Resolution: A key technical indicator for the application value of remote sensing imagery

In the operation of remote sensing satellites, the main function is to use sensors mounted on remote sensing platforms to record the electromagnetic wave information emitted or reflected by target objects, thereby forming remote sensing images. Among these, resolution, as a measure of the sensor imaging system's ability to distinguish details in the output image, is an important technical indicator of the application value of remote sensing images. Different measures of "image detail" result in various types of resolution, mainly including spatial resolution, spectral resolution, temporal resolution, and radiometric resolution.

 Spatial resolution：Zoom in again and again to make the satellite's "eyes" even sharper.

Spatial resolution refers to the pixel detail of an image, specifically the smallest target or feature a sensor can distinguish. It represents the area of ​​the ground corresponding to one pixel in a satellite-observed image. It determines the ability to discern spatial detail in remote sensing images; higher spatial resolution means more detail and smaller pixel sizes.

▲ An image of the Yunnan Dianchi International Convention and Exhibition Center taken by my country's Gaofen-1 satellite, achieving a spatial resolution of 0.5m.

High spatial resolution images play a crucial role in target feature identification and visual interpretation. Generally, the closer to the observed object, the clearer the image, which is closely related to the orbital altitude of the detector. Furthermore, the spatial resolution is also related to the aperture size of the camera on the detector. To achieve both clear images and a wider field of view, the detector needs to be in a higher orbit to see a larger area clearly.

Spectral resolution

By observing the smallest details, satellites become "eagle eyes."

Spectral resolution is the ability to distinguish spectral details of ground objects in an image; it is the smallest wavelength interval that a satellite sensor can distinguish when receiving the spectral spectrum of a ground object.

Smaller intervals result in higher spectral resolution. Within the same spectral range, generally, the more image bands, the higher the spectral resolution. High spectral resolution means satellite detectors can identify more objects; hyperspectral imagery often has higher spectral resolution than multispectral imagery. This ability to detect minute details, like having a keen eye, is crucial for the classification and identification of ground features in imagery.

Time resolution：Taking pictures while rotating makes the satellite more agile.

Temporal resolution refers to the ability to repeatedly observe the same location, and is the time required for a satellite to complete a full orbital operation. It is also commonly referred to as the revisit period; the shorter the revisit period, the higher the temporal resolution, and the more complete the information collected by the detector.

▲my country's successfully developed Gaofen-4 satellite can basically achieve real-time Earth observation.

Since most targets are moving, non-stationary targets, without sufficient temporal resolution, by the time the detector returns to investigate, the target will have already disappeared. Therefore, high temporal resolution plays an important role in detecting dynamic changes in ground features.

When the probe is in a geostationary orbit, its angular velocity will be the same as the Earth's rotational angular velocity, allowing it to continuously observe from the same location.

Radiometric resolution：Meticulous observation of subtle changes in radiant energy.

Radiometric resolution, or sensor sensitivity, refers to a sensor's ability to distinguish the smallest difference between two radiation intensities. The higher the radiometric resolution of a sensor, the stronger its ability to detect minute changes in the energy of radiation reflected or emitted by ground objects. In remote sensing images, this is represented by the radiometric quantization level of each pixel.

The distribution of pixels in remote sensing satellite images reflects the spatial structure of the image, and its radiation characteristics describe the information contained in the image, i.e., the image obtained by the sensor or film.

As the eyes of space, remote sensing satellites have greatly broadened people's ability to understand and perceive the universe. With the continuous development of science and technology, their technical indicators are also constantly improving. It is believed that these ever-upgrading eyes will contribute value and strength to more fields in the future, and provide assistance for mankind's continuous exploration of the Earth and even the universe.