. High spatial resolution images can distinguish smaller features, while low spatial resolution images can only distinguish larger features.
Some examples of spatial resolution in remote sensing include:
- A satellite image with a spatial resolution of 30 meters per pixel can distinguish features that are at least 30 meters in size.
- An aerial photograph with a spatial resolution of 1 meter per pixel can distinguish features that are at least 1 meter in size.
- A laser scanning system with a spatial resolution of 10 centimetres per pixel can distinguish features that are at least 10 centimetres in size.
- Spectral Resolution: It refers to the number of discrete wavelength intervals that are used to capture the electromagnetic spectrum, and is typically measured in units of nanometers (nm). High spectral resolution images can distinguish between different materials or substances based on their unique spectral signatures, while low spectral resolution images may not have enough detail to differentiate between different materials.
Some examples of spectral resolution in remote sensing include:
- A satellite image with a spectral resolution of 10 nanometers per band can distinguish between materials with slightly different spectral signatures, such as different types of vegetation.
- An aerial photograph with a spectral resolution of 50 nanometers per band may not have enough detail to distinguish between different types of vegetation.
- A hyperspectral sensor with a spectral resolution of 1 nanometer per band can distinguish between very small differences in the spectral signatures of materials, such as different types of minerals.
- Temporal Resolution: It refers to the frequency at which images are collected over time. High temporal resolution images are collected frequently, allowing for the detection of short-term changes or events, while low temporal resolution images are collected less frequently and may not be able to detect short-term changes.
Some examples of temporal resolution in remote sensing include:
- A satellite image with a temporal resolution of once per day can be used to detect long-term changes, such as the growth of a city over several years.
- A drone with a temporal resolution of once per hour can be used to detect shorter-term changes, such as the movement of vehicles on a road.
- A camera with a temporal resolution of once per minute can be used to detect very short-term changes, such as the movement of clouds in the sky.
- Radiometric Resolution: It refers to the number of bits used to represent the digital values of an image. High radiometric resolution images have more bits per pixel, allowing for a larger range of digital values and a greater ability to distinguish between different materials or substances. Low radiometric resolution images may not have enough bits per pixel to accurately represent the full range of digital values in an image.
Some examples of radiometric resolution in remote sensing include:
- An image with 8 bits per pixel has a radiometric resolution of 8 bits and can represent 256 different digital values (2 to the power of 8).
- An image with 12 bits per pixel has a radiometric resolution of 12 bits and can represent 4096 different digital values (2 to the power of 12).
- An image with 16 bits per pixel has a radiometric resolution of 16 bits and can represent 65536 different digital values (2 to the power of 16).